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What Are Quantitative Survey Questions? Types and Examples

Table of contents: 

• Types of quantitative survey questions - with examples 
• Quantitative question formats
• How to write quantitative survey questions 
• Examples of quantitative survey questions 

Leveraging quantilope for your quantitative survey 

In a quantitative research study brands will gather numeric data for most of their questions through formats like numerical scale questions or ranking questions. However, brands can also include some non-quantitative questions throughout their quantitative study - like open-ended questions, where respondents will type in their own feedback to a question prompt. Even so, open-ended answers can be numerically coded to sift through feedback easily (e.g. anyone who writes in 'Pepsi' in a soda study would be assigned the number '1', to look at Pepsi feedback as a whole).  One of the biggest benefits of using a quantitative research approach is that insights around a research topic can undergo statistical analysis; the same can’t be said for qualitative data like focus group feedback or interviews. Another major difference between quantitative and qualitative research methods is that quantitative surveys require respondents to choose from a limited number of choices in a close-ended question - generating clear, actionable takeaways. However, these distinct quantitative takeaways often pair well with freeform qualitative responses - making quant and qual a great team to use together.  The rest of this article focuses on quantitative research, taking a closer look at quantitative survey question types and question formats/layouts. 

Back to table of contents 

Types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions - with examples 

Quantitative questions come in many forms, each with different benefits depending on dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139784">your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives. Below we’ll explore some of these dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139785">survey question dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139785" data-dropdown-placement-param="top" data-term-id="281139785"> types, which are commonly used together in a single survey to keep things interesting for dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . The style of questioning used during dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139739">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139750">data dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139750" data-dropdown-placement-param="top" data-term-id="281139750"> collection is important, as a good mix of the right types of questions will deliver rich data, limit dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent fatigue, and optimize the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139757">response rate . dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">Questionnaires should be enjoyable - and varying the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755">types of dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139755" data-dropdown-placement-param="top" data-term-id="281139755">quantitative research dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755"> questions used throughout your survey will help achieve that. 

Descriptive survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139763">Descriptive research questions (also known as usage and attitude, or, U&A questions) seek a general indication or prediction about how a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139773">group of people behaves or will behave, how that group is characterized, or how a group thinks.

For example, a business might want to know what portion of adult men shave, and how often they do so. To find this out, they will survey men (the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience ) and ask descriptive questions about their frequency of shaving (e.g. daily, a few times a week, once per week, and so on.) Each of these frequencies get assigned a numerical ‘code’ so that it’s simple to chart and analyze the data later on; daily might be assigned ‘5’, a few times a week might be assigned ‘4’, and so on. That way, brands can create charts using the ‘top two’ and ‘bottom two’ values in a descriptive question to view these metrics side by side.

Another business might want to know how important local transit issues are to residents, so dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions will allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to indicate the degrees of opinion attached to various transit issues. Perhaps the transit business running this survey would use a sliding numeric scale to see how important a particular issue is.

Comparative survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139782">Comparative research questions are concerned with comparing individuals or groups of people based on one or more variables. These questions might be posed when a business wants to find out which segment of its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience might be more profitable, or which types of products might appeal to different sets of consumers.

For example, a business might want to know how the popularity of its chocolate bars is spread out across its entire customer base (i.e. do women prefer a certain flavor? Are children drawn to candy bars by certain packaging attributes? etc.). Questions in this case will be designed to profile and ‘compare’ segments of the market.

Other businesses might be looking to compare coffee consumption among older and younger consumers (i.e. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic segments), the difference in smartphone usage between younger men and women, or how women from different regions differ in their approach to skincare.

Relationship-based survey questions

As the name suggests, relationship-based survey questions are concerned with the relationship between two or more variables within one or more dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic groups. This might be a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link between one thing and the other - for example, the consumption of caffeine and dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents ’ reported energy levels throughout the day. In this case, a coffee or energy drink brand might be interested in how energy levels differ between those who drink their caffeinated line of beverages and those who drink decaf/non-caffeinated beverages.

Alternatively, it might be a case of two or more factors co-existing, without there necessarily being a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link - for example, a particular type of air freshener being more popular amongst a certain dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic (maybe one that is controlled wirelessly via Bluetooth is more popular among younger homeowners than one that’s plugged into the wall with no controls). Knowing that millennials favor air fresheners which have options for swapping out scents and setting up schedules would be valuable information for new product development.

Advanced method survey questions

Aside from descriptive, comparative, and relationship-based survey questions, brands can opt to include advanced methodologies in their quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire for richer depth. Though advanced methods are more complex in terms of the insights output, quantilope’s Consumer Intelligence Platform automates the setup and analysis of these methods so that researchers of any background or skillset can leverage them with ease.

With quantilope’s pre-programmed suite of 12 advanced methodologies , including MaxDiff , TURF , Implicit , and more, users can drag and drop any of these into a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire and customize for their own dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives.

For example, consider a beverage company that’s looking to expand its flavor profiles. This brand would benefit from a MaxDiff which forces dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to make tradeoff decisions between a set of flavors. A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent might say that coconut is their most-preferred flavor, and lime their least (when in a consideration set with strawberry), yet later on in the MaxDiff that same dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent may say Strawberry is their most-preferred flavor (over black cherry and kiwi). While this is just one example of an advanced method, instantly you can see how much richer and more actionable these quantitative metrics become compared to a standard usage and attitude question .

Advanced methods can be used alongside descriptive, comparison, or relationship questions to add a new layer of context wherever a business sees fit. Back to table of contents 

Quantitative question formats  

So we’ve covered the kinds of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative research questions you might want to answer using dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research , but how do these translate into the actual format of questions that you might include on your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire ?

Thinking ahead to your reporting process during your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire setup is actually quite important, as the available chart types differ among the types of questions asked; some question data is compatible with bar chart displays, others pie charts, others in trended line graphs, etc. Also consider how well the questions you’re asking will translate onto different devices that your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents might be using to complete the survey (mobile, PC, or tablet).

Single Select questions

Single select questions are the simplest form of quantitative questioning, as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents are asked to choose just one answer from a list of items, which tend to be ‘either/or’, ‘yes/no’, or ‘true/false’ questions. These questions are useful when you need to get a clear answer without any qualifying nuances.

Multi-select questions

Multi-select questions (aka, dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139767">multiple choice ) offer more flexibility for responses, allowing for a number of responses on a single question. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents can be asked to ‘check all that apply’ or a cap can be applied (e.g. ‘select up to 3 choices’).

For example:

Aside from asking text-based questions like the above examples, a brand could also use a single or multi-select question to ask respondents to select the image they prefer more (like different iterations of a logo design, packaging options, branding colors, etc.). 

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139766">scale dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139766" data-dropdown-placement-param="top" data-term-id="281139766"> questions

A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert scale   is widely used as a convenient and easy-to-interpret rating method. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents find it easy to indicate their degree of feelings by selecting the response they most identify with.

Slider scales

Slider scales are another good interactive way of formatting questions. They allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to customize their level of feeling about a question, with a bit more variance and nuance allowed than a numeric scale:

One particularly common use of a slider scale in a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139770">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139770" data-dropdown-placement-param="top" data-term-id="281139770"> study is known as a NPS (Net Promoter Score) - a way to measure dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139775">customer experience and loyalty . A 0-10 scale is used to ask customers how likely they are to recommend a brand’s product or services to others. The NPS score is calculated by subtracting the percentage of ‘detractors’ (those who respond with a 0-6) from the percentage of promoters (those who respond with a 9-10). dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents who select 7-8 are known as ‘passives’.

For example: 

Drag and drop questions

Drag-and-drop question formats are a more ‘gamified’ approach to survey capture as they ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to do more than simply check boxes or slide a scale. Drag-and-drop question formats are great for ranking exercises - asking dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to place answer options in a certain order by dragging with their mouse. For example, you could ask survey takers to put pizza toppings in order of preference by dragging options from a list of possible answers to a box displaying their personal preferences:

Matrix questions

Matrix   questions are a great way to consolidate a number of questions that ask for the same type of response (e.g. single select yes/no, true/false, or multi-select lists). They are mutually beneficial - making a survey look less daunting for the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent , and easier for a brand to set up than asking multiple separate questions.

Items in a matrix question are presented one by one, as respondents cycle through the pages selecting one answer for each coffee flavor shown. 

While the above example shows a single-matrix question - meaning a respondent can only select one answer per element (in this case, coffee flavors), a matrix setup can also be used for multiple-choice questions - allowing respondents to choose multiple answers per element shown, or for rating questions - allowing respondents to assign a rating (e.g. 1-5) for a list of elements at once.  Back to table of contents 

How to write dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

We’ve reviewed the types of questions you might ask in a quantitative survey, and how you might format those questions, but now for the actual crafting of the content.

When considering which questions to include in your survey, you’ll first want to establish what your research goals are and how these relate to your business goals. For example, thinking about the three types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions explained above - descriptive, comparative, and relationship-based - which type (or which combination) will best meet your research needs? The questions you ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents may be phrased in similar ways no matter what kind of layout you leverage, but you should have a good idea of how you’ll want to analyze the results as that will make it much easier to correctly set up your survey.

Quantitative questions tend to start with words like ‘how much,’ ‘how often,’ ‘to what degree,’ ‘what do you think of,’ ‘which of the following’ - anything that establishes what consumers do or think and that can be assigned a numerical code or value. Be sure to also include ‘other’ or ‘none of the above’ options in your quant questions, accommodating those who don’t feel the pre-set answers reflect their true opinion. As mentioned earlier, you can always include a small number of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139748">open-ended questions in your quant survey to account for any ideas or expanded feedback that the pre-coded questions don’t (or can’t) cover. Back to table of contents 

Examples of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">Quantitative survey questions impose limits on the answers that dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents can choose from, and this is a good thing when it comes to measuring consumer opinions on a large scale and comparing across dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . A large volume of freeform, open-ended answers is interesting when looking for themes from qualitative studies, but impractical to wade through when dealing with a large dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139756">sample size , and impossible to subject to dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139774">statistical analysis .

For example, a quantitative survey might aim to establish consumers' smartphone habits. This could include their frequency of buying a new smartphone, the considerations that drive purchase, which features they use their phone for, and how much they like their smartphone.

Some examples of quantitative survey questions relating to these habits would be:

Q. How often do you buy a new smartphone?

[single select question]

More than once per year

Every 1-2 years

Every 3-5 years

Every 6+ years

Q. Thinking about when you buy a smartphone, please rank the following factors in order of importance:

[drag and drop ranking question]

screen size

storage capacity

Q. How often do you use the following features on your smartphone?

[matrix question]

Q. How do you feel about your current smartphone?

[sliding scale]

I love it <-------> I hate it

Answers from these above questions, and others within the survey, would be analyzed to paint a picture of smartphone usage and attitude trends across a population and its sub-groups. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">Qualitative research might then be carried out to explore those findings further - for example, people’s detailed attitudes towards their smartphones, how they feel about the amount of time they spend on it, and how features could be improved. Back to table of contents 

quantilope’s Consumer Intelligence Platform specializes in automated, advanced survey insights so that researchers of any skill level can benefit from quick, high-quality consumer insights. With 12 advanced methods to choose from and a wide variety of quantitative question formats, quantilope is your one-stop-shop for all things dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research (including its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139776">in-depth dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">qualitative research solution - inColor ).

When it comes to building your survey, you decide how you want to go about it. You can start with a blank slate and drop questions into your survey from a pre-programmed list, or you can get a head start with a survey dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139765">template for a particular business use case (like concept testing ) and customize from there. Once your survey is ready to launch, simply specify your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience , connect any panel (quantilope is panel agnostic), and watch as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139783">answer questions in your survey in real-time by monitoring the fieldwork section of your project. AI-driven dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139764">data analysis takes the raw data and converts it into actionable findings so you never have to worry about manual calculations or statistical testing.

Whether you want to run your quantitative study entirely on your own or with the help of a classically trained research team member, the choice is yours on quantilope’s platform. For more information on how quantilope can help with your next dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139768">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139768" data-dropdown-placement-param="top" data-term-id="281139768"> project , get in touch below!

Get in touch to learn more about quantitative research with quantilope!

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98 Quantitative Research Questions & Examples

As researchers, we know how powerful quantitative research data can be in helping answer strategic questions. Here, I’ve detailed 23 use cases and curated 98 quantitative market research questions with examples – making this a post you should add to your bookmark list , so you can quickly refer back.

I’ve formatted this post to show you 10-15 questions for each use case. At the end of each section, I also share a quicker way to get similar insights using modern market research tools like Similarweb.

What is a quantitative research question?

Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages– using quantitative data is a clear and effective way to start solving business problems.

Types of quantitative research questions

Quantitative market research questions are divided into two main types: descriptive and causal.

• Descriptive research questions seek to quantify a phenomenon by focusing on a certain population or phenomenon to measure certain aspects of it, such as frequency, average, or relationship.
• Causal research questions explore the cause-and-effect relationship between two or more variables.

The ultimate list of questions for quantitative market research

Get clear explanations of the different applications and approaches to quantitative research–with the added bonus of seeing what questions to ask and how they can impact your business.

Examples of quantitative research questions for competitive analysis

A powerful example of quantitative research in play is when it’s used to inform a competitive analysis . A process that’s used to analyze and understand how industry leaders and companies of interest are performing.

Pro Tip: Collect data systematically, and use a competitive analysis framework to record your findings. You can refer back to it when you repeat the process later in the year.

• What is the market share of our major competitors?
• What is the average purchase price of our competitors’ products?
• How often do our competitors release new products?
• What is the total number of customer reviews for our competitors’ products?
• What is the average rating of our competitors’ products?
• What is the average customer satisfaction score for our competitors?
• What is the average return rate of our competitors’ products?
• What is the average shipping time for our competitors’ products?
• What is the average price discount offered by our competitors?
• What is the average lifespan of our competitors’ products?

With this data, you can determine your position in the market and benchmark your performance against rival companies. It can then be used to improve offerings, service standards, pricing, positioning, and operational effectiveness. Notice that all questions can be answered with a numerical response , a key component of all successful examples of quantitative market research questions.

Quantitative research question example: market analysis

‍♀️ Question: What is the market share of our major competitors?

Insight sought: Industry market share of leaders and key competitors.

Challenges with traditional quantitative research methods: Outdated data is a major consideration; data freshness remains critical, yet is often tricky to obtain using traditional research methods. Markets shift fast, so being able to obtain and track market share in real time is a challenge many face.

A new approach: Similarweb enables you to track this key business KPI in real-time using digital data directly from the platform. On any day, you can see what your market share is, along with any players in your market. Plus, you get to see rising stars showing significant growth, who may pose a threat through market disruption or new tactics.

⏰ Time to insight: 30 seconds

✅ How it’s done: Using Similarweb’s Web Industry Analysis, two digital metrics give you the intel needed to decipher the market share in any industry. I’m using the Banking, Credit, and Lending market throughout these examples. I’ve selected the US market, analyzing the performance of the previous 3 months.

• Share of visits 

Here, I can see the top players in my market based on the number of unique visitors to their sites. On top of the raw data that shows me the volume of visitors as a figure, I can quickly see the two players ( Capital One and Chase ) that have grown and by what percentage. On the side, you can see rising players in the industry. Now, while my initial question was to establish the market share of my major competitors, I can see there are a few disruptive players in my market who I’d want to track too; Synchrony.com being one of particular interest, given their substantial growth and traffic numbers.

• Share of search 

Viewing the overall market size based on total search volumes, you can explore industry leaders in more detail. The top websites are the top five players, ranking by traffic share . You can also view the month-over-month change in visits, which shows you who is performing best at any given time . It’s the same five names, with Paypal and Chase leading the pack. However, I see Wells Fargo is better at attracting repeat visitors, while Capital One and Bank of America perform better at drawing in unique visitors.

In answer to my question, what is the market share of my major competitors, I can quickly use Similarweb’s quantitative data to get my answer.

This traffic share visual can be downloaded from the platform. It plots the ten industry leader’s market share and allocates the remaining share to the rest of the market.

I can also download a market quadrant analysis, which takes two key data points, traffic share and unique visitors, and plots the industry leaders. All supporting raw data can be downloaded in .xls format or connected to other business intelligence platforms via the API.

Quantitative research questions for consumer behavior studies

These studies measure and analyze consumer behavior, preferences, and habits . Any type of audience analysis helps companies better understand customer intent, and adjust offerings, messaging, campaigns, SEO, and ultimately offer more relevant products and services within a market.

• What is the average amount consumers spend on a certain product each month?
• What percentage of consumers are likely to purchase a product based on its price?
• How do the demographics of the target audience affect their purchasing behavior?
• What type of incentive is most likely to increase the likelihood of purchase?
• How does the store’s location impact product sales and turnover?
• What are the key drivers of product loyalty among consumers?
• What are the most commonly cited reasons for not buying a product?
• How does the availability of product information impact purchasing decisions?
• What is the average time consumers spend researching a product before buying it?
• How often do consumers use social media when making a purchase decision?

While applying a qualitative approach to such studies is also possible, it’s a great example of quantitative market research in action. For larger corporations, studies that involve a large, relevant sample size of a target market deliver vital consumer insights at scale .

Read More: 83 Qualitative Research Questions & Examples

Quantitative research question and answer: content strategy and analysis

‍♀️ Question: What type of content performed best in the market this past month?

Insight sought: Establish high-performing campaigns and promotions in a market.

Challenges with traditional quantitative research methods: Whether you consider putting together a panel yourself, or paying a company to do it for you, quantitative research at scale is costly and time-consuming. What’s more, you have to ensure that sampling is done right and represents your target audience.

A new approach: Data analysis is the foundation of our entire business. For over 10 years, Similarweb has developed a unique , multi-dimensional approach to understanding the digital world. To see the specific campaigns that resonate most with a target audience, use Similarweb’s Popular Pages feature. Key metrics show which campaigns achieve the best results for any site (including rival firms), campaign take-up, and periodic changes in performance and interest.

✅ How it’s done: I’ve chosen Capital One and Wells Fargo to review. Using the Popular Pages campaign filter, I can view all pages identified by a URL parameter UTM. For clarity, I’ve highlighted specific campaigns showing high-growth and increasing popularity. I can view any site’s trending, new, or best-performing pages using a different filter.

In this example, I have highlighted three campaigns showing healthy growth, covering teen checking accounts, performance savings accounts, and add-cash-in-store. Next, I will perform the same check for another key competitor in my market.

Here, I can see financial health tools campaigns with over 300% month-over-month growth and smarter credit and FICO campaigns showing strong performance. This tells me that campaigns focussing on education and tools are growing in popularity within this market. 

Examples of quantitative research questions for brand tracking

These studies are designed to measure customers’ awareness, perceptions, behaviors, and attitudes toward a brand over time. Different applications include measuring brand awareness , brand equity, customer satisfaction, and purchase or usage intent.

These types of research surveys ask questions about brand knowledge, brand attributes, brand perceptions, and brand loyalty . The data collected can then be used to understand the current state of a brand’s performance, identify improvements, and track the success of marketing initiatives.

• To what extent is Brand Z associated with innovation?
• How do consumers rate the quality of Brand Z’s products and services?
• How has the awareness of Brand Z changed over the past 6 months?
• How does Brand Z compare to its competitors in terms of customer satisfaction?
• To what extent do consumers trust Brand Z?
• How likely are consumers to recommend Brand Z?
• What factors influence consumers’ purchase decisions when considering Brand Z?
• What is the average customer satisfaction score for equity?
• How does equity’s customer service compare to its competitors?
• How do customer perceptions of equity’s brand values compare to its competitors?

Quantitative research question example and answer: brand tracking

‍♀️ Question: How has the awareness of Brand Z changed over the past 6 months?

Insight sought: How has brand awareness changed for my business and competitors over time.

⏰ Time to insight: 2 minutes

✅ How it’s done: Using Similarweb’s search overview, I can quickly identify which brands in my chosen market have the highest brand awareness over any time period or location. I can view these stats as a custom market or examine brands individually.

Here, I’ve chosen a custom view that shows me five companies side-by-side. In the top right-hand corner, under branded traffic, you get a quick snapshot of the share of website visits that were generated by branded keywords. A branded keyword is when a consumer types the brand name + a search term.

Below that, you will see the search traffic and engagement section. Here, I’ve filtered the results to show me branded traffic as a percentage of total traffic. Similarweb shows me how branded search volumes grow or decline monthly. Helping me answer the question of how brand awareness has changed over time.

Quantitative research questions for consumer ad testing

Another example of using quantitative research to impact change and improve results is ad testing. It measures the effectiveness of different advertising campaigns. It’s often known as A/B testing , where different visuals, content, calls-to-action, and design elements are experimented with to see which works best. It can show the impact of different ads on engagement and conversions.

A range of quantitative market research questions can be asked and analyzed to determine the optimal approach.

• How does changing the ad’s headline affect the number of people who click on the ad?
• How does varying the ad’s design affect its click-through rate?
• How does altering the ad’s call-to-action affect the number of conversions?
• How does adjusting the ad’s color scheme influence the number of people who view the ad?
• How does manipulating the ad’s text length affect the average amount of time a user spends on the landing page?
• How does changing the ad’s placement on the page affect the amount of money spent on the ad?
• How does varying the ad’s targeting parameters affect the number of impressions?
• How does altering the ad’s call-to-action language impact the click-through rate?

Quantitative question examples for social media monitoring

Quantitative market research can be applied to measure and analyze the impact of social media on a brand’s awareness, engagement, and reputation . By tracking key metrics such as the number of followers, impressions, and shares, brands can:

• Assess the success of their social media campaigns
• Understand what content resonates with customers
• Spot potential areas for improvement
• How often are people talking about our brand on social media channels?
• How many times has our brand been mentioned in the past month?
• What are the most popular topics related to our brand on social media?
• What is the sentiment associated with our brand across social media channels?
• How do our competitors compare in terms of social media presence?
• What is the average response time for customer inquiries on social media?
• What percentage of followers are actively engaging with our brand?
• What are the most popular hashtags associated with our brand?
• What types of content generate the most engagement on social media?
• How does our brand compare to our competitors in terms of reach and engagement on social media?

Example of quantitative research question and answer: social media monitoring

‍♀️ Question: How does our brand compare to our competitors in terms of reach and engagement on social media?

Insight sought: The social channels that most effectively drive traffic and engagement in my market

✅ How it’s done: Similarweb Digital Research Intelligence shows you a marketing channels overview at both an industry and market level. With it, you can view the most effective social media channels in any industry and drill down to compare social performance across a custom group of competitors or an individual company.

Here, I’ve taken the five closest rivals in my market and clicked to expand social media channel data. Wells Fargo and Bank of America have generated the highest traffic volume from social media, with over 6.6 million referrals this year. Next, I can see the exact percentage of traffic generated by each channel and its relative share of traffic for each competitor. This shows me the most effective channels are YouTube, Facebook, LinkedIn, and Reddit – in that order.

In 30-seconds, I’ve discovered the following:

• YouTube is the most popular social network in my market.
• Facebook and LinkedIn are the second and third most popular channels.
• Wells Fargo is my primary target for a more in-depth review, with the highest performance on the top two channels.
• Bank of America is outperforming all key players significantly on LinkedIn.
• American Express has found a high referral opportunity on Reddit that others have been unable to match.

Power-up Your Market Research with Similarweb Today

Examples of quantitative research questions for online polls.

This is one of the oldest known uses of quantitative market research. It dates back to the 19th century when they were first used in America to try and predict the outcome of the presidential elections.

Polls are just short versions of surveys but provide a point-in-time perspective across a large group of people. You can add a poll to your website as a widget, to an email, or if you’ve got a budget to spend, you might use a company like YouGov to add questions to one of their online polls and distribute it to an audience en-masse.

• What is your annual income?
• In what age group do you fall?
• On average, how much do you spend on our products per month?
• How likely are you to recommend our products to others?
• How satisfied are you with our customer service?
• How likely are you to purchase our products in the future?
• On a scale of 1 to 10, how important is price when it comes to buying our products?
• How likely are you to use our products in the next six months?
• What other brands of products do you purchase?
• How would you rate our products compared to our competitors?

Quantitative research questions for eye tracking studies

These research studies measure how people look and respond to different websites or ad elements. It’s traditionally an example of quantitative research used by enterprise firms but is becoming more common in the SMB space due to easier access to such technologies.

• How much time do participants spend looking at each visual element of the product or ad?
• How does the order of presentation affect the impact of time spent looking at each visual element?
• How does the size of the visual elements affect the amount of time spent looking at them?
• What is the average time participants spend looking at the product or ad as a whole?
• What is the average number of fixations participants make when looking at the product or ad?
• Are there any visual elements that participants consistently ignore?
• How does the product’s design or advertising affect the average number of fixations?
• How do different types of participants (age, gender, etc.) interact with the product or ad differently?
• Is there a correlation between the amount of time spent looking at the product or ad and the participants’ purchase decision?
• How does the user’s experience with similar products or ads affect the amount of time spent looking at the current product or ad?

Quantitative question examples for customer segmentation

Segmentation is becoming more important as organizations large and small seek to offer more personalized experiences. Effective segmentation helps businesses understand their customer’s needs–which can result in more targeted marketing, increased conversions, higher levels of loyalty, and better brand awareness.

If you’re just starting to segment your market, and want to know the best quantitative research questions to ask to help you do this, here are 20 to choose from.

Examples of quantitative research questions to segment customers

• What is your age range?
• What is your annual household income?
• What is your preferred online shopping method?
• What is your occupation?
• What types of products do you typically purchase?
• Are you a frequent shopper?
• How often do you purchase products online?
• What is your typical budget for online purchases?
• What is your primary motivation for purchasing products online?
• What factors influence your decision to purchase a product online?
• What device do you use most often when shopping online?
• What type of product categories are you most interested in?
• Do you prefer to shop online for convenience or for a better price?
• What type of discounts or promotions do you look for when making online purchases?
• How do you prefer to receive notifications about product promotions or discounts?
• What type of payment methods do you prefer when shopping online?
• What methods do you use to compare different products and prices when shopping online?
• What type of customer service do you expect when shopping online?
• What type of product reviews do you consider when making online purchases?
• How do you prefer to interact with a brand when shopping online?

Examples of quantitative research questions for analyzing customer segments

• What is the average age of customers in each segment?
• How do spending habits vary across customer segments?
• What is the average length of time customers spend in each segment?
• How does loyalty vary across customer segments?
• What is the average purchase size in each segment?
• What is the average frequency of purchases in each segment?
• What is the average customer lifetime value in each segment?
• How does customer satisfaction vary across customer segments?
• What is the average response rate to campaigns in each segment?
• How does customer engagement vary across customer segments?

These questions are ideal to ask once you’ve already defined your segments. We’ve written a useful post that covers the ins and outs of what market segmentation is and how to do it.

Additional applications of quantitative research questions

I’ve covered ten use cases for quantitative questions in detail. Still, there are other instances where you can put quantitative research to good use.

Product usage studies: Measure how customers use a product or service.

Preference testing: Testing of customer preferences for different products or services.

Sales analysis: Analysis of sales data to identify trends and patterns.

Distribution analysis: Analyzing distribution channels to determine the most efficient and effective way to reach customers.

Focus groups: Groups of consumers brought together to discuss and provide feedback on a particular product, service, or marketing campaign.

Consumer interviews: Conducted with customers to understand their behavior and preferences better.

Mystery shopping: Mystery shoppers are sent to stores to measure customer service levels and product availability.

Conjoint analysis: Analysis of how consumers value different attributes of a product or service.

Regression analysis: Statistical analysis used to identify relationships between different variables.

A/B testing: Testing two or more different versions of a product or service to determine which one performs better.

Brand equity studies: Measure, compare and analyze brand recognition, loyalty, and consumer perception.

Exit surveys: Collect numerical data to analyze employee experience and reasons for leaving, providing insight into how to improve the work environment and retain employees.

Price sensitivity testing: Measuring responses to different pricing models to find the optimal pricing model, and identify areas if and where discounts or incentives might be beneficial.

Quantitative market research survey examples

A recent GreenBook study shows that 89% of people in the market research industry use online surveys frequently–and for good reason. They’re quick and easy to set up, the cost is minimal, and they’re highly scalable too.

Questions are always formatted to provide close-ended answers that can be quantified. If you wish to collect free-text responses, this ventures into the realm of qualitative research . Here are a few examples.

Brand Loyalty Surveys: Companies use online surveys to measure customers’ loyalty to their brand. They include questions about how long an individual has been a customer, their overall satisfaction with the service or product, and the likelihood of them recommending the brand to others.

Customer Satisfaction Surveys: These surveys may include questions about the customer’s experience, their overall satisfaction, and the likelihood they will recommend a product or service to others.

Pricing Studies: This type of research reveals how customers value their products or services. These surveys may include questions about the customer’s willingness to pay for the product, the customer’s perception of the price and value, and their comparison of the price to other similar items.

Product/Service Usage Studies: These surveys measure how customers use their products or services. They can include questions about how often customers use a product, their preferred features, and overall satisfaction.

Here’s an example of a typical survey we’ve used when testing out potential features with groups of clients. After they’ve had the chance to use the feature for a period, we send a short survey, then use the feedback to determine the viability of the feature for future release.

Employee Experience Surveys: Another great example of quantitative data in action, and one we use at Similarweb to measure employee satisfaction. Many online platforms are available to help you conduct them; here, we use Culture AMP . The ability to manipulate the data, spot patterns or trends, then identify the core successes and development areas are astounding.

How to answer quantitative research questions with Similarweb

For the vast majority of applications I’ve covered in this post, there’s a more modern, quicker, and more efficient way to obtain similar insights online. Gone are the days when companies need to use expensive outdated data or pay hefty sums of money to market research firms to conduct broad studies to get the answers they need.

By this point, I hope you’ve seen how quick and easy it is to use Similarweb to do market research the modern way. But I’ve only scratched the surface of its capabilities.

Take two to watch this introductory video and see what else you can uncover.

Added bonus: Similarweb API

If you need to crunch large volumes of data and already use tools like Tableau or PowerBI, you can seamlessly connect Similarweb via the API and pipe in the data. So for faster analysis of big data, you can leverage Similarweb data to use alongside the visualization tools you already know and love.

Similarweb’s suite of market intelligence solutions offers unbiased, accurate, honest insights you can trust. With a world of data at your fingertips, use Similarweb Research Intelligence to uncover facts that help inform your research and strengthen your position.

Take a look at:

• Our Market Research suite
• Our Benchmarking tools
• Our Audience Insights tool
• Our Company Research module
• Our Consumer Journey Tracker
• Our Competitive Analysis Tool

Wrapping up

Today’s markets change at lightning speed. To keep up and succeed, companies need access to insights and intel they can depend on to be timely and on-point. While quantitative market research questions can and should always be asked, it’s important to leverage technology to increase your speed to insight, and thus improve reaction times and response to market shifts.

What is quantitative market research?

Quantitative market research is a form of research that uses numerical data to gain insights into the behavior and preferences of customers. It is used to measure and track the performance of products, services, and campaigns.

How does quantitative market research help businesses?

Quantitative market research can help businesses identify customer trends, measure customer satisfaction, and develop effective marketing strategies. It can also provide valuable insights into customer behavior, preferences, and attitudes.

What types of questions should be included in a quantitative market research survey?

Questions in a quantitative market research survey should be focused, clear, and specific. Questions should be structured to collect quantitative data, such as numbers, percentages, or frequency of responses.

What methods can be used to collect quantitative market research data?

Common methods used to collect quantitative market research data include surveys, interviews, focus groups, polls, and online questionnaires.

What are the advantages and disadvantages of using quantitative market research?

The advantages of using quantitative market research include the ability to collect data quickly, the ability to analyze data in a structured way, and the ability to identify trends. Disadvantages include the potential for bias, the cost of collecting data, and the difficulty in interpreting results.

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Quantitative Research: Examples of Research Questions and Solutions

Are you ready to embark on a journey into the world of quantitative research? Whether you’re a seasoned researcher or just beginning your academic journey, understanding how to formulate effective research questions is essential for conducting meaningful studies. In this blog post, we’ll explore examples of quantitative research questions across various disciplines and discuss how StatsCamp.org courses can provide the tools and support you need to overcome any challenges you may encounter along the way.

Understanding Quantitative Research Questions

Quantitative research involves collecting and analyzing numerical data to answer research questions and test hypotheses. These questions typically seek to understand the relationships between variables, predict outcomes, or compare groups. Let’s explore some examples of quantitative research questions across different fields:

• What is the relationship between class size and student academic performance?
• Does the use of technology in the classroom improve learning outcomes?
• How does parental involvement affect student achievement?
• What is the effect of a new drug treatment on reducing blood pressure?
• Is there a correlation between physical activity levels and the risk of cardiovascular disease?
• How does socioeconomic status influence access to healthcare services?
• What factors influence consumer purchasing behavior?
• Is there a relationship between advertising expenditure and sales revenue?
• How do demographic variables affect brand loyalty?

Stats Camp: Your Solution to Mastering Quantitative Research Methodologies

At StatsCamp.org, we understand that navigating the complexities of quantitative research can be daunting. That’s why we offer a range of courses designed to equip you with the knowledge and skills you need to excel in your research endeavors. Whether you’re interested in learning about regression analysis, experimental design, or structural equation modeling, our experienced instructors are here to guide you every step of the way.

Bringing Your Own Data

One of the unique features of StatsCamp.org is the opportunity to bring your own data to the learning process. Our instructors provide personalized guidance and support to help you analyze your data effectively and overcome any roadblocks you may encounter. Whether you’re struggling with data cleaning, model specification, or interpretation of results, our team is here to help you succeed.

Courses Offered at StatsCamp.org

• Latent Profile Analysis Course : Learn how to identify subgroups, or profiles, within a heterogeneous population based on patterns of responses to multiple observed variables.
• Bayesian Statistics Course : A comprehensive introduction to Bayesian data analysis, a powerful statistical approach for inference and decision-making. Through a series of engaging lectures and hands-on exercises, participants will learn how to apply Bayesian methods to a wide range of research questions and data types.
• Structural Equation Modeling (SEM) Course : Dive into advanced statistical techniques for modeling complex relationships among variables.
• Multilevel Modeling Course : A in-depth exploration of this advanced statistical technique, designed to analyze data with nested structures or hierarchies. Whether you’re studying individuals within groups, schools within districts, or any other nested data structure, multilevel modeling provides the tools to account for the dependencies inherent in such data.

As you embark on your journey into quantitative research, remember that StatsCamp.org is here to support you every step of the way. Whether you’re formulating research questions, analyzing data, or interpreting results, our courses provide the knowledge and expertise you need to succeed. Join us today and unlock the power of quantitative research!

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Quantitative Research Questions: What It Is Types & Examples

If you’re struggling to create the perfect research question that will lead to meaningful insights, look no further than this article.

We’ll show you how to craft compelling quantitative research questions to take your research to the next level.

We all know that asking the right questions is crucial to the success of any study.

Quantitative research questions are essential in determining the direction of your research, data, and final insights.

However, crafting the perfect question can be a daunting task. How do you ensure your question is specific, measurable, and relevant to your goals?

How do you avoid bias?

In this article, we’ll answer all of these questions and more. Also, you’ll learn the following:

What are Quantitative Research Questions?

Importance of quantitative research questions, when to use quantitative research questions, characteristics of quantitative research questions, types of quantitative research questions, quantitative research questions examples, how to conduct quantitative research questions, how to analyze quantitative research questions.

Before diving into the blog’s core, we’ll address the following question: what is quantitative research?

Quantitative research questions are inquiries crafted to gather numerical data and quantify phenomena within a research study. These questions seek to understand relationships between variables, measure frequencies, or assess the extent of certain behaviors, attitudes, or trends within a defined population. They are structured and precise, often aiming to elicit specific responses that can be quantified and analyzed statistically. Quantitative research questions play a fundamental role in studies that require numerical data to draw objective conclusions, establish patterns, and correlations, or make predictions. These questions provide a framework for designing surveys, experiments, or data collection methods that generate quantifiable data, facilitating rigorous analysis and empirical validation of findings across various disciplines.

Quantitative research questions play a pivotal role in structured data collection, providing a framework to gather precise, measurable information. These questions are crucial as they enable researchers to quantify phenomena, trends, or behaviors within a population, offering statistical insights and objective findings. By formulating clear, specific questions, researchers can design surveys or experiments that yield numerical data, facilitating rigorous analysis and comparisons. This approach is instrumental in uncovering patterns, correlations, and trends, allowing for generalizations and predictions within a given context. Moreover, quantitative research questions are vital in validating hypotheses, informing decision-making processes, and contributing to evidence-based conclusions across various fields, from social sciences to business and beyond. Their importance lies in their ability to offer structured, quantifiable data that enhances understanding and drives informed actions.

Quantitative research questions are best employed when seeking precise, numerical data to answer specific queries or test hypotheses. These questions find their place in scenarios where a structured approach is necessary to measure, quantify, or statistically analyze phenomena within a defined population or sample. They are particularly valuable when aiming to identify patterns, relationships, or correlations among variables that can be objectively measured or quantified. Additionally, quantitative research questions are well-suited for large-scale studies, surveys, or experiments where numerical data is essential for drawing statistically valid conclusions. Their use is prominent in fields such as economics, psychology, sociology, marketing, and other sciences, providing a robust framework to gather data that can be analyzed rigorously using statistical methods. Overall, quantitative research questions excel in scenarios requiring precise measurement, numerical analysis, and statistical validation of findings.

For a research question to be effective, several key attributes must be adhered to. Clarity and specificity are paramount; the question should be crystal clear, leaving no room for ambiguity. Additionally, it should directly align with the research objectives and hypotheses, ensuring a seamless connection between the inquiry and the study’s purpose. Testability and measurability are equally crucial; the question should lend itself to empirical testing and quantifiable outcomes.

Quantitative research questions typically fall into several categories, each serving a specific purpose within a study:

Descriptive Questions: Aim to describe characteristics, frequencies, or trends within a population or sample. For example, “What percentage of customers prefer product A over product B?”

Comparative Questions: Focus on comparing two or more groups, variables, or conditions to identify differences or similarities. For instance, “Is there a significant difference in sales between urban and rural markets?”

Relationship Questions: Investigate the correlation or association between two or more variables. An example is, “Is there a relationship between advertising expenditure and sales revenue?”

Predictive Questions: Seek to forecast or predict future outcomes based on identified patterns or relationships. For instance, “Can customer satisfaction scores predict future purchase intentions?”

Causal Questions: Explore cause-and-effect relationships between variables. These questions aim to determine if changes in one variable cause changes in another. For example, “Does increased training lead to higher employee productivity?”

These types of quantitative research questions guide the design of studies and the collection of numerical data to address specific research objectives within various fields of inquiry.

Quantitative research questions can be a lifesaver in creating surveys .

Below are two examples of questionnaires you can use to gather quantitative data regarding customer service and product usage.

Customer Service Questions

If you’re looking to improve your customer service , these questions can help you identify areas of strength.

They’re designed to be quick and easy for customers to answer.

For instance, you might ask your customers to rate their overall satisfaction on a scale of 1 to 5 .

You could also ask how easy it was for them to contact customer service and how helpful and knowledgeable the representatives were.

Product and Usage Questions

If you’re interested in improving your product or understanding your customers’ usage patterns, these questions can help.

They’re designed to be straightforward to answer.

For instance, you might ask customers how satisfied they are with the product’s performance or how often they use it.

You could also ask how easy it was to set up and start using the product or whether they’ve encountered any issues.

The tool we recommend you use to gather qualitative research questions’ responses is Google Forms .

Follow the easy steps below to get started with Google Forms application.

• Open Google Sheets and click the Tools Click the Create a new form , as shown below.

• Fill in your question in the Untitled Question Fill in the multiple-choice questions in Option 1, 2, etc.

• Click the three dots in the Responses Tab to link your Google Form survey template to Google Sheets.
• Download your qualitative research questions data by clicking the Download Responses (CSV) in the dropdown.

Excel is a great tool for creating charts.

But it lacks survey-specific charts and graphs, like Likert Scale Chart .

Fortunately, there’s a solution: ChartExpo.

ChartExpo is a powerful data visualization tool that offers a range of benefits, like access to the best charts for survey analysis. With ChartExpo, you can easily and quickly create effective charts and graphs that will help you gain a deeper understanding.

One of the biggest merits of the ChartExpo add-in for Excel is its user-friendly interface.

You don’t need coding experience to use it. This makes it accessible to everyone.

Plus, the visualizations provided by ChartExpo can help you uncover hidden patterns and trends in your data.

This means you’ll have unlimited access to valuable insights into your customers’ experiences .

ChartExpo takes your data security seriously.  Your data does not leave your environment.

ChartExpo is affordable at just $10 monthly, with a 7-day free trial.

Sign up for ChartExpo today and start gaining insights like never before!

Let’s assume we’ve downloaded our survey data into Excel by following the easy steps below.

We’ll use ChartExpo’s Likert Scale Chart to visualize the data below

Before we visualize the data above, we’ll show you how to install and use ChartExpo add-in.

To get started with ChartExpo in Excel, follow the steps below:

• Open your Microsoft Excel.
• Open the worksheet and click the Insert button to  access the  My Apps

• Click the Insert button to initiate the ChartExpo engine.

• Click the Search box and type “Likert Scale Chart.”

• Highlight your data and click the Create Chart From Selection button, as shown below.

• Use the multiple-choice responses you deployed in your survey to gather responses to map your Likert Scale.

In our case, we’ll use the following multiple-choice responses:

• Very Unlikely = 1
• Unlikely = 2
• Not Sure = 3
• Very Likely = 5

• To include the chart header, click the Edit Chart

• Once the Chart Header Properties window shows, fill in your header in Line 1, as shown.

• Toggle the small button below Line 2 to the right side to activate the header.
• Click the Apply button, as shown above.
• Click the Save Changes button to preserve all the changes.

• Check out the final chart below.

• According to the survey results, 60% of customers indicated that they would buy the product again.
• However, 25% said they would not.
• The remaining 15% were unsure about their future purchasing intentions.
• Regarding the discount code, 55% of customers said they would use it. Only 35% said they would not.
• Regarding recommending the product to their friends, 55% of customers said they would. However, 20% said they would not.
• Overall, 56% of respondents expressed satisfaction with both the product and store. Only 27% expressed dissatisfaction.

What are examples of quantitative research questions?

Examples of quantitative research questions include:

• What is the relationship between your education level and your income?
• How does your age affect memory recall?
• “What is the impact of exercise on your blood pressure?”

These questions are measurable and objective and typically involve the collection and visualization of numerical data.

What is the main purpose of quantitative research?

The main purpose of quantitative research is to provide objective answers to research questions through the analysis of numerical data.

Use it to identify patterns and relationships between variables and to provide evidence-based solutions.

In conclusion, quantitative research questions are a powerful tool for gathering accurate and reliable insights.

By using well-crafted questionnaires and data visualization tools like ChartExpo, you can gain valuable insights into your customers’ experiences and preferences.

ChartExpo offers numerous benefits, including a user-friendly interface and the ability to create compelling charts that uncover hidden patterns and trends in survey data.

Whether you’re looking to improve customer service, understand product usage patterns, or gain insights into any other area of your business, quantitative research questions can help.

 So why not use them today?

If you need a tool to help you visualize your data, give ChartExpo a try. It has an affordable monthly subscription and 7-day free trial.

Start making data-driven decisions today with the help of quantitative research questions and ChartExpo.

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• Quantitative research questions: Types, tips & examples

Defne Çobanoğlu

Deciding on your next survey’s goal gives you a starting point as to what kind of questions you will use on your survey. And if you want to do concrete market research, give a data summary to your supervisors, or make informed decisions based on the data you collect, you should use quantitative survey questions.

In this article, we have gathered more than 100 survey question examples about gender, marketing, stress, psychology, academic performance, social media, and mental health to get you started. You can add these questions to your next research survey, or you can use them to get inspiration to write many more. Let us get started!

• What is a quantitative research question?

The quantitative research question is a type of question where the person asking the question wants to obtain a numeric answer that will provide them with a tangible answer. It involves collecting objective, measurable data about a particular subject or topic, often through surveys, experiments, or other structured methods.

The definition of a quantitative research question

The data collected is typically numerical in nature, such as ratings, counts, measurements, or percentages . So, an answer to this type of question can be confidentially used when creating a quantitative analysis.

Quantitative vs. qualitative research questions

The main difference between quantitative and qualitative questions is what you want to achieve from the question and methods of data collection. Qualitative research focuses on exploring and understanding complex phenomena, experiences, and perspectives . And qualitative research questions aim to gather detailed descriptions and subjective experiences to gain insights.

On the other hand, quantitative research aims to answer questions that involve measuring and quantifying variables, examining relationships, and making statistical deductions. It mainly relies on structured data collection methods, such as surveys, experiments, observations, and existing datasets, in order to collect numerical data .

• How to write a quantitative research question

If you want to obtain concrete data on a research topic, you should use quantitative research questions. They give you numerical answers such as ratings, measurements, counts, or percentages. That makes it easier to conclude a quantitative analysis. Therefore, use questions that will give you answers like; “three times a week”, “about 11”, “20% of the students”, etc. Here are some question starters to have in mind to give you quantitative research questions ideas:

• How frequently?
• What percentage?
• To what extent?
• What proportion?
• On a scale of…

Here are some simple examples:

• How often do you go to the gym in a week?
• How much do you spend on groceries?
• How many phone calls do you make a day?
• Types of quantitative questions

When you try to get numerical answers, the only option is not the multiple-choice one. You can use different types of quantitative research questions to make the form more interesting, visually appealing, and detailed if you use a smart survey creator, such as forms.app, you can make use of its multiple smart form fields to build your form. Let us see what are some good options to use on your next survey.

Star rating:

It is a good way to ask people their opinions, and the survey takers can rate criteria based on different categories. Each star represents an equivalent numeric value, and they typically range from 1 to 5. Even if they are clicking on stars, you get numeric data in the end.

A star rating question example

Opinion scale:

It is basically the same thing with the stars but instead, the survey takers rate criteria as numbers from 1-5 or 1-10. It is better to keep in mind the best way for this is using a 1-5 scale, with 5 being the best and 1 being the worst rating.

An opinion scale question example

Picture selection:

Having people choose their opinions in a picture selection form is a good way to go. It is a good option to use when you are creating a survey for market research and such.

A picture selection question example

Multiple-choice:

When you ask people a question such as; “what are the reasons that negatively affect your mental health?” it is better to let them choose multiple reasons rather than a single one. You would not want to limit the target audience by making them choose only one thing on the list.

A multiple-choice question example

Selection matrix:

In this type of question, you can make multiple sentences, categories, and statements, and survey takers can answer them accordingly. They allow you to get the answers as one question rather than setting up multiple questions.

A selection matrix example

• 100+ Quantitative research questions to ask in your research surveys

In your next survey, you can use any of the questions below, or you can create your own. If you use smart questions focused on a subject or aspect, it will make it easier for you to make an informed analysis at the end. Now, let us start with the first one:

Quantitative research questions about gender

A question example about quantitative research about gender

Quantitative research questions about gender aim to gather numerical data to quantify and analyze gender-related patterns, differences, and associations. They focus on exploring gender-related issues and investigating gender influences on several aspects of life.

1 - What is the difference in average earnings between male and female employees in a specific industry?

2 - How does gender affect academic achievement in STEM subjects among high school students?

3 - What is the percentage of women in leadership positions in Fortune 500 companies?

4 - What is the impact of gender on access to and utilization of health services?

5 - What is the percentage of female students speaking in a classroom as opposed to male students?

6 - How does gender influence consumer preferences and purchasing behavior in the fashion industry?

7 - What are the gender differences in response to specific marketing strategies for a particular product?

8 - What is the correlation between gender and mental health outcomes in a specific population?

9 - How does gender influence the perception of work-life balance among working professionals?

10 - How often do you feel discriminated against in a work environment because of your gender?

11 - What is the effect of gender on smoking at the ages 14-18?

Quantitative research questions about stress

A question example about quantitative research about stress

Research questions about stress aim to investigate different aspects of stress, its causes, and its consequences. Researchers can measure stress levels and examine the relationships between stress and other variables. Also, they can analyze patterns and trends associated with stress after collecting appropriate data.

12 - On a scale of 1 to 10, how often do you feel stressed?

13 - What is the prevalence of stress among college students?

14 - How does stress impact academic achievement among high school students?

15 - How does mindfulness meditation training impact stress levels in university students?

16 - What are the primary sources of work-related stress among employees?

17 - What is the relationship between stress levels and job performance among healthcare professionals?

18 - Who are the people in your life that cause you the most stress?

19 - In the last month, how often have you felt that you were unable to control important things in your life?

20 - How does workplace stress influence employee turnover rates in a specific organization?

21 - What is the correlation between stress levels and physical health in young people?

22 - What are the demographic factors (such as age, gender, or income) associated with higher levels of stress?

23 - What is the impact of stress on sleep quality and duration among adults?

24 - What are the stress levels experienced by parents of children with special needs compared to parents of typically developing children?

25 - What is the effectiveness of stress management interventions in reducing stress levels among individuals with chronic illnesses?

26 - What is the impact of daily meditation helping stress levels?

27 - What are the factors contributing to job-related stress among healthcare professionals in a specific specialty?

Quantitative research questions in Psychology

A question example about quantitative research in psychology

Quantitative research questions in psychology cover a range of psychological topics, including mental health, personality, behavior, and social dynamics. The aim of these questions is to collect quantitative data to examine relationships, assess the effectiveness of interventions, and identify factors associated with psychological events.

28 - What is the relationship between self-esteem and academic performance in high school students?

29 - How does exposure to violent media affect aggressive behavior in children?

30 - What is the prevalence of depression among college students?

31 - How is parental attachment style associated with the development of anxiety disorders in children?

32 - How many times a month should one use professional therapy?

33 - What are the factors influencing job satisfaction among employees in a specific industry?

34 - What are the predictors of job performance among healthcare professionals?

35 - Generally, at what age do children start getting psychological help?

36 - What is the effect of cognitive-behavioral therapy on reducing symptoms of post-traumatic stress disorder?

37 - How does the classroom environment affect academic motivation and achievement in elementary school students?

38 - What is the effectiveness of a cognitive training program in improving memory function in older adults?

39 - How do exercise frequency and intensity impact symptoms of anxiety and depression in individuals with diagnosed mental health conditions?

40 - What is the correlation between sleep duration and academic performance in college students?

41 - How does parental divorce during childhood impact the development of attachment styles in adulthood?

42 - What is the relationship between self-esteem and job satisfaction among working professionals?

43 - What are the predictors of eating disorder symptoms in adolescent females?

44 - At what age the teenage girls prone to depression?

45 - What is the correlation between young adults and suicide rates?

46 - What is the effect of a specific cognitive training program on improving cognitive functioning in elders?

47 - How does the presence of social support networks impact resilience levels in individuals who have experienced traumatic events?

48 - What are the effects of a specific therapeutic intervention on reducing symptoms of anxiety in individuals with a generalized anxiety disorder?

49 - What is the correlation between social media use and symptoms of depression in young adults?

50 - How does mindfulness meditation training influence stress levels in individuals with high-stress occupations?

51 - How does exposure to violent video games affect aggressive behavior in adolescents?

Quantitative research questions about mental health

A question example about quantitative research about mental health

Quantitative research questions about mental health focus on various aspects of mental health, including the prevalence of disorders, risk factors, treatment interventions, and the impact of lifestyle factors. 

52 - How does the frequency of social media use relate to levels of depressive symptoms in adolescents?

53 - What is the correlation between sleep quality and mental health outcomes in adults with diagnosed mental health conditions?

54 - What is the percentage of people diagnosed with anxiety disorder that has a college education?

55 - What kind of activities helps with your mental health?

56 - How many times a week do you spare time for your mental well-being?

57 - What is the effect of a specific psychotherapy intervention on reducing symptoms of depression?

58 - What are the factors determining treatment adherence in patients with schizophrenia?

59 - How do exercise frequency and intensity relate to anxiety levels?

60 - What is the relationship between social support and endurance in individuals with a history of trauma?

61 - How does stigma surrounding mental illness influence help-seeking behavior among college students?

62 - What is the prevalence of anxiety disorders among college students?

Quantitative research questions about social media

A question example about quantitative research about social media

Quantitative research questions about social media try to explore various aspects of social media, including its impact on psychological well-being, behavior, relationships, and society. They aim to collect quantitative data to analyze relations, examine effects, and measure the influence of social media.

63 - How many times a day do you check your social media accounts?

64 - How much time do you spend on social media every day?

65 - How many social media accounts do you own?

66 - What is the correlation between social media engagement and academic performance in high school students?

67 - What are the most used social media accounts among teenagers?

68 - What is the psychological effect of social media accounts on young people?

69 - What is the relationship between social media use and self-esteem among adolescents?

70 - How does the frequency of social media use relate to levels of loneliness in young adults?

71 - How does exposure to idealized body images on social media impact body dissatisfaction in women?

72 - What are the predictors of problematic social media use among college students?

73 - How does social media use influence political attitudes and behaviors among young adults?

74 - What is the effect of social media advertising on consumer purchasing behavior and brand loyalty?

75 - What is the association between cyberbullying on social media and mental health outcomes among teenagers?

76 - How does social media use affect sleep quality and duration in adults?

77 - How does social media use impact interpersonal relationships and social support among individuals in long-distance relationships?

Quantitative research questions about academic performance

A question example about quantitative research about academic performance

Quantitative research questions about academic performance focus on academic performance, the predictors, and the elements affecting it negatively and positively. They aim to collect quantitative data to figure out the relation between academic performance and the environment of the students and make informed decisions.

78 - What is the correlation between student attendance rates and academic achievement in a specific grade level?

79 - How does parental involvement in education relate to students' academic performance?

80 - What is the impact of classroom size on student academic outcomes?

81 - What are the predictors of academic success among undergraduate students in a specific major?

82 - How many times were you absent during the last semester?

83 - What is the correlation between student engagement in extracurricular activities and their academic performance?

84 - What is the effect of peer tutoring programs on student grades and test scores?

85 - How do student motivation and self-efficacy influence academic achievement in a specific academic setting?

86 - What is the relationship between study habits and academic performance among high school students?

87 - How does the implementation of a specific teaching methodology or instructional approach impact student achievement in a particular subject?

Quantitative research questions about marketing

A question example about quantitative research about marketing

Quantitative research questions about marketing explore various aspects of marketing, including advertising effectiveness, consumer behavior, branding, pricing, and customer satisfaction. They involve collecting quantitative data to analyze relationships and assess the impact of marketing strategies. 

88 - What is the correlation between advertising expenditure and sales revenue for a specific product?

89 - As a consumer, how often do you make purchasing decisions based on marketing exposure?

90 - What are the top 5 brands that stand out to you because of ads of their quality?

91 - How does brand loyalty relate to customer satisfaction and repeat purchase behavior?

92 - What is the impact of pricing strategies on consumer purchase intentions and price sensitivity?

93 - When making a purchase, how important is the packaging of the product to you?

94 - What is the effectiveness of different marketing channels (e.g., social media, television, email marketing) in reaching and engaging the target audience?

95 - How does product packaging design influence consumer perception and purchase decisions?

96 - What are the key factors influencing customer loyalty in the retail industry?

97 - What is the relationship between online customer reviews and purchase decisions in e-commerce?

98 - How do brand reputation and perception affect consumer trust and willingness to recommend a product or service?

99 - What are the channels you visit to ensure the quality of the product you will purchase?

100 - How does the personalization of marketing messages impact customer engagement and response rates?

101 - What is the effect of promotional offers (e.g., discounts, coupons) on consumer purchase behavior?

102 - What is the effect of ad placement on popular social media accounts on teenagers?

• Tips for creating quantitative research questions

When you want to create your survey, you should be professional and collect the data systematically. That will help you have clear results. In order to achieve this: 

• Use clear and unambiguous language
• Avoid leading or biased questions 
• Use different question types 
• Keep the length of your survey at an appropriate level

After you create your survey in a systematic manner and use a competitive analysis framework to record your findings, you can achieve the concrete results you want. Also, always remember to obtain the necessary ethical approvals and informed consent required for your research study.

• How to create a quantitative research survey

When you are creating your next survey, you can go old-fashion and write everything down on a piece of paper and try to get people to fill them out. However, there is a much easier option thanks to online survey tools. And a great survey maker you can use is forms.app. It has over 1000 ready-to-use templates, and each of them is as useful. Now, let us go through the steps to creating a quantitative survey using forms.app:

1 - Go to forms.app and log in to your account (or create one for free).

2 - Go to the dropdown menu and click on the templates option .

3 - Choose one of the survey templates and click on the “use template” button and customize it as much as you want by adding question fields and changing the visuals as much as you want.

4 - Or, you can decide on starting from scratch and build everything from the start in a matter of minutes.

5 - Save your changes, and by clicking on the “eye” icon on the upper left side of the page, see the final result.

6 - Copy the unique link and share it with your audience. If you want, you can also embed the survey on the page of your choosing.

• Key points to take away

Creating a simple survey to collect numerical values to make informed and supported plans is very easy. It can be done with a simple and effective form creator, such as forms.app. It has many functional form fields and is also completely adjustable.

You can easily create your own research survey with the questions we have gathered for you. It should be mentioned that you should keep in mind to have a structured plan to go with. Because only then can you analyze your results effectively and repeat the research if it is needed.

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

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Quantitative research question examples

One of the best ways to determine how your target audience feels about your company or organization is through quantitative research. Once you understand user opinions, attitudes, behaviors, preferences, and market trends, you can make informed decisions that help you improve your products, services, and every aspect of the customer experience.

In this post, we’ll review what a quantitative research question is, cover the types of quantitative research questions, share examples of quantitative research questions across various fields, and highlight tips for creating a quantitative research survey.

Some background on quantitative research questions

Quantitative research questions collect objective, measurable, numerical data through

• Surveys and questionnaires
• Controlled observations
• Reviewing existing research to produce sound statistical analysis

The data includes ratings, counts, measurements, and percentages. Because this data is objective, it’s considered more reliable than qualitative research data.

Quantitative data helps researchers identify trends and patterns. They can use these insights to make informed decisions about company or organizational goals, targets, and strategic improvements to undertake.

Quantitative research questions are useful for measuring many things, but businesses commonly use them to determine overall customer satisfaction , gather feedback on existing products and services, gauge the demand for new products and services, and decide on business improvements to roll out.

Some examples of quantitative research questions include

• How many times per week do you use social media?
• How often do you visit our website?
• How many mobile shopping apps do you use?

Types of quantitative research questions

The three main types of quantitative research questions are descriptive, comparative, and relationship-based. Which type or types you use will depend on the kind of data you want to collect and your research objective.

Descriptive research questions are usually closed-ended, and they elicit participants’ opinions about a specific variable. With these questions, you may ask how often someone uses your product, when they use your product, or how much they’d be willing to pay for a specific product.

Comparative research questions consider differences between groups based on dependable variables. With these questions, you may want to compare brand preferences among men versus women, compare how often individuals use similar products, or assess how your products stack up against competitors’ offerings.

Relationship-based research questions are helpful for gauging trends, causal relationships, or connections between variables. You may develop questions that help you explore how color influences buying decisions for a product or assess the relationship between employee turnover and workplace environment.

Examples of quantitative research questions

Now let’s take a look at some examples of quantitative research questions in the fields of education, health, marketing, and social sciences.

Examples of quantitative research questions in education

• On a scale of 1 to 10, how much does parental participation in education impact student academic achievement?
• What impact does classroom size have on academic performance? Choose from the following: no impact, limited impact, high impact.
• How many times were you (the student) absent last semester?
• Is the relationship between extracurricular activities and student performance positive, negative, or neutral?
• On a scale of 1 to 5, how much do study habits impact student grades and test scores?

Examples of quantitative research questions in the mental and physical health fields

• On a scale of 1–10, how often do you feel stressed?
• How many times per week do you engage in activities to improve your mental well-being?
• How frequently do you exercise?
• Do you have a health insurance plan?
• How would you rate the care you received on your last visit with a primary care provider?
• What is the relationship between stress levels and physical health in retirees?
• On average, how many times per year do you visit a healthcare provider or facility?

Examples of quantitative research questions in marketing

• How often do you make buying decisions based on advertising or marketing campaigns?
• How often do you use products in this category?
• On a scale of 1–10, how satisfied are you with the quality of this product?
• On a scale of 1–10, how likely are you to recommend this product to others?
• How much are you willing to pay for this product?
• Which product features are the most important to you when making buying decisions in this category?
• How much do customer reviews impact your buying decisions?
• What is your preferred way to purchase products in this category (online or in the store)?

Examples of quantitative research questions in social sciences

• On a scale of 1 to 10, how much does income inequality impact academic performance?
• To what extent is there still a gender imbalance in pay/wages? Rate your answer on a scale of 1 to 5.
• To what degree does race impact rates of mental health diagnosis in adults? Rate your answer on a scale of 1 to 5.
• Does gender affect an individual’s contribution to household tasks?

Tips for creating quantitative research questions

Now that we’ve seen some examples, let’s review a few tips for creating your own quantitative research questions.

Since you’re looking for concrete data, ask questions such as

• What percentage?
• What proportion?

Let’s look at some concrete examples:

• How much is your weekly grocery budget?
• How many times per month do you visit a brick-and-mortar store?
• What percentage of your monthly income is spent on housing?

To increase the quality of your questions and ensure the best results

• Use different question types (i.e., descriptive, comparative, relationship-based).
• Keep the survey or questionnaire as short as you can without sacrificing data collection.
• Don’t use leading or biased questions.
• Use clear language and avoid jargon.
• Address one topic per question, starting with easier questions first to build momentum.
• Be sure to get approvals and informed consent before proceeding.

How to create a quantitative research survey

• Select the type of quantitative research question or questions from among the three discussed above — descriptive, comparative, or relationship-based — based on your research objective.
• Identify the type of variable you’re trying to measure — either independent (the variable being manipulated) or dependent (the outcome variable) — and the target audience. Measurement variables include nominal, ordinal, interval, and ratio.
• Decide on the structure of your research questions based on the type of questions you’ll be presenting. Structure pertains to variables, groups, and the order of the variables and groups in the questions.
• Draft your research questions and finalize your survey.

If you’re interested in learning more, we offer a more in-depth look at quantitative market research best practices . Also, check out our detailed, step-by-step guide on how to do market research .

You can build beautiful, easy-to-use, fully customizable surveys using Jotform’s premade survey templates or create them from scratch — no coding required. Tailor your surveys to match your business and your specific goals, and even share, collect, and analyze your survey results with our free online survey maker .

If you want to gather invaluable insights into user behavior, opinions, attitudes, and preferences, quantitative research is a great way to go about it. Jotform’s robust survey and questionnaire tools make it easy to get started.

Photo by ODISSEI on Unsplash

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21 Questionnaire Templates: Examples and Samples

Questionnaire: Definition

A questionnaire is defined a market research instrument that consists of questions or prompts to elicit and collect responses from a sample of respondents. A questionnaire is typically a mix of open-ended questions and close-ended questions ; the latter allowing for respondents to enlist their views in detail.

A questionnaire can be used in both, qualitative market research as well as quantitative market research with the use of different types of questions .

LEARN ABOUT: Open-Ended Questions

Types of Questionnaires

We have learnt that a questionnaire could either be structured or free-flow. To explain this better:

• Structured Questionnaires: A structured questionnaires helps collect quantitative data . In this case, the questionnaire is designed in a way that it collects very specific type of information. It can be used to initiate a formal enquiry on collect data to prove or disprove a prior hypothesis.
• Unstructured Questionnaires: An unstructured questionnaire collects qualitative data . The questionnaire in this case has a basic structure and some branching questions but nothing that limits the responses of a respondent. The questions are more open-ended.

LEARN ABOUT:   Structured Question

Types of Questions used in a Questionnaire

A questionnaire can consist of many types of questions . Some of the commonly and widely used question types though, are:

• Open-Ended Questions: One of the commonly used question type in questionnaire is an open-ended question . These questions help collect in-depth data from a respondent as there is a huge scope to respond in detail.
• Dichotomous Questions: The dichotomous question is a “yes/no” close-ended question . This question is generally used in case of the need of basic validation. It is the easiest question type in a questionnaire.
• Multiple-Choice Questions: An easy to administer and respond to, question type in a questionnaire is the multiple-choice question . These questions are close-ended questions with either a single select multiple choice question or a multiple select multiple choice question. Each multiple choice question consists of an incomplete stem (question), right answer or answers, close alternatives, distractors and incorrect answers. Depending on the objective of the research, a mix of the above option types can be used.
• Net Promoter Score (NPS) Question: Another commonly used question type in a questionnaire is the Net Promoter Score (NPS) Question where one single question collects data on the referencability of the research topic in question.
• Scaling Questions: Scaling questions are widely used in a questionnaire as they make responding to the questionnaire, very easy. These questions are based on the principles of the 4 measurement scales – nominal, ordinal, interval and ratio .

Questionnaires help enterprises collect valuable data to help them make well-informed business decisions. There are powerful tools available in the market that allows using multiple question types, ready to use survey format templates, robust analytics, and many more features to conduct comprehensive market research.

LEARN ABOUT: course evaluation survey examples

For example, an enterprise wants to conduct market research to understand what pricing would be best for their new product to capture a higher market share. In such a case, a questionnaire for competitor analysis can be sent to the targeted audience using a powerful market research survey software which can help the enterprise conduct 360 market research that will enable them to make strategic business decisions.

Now that we have learned what a questionnaire is and its use in market research , some examples and samples of widely used questionnaire templates on the QuestionPro platform are as below:

LEARN ABOUT: Speaker evaluation form

Customer Questionnaire Templates: Examples and Samples

QuestionPro specializes in end-to-end Customer Questionnaire Templates that can be used to evaluate a customer journey right from indulging with a brand to the continued use and referenceability of the brand. These templates form excellent samples to form your own questionnaire and begin testing your customer satisfaction and experience based on customer feedback.

LEARN ABOUT: Structured Questionnaire

USE THIS FREE TEMPLATE

Employee & Human Resource (HR) Questionnaire Templates: Examples and Samples

QuestionPro has built a huge repository of employee questionnaires and HR questionnaires that can be readily deployed to collect feedback from the workforce on an organization on multiple parameters like employee satisfaction, benefits evaluation, manager evaluation , exit formalities etc. These templates provide a holistic overview of collecting actionable data from employees.

Community Questionnaire Templates: Examples and Samples

The QuestionPro repository of community questionnaires helps collect varied data on all community aspects. This template library includes popular questionnaires such as community service, demographic questionnaires, psychographic questionnaires, personal questionnaires and much more.

Academic Evaluation Questionnaire Templates: Examples and Samples

Another vastly used section of QuestionPro questionnaire templates are the academic evaluation questionnaires . These questionnaires are crafted to collect in-depth data about academic institutions and the quality of teaching provided, extra-curricular activities etc and also feedback about other educational activities.

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A Comprehensive Guide to Quantitative Research: Types, Characteristics, Methods & Examples

Step into the fascinating world of quantitative research, where numbers reveal extraordinary insights!

By gathering and studying data in a systematic way, quantitative research empowers us to understand our ever-changing world better. It helps understand a problem or an already-formed hypothesis by generating numerical data. The results don’t end here, as you can process these numbers to get actionable insights that aid decision-making.

You can use quantitative research to quantify opinions, behaviors, attitudes, and other definitive variables related to the market, customers, competitors, etc. The research is conducted on a larger sample population to draw predictive, average, and pattern-based insights.

Here, we delve into the intricacies of this research methodology, exploring various quantitative methods, their advantages, and real-life examples that showcase their impact and relevance.

Ready to embark on a journey of discovery and knowledge? Let’s go!

What Is Quantitative Research?

Quantitative research is a method that uses numbers and statistics to test theories about customer attitudes and behaviors. It helps researchers gather and analyze data systematically to gain valuable insights and draw evidence-based conclusions about customer preferences and trends.

Researchers use online surveys , questionnaires , polls , and quizzes to question a large number of people to obtain measurable and bias-free data.

In technical terms, quantitative research is mainly concerned with discovering facts about social phenomena while assuming a fixed and measurable reality.

Offering numbers and stats-based insights, this research methodology is a crucial part of primary research and helps understand how well an organizational decision is going to work out.

Let’s consider an example.

Suppose your qualitative analysis shows that your customers are looking for social media-based customer support . In that case, quantitative analysis will help you see how many of your customers are looking for this support.

If 10% of your customers are looking for such a service, you might or might not consider offering this feature. But, if 40% of your regular customers are seeking support via social media, then it is something you just cannot overlook.

Characteristics of Quantitative Research

Quantitative research clarifies the fuzziness of research data from qualitative research analysis. With numerical insights, you can formulate a better and more profitable business decision.

Hence, quantitative research is more readily contestable, sharpens intelligent discussion, helps you see the rival hypotheses, and dynamically contributes to the research process.

Let us have a quick look at some of its characteristics.

• Measurable Variables

The data collection methods in quantitative research are structured and contain items requiring measurable variables, such as age, number of family members, salary range, highest education, etc.

These structured data collection methods comprise polls, surveys, questionnaires, etc., and may have questions like the ones shown in the following image:

As you can see, all the variables are measurable. This ensures that the research is in-depth and provides less erroneous data for reliable, actionable insights.

• Sample Size

No matter what data analysis methods for quantitative research are being used, the sample size is kept such that it represents the target market.

As the main aim of the research methodology is to get numerical insights, the sample size should be fairly large. Depending on the survey objective and scope, it might span hundreds of thousands of people.

• Normal Population Distribution

To maintain the reliability of a quantitative research methodology, we assume that the population distribution curve is normal.

This type of population distribution curve is preferred over a non-normal distribution as the sample size is large, and the characteristics of the sample vary with its size.

This requires adhering to the random sampling principle to avoid the researcher’s bias in result interpretation. Any bias can ruin the fairness of the entire process and defeats the purpose of research.

• Well-Structured Data Representation

Data analysis in quantitative research produces highly structured results and can form well-defined graphical representations. Some common examples include tables, figures, graphs, etc., that combine large blocks of data.

This way, you can discover hidden data trends, relationships, and differences among various measurable variables. This can help researchers understand the survey data and formulate actionable insights for decision-making.

• Predictive Outcomes

Quantitative analysis of data can also be used for estimations and prediction outcomes. You can construct if-then scenarios and analyze the data for the identification of any upcoming trends or events.

However, this requires advanced analytics and involves complex mathematical computations. So, it is mostly done via quantitative research tools that come with advanced analytics capabilities.

8 Best Practices to Conduct Quantitative Research

Here are some best practices to keep in mind while conducting quantitative research:

1. Define Research Objectives

There can be many ways to collect data via quantitative research methods that are chosen as per the research objective and scope. These methods allow you to build your own observations regarding any hypotheses – unknown, entirely new, or unexplained. 

You can hypothesize a proof and build a prediction of outcomes supporting the same. You can also create a detailed stepwise plan for data collection, analysis, and testing. 

Below, we explore quantitative research methods and discuss some examples to enhance your understanding of them.

2. Keep Your Questions Simple

The surveys are meant to reach people en-masse, and that includes a wide demographic range with recipients from all walks of life. Asking simple questions will ensure that they grasp what’s being asked easily.

Read More: Proven Tips to Avoid Leading and Loaded Questions in Your Survey

3. Develop a Solid Research Design

Choose an appropriate research design that aligns with your objectives, whether it’s experimental, quasi-experimental, or correlational. You also need to pay attention to the sample size and sampling technique such that it represents the target population accurately.

4. Use Reliable & Valid Instruments

It’s crucial to select or develop measurement instruments such as questionnaires, scales, or tests that have been validated and are reliable. Before proceeding with the main study, pilot-test these instruments on a small sample to assess their effectiveness and make any necessary improvements.

5. Ensure Data Quality

Implement data collection protocols to minimize errors and bias during data gathering. Double-check data entries and cleaning procedures to eliminate any inconsistencies or missing values that may affect the accuracy of your results. For instance, you might regularly cross-verify data entries to identify and correct any discrepancies.

6. Employ Appropriate Data Analysis Techniques

Select statistical methods that match the nature of your data and research questions. Whether it’s regression analysis, t-tests, ANOVA, or other techniques, using the right approach is important for drawing meaningful conclusions. Utilize software tools like SPSS or R for data analysis to ensure the accuracy and reproducibility of your findings.

7. Interpret Results Objectively

Present your findings in a clear and unbiased manner. Avoid making unwarranted causal claims, especially in correlational studies. Instead, focus on describing the relationships and patterns observed in your data.

8. Address Ethical Considerations

Prioritize ethical considerations throughout your research process. Obtain informed consent from participants, ensuring their voluntary participation and confidentiality of data. Comply with ethical guidelines and gain approval from a governing body if necessary.

Read More: How to Find Survey Participants & Respondents

Types of Quantitative Research Methods

Quantitative research is usually conducted using two methods. They are-

• Primary quantitative research methods
• Secondary quantitative research methods

1. Primary Methods

Primary quantitative research is the most popular way of conducting market research. The differentiating factor of this method is that the researcher relies on collecting data firsthand instead of relying on data collected from previous research.

There are multiple types of primary quantitative research. They can be distinguished based on three distinctive aspects, which are:

A. Techniques & Types of Studies:

• Survey Research

Surveys are the easiest, most common, and one of the most sought-after quantitative research techniques. The main aim of a survey is to widely gather and describe the characteristics of a target population or customers. Surveys are the foremost quantitative method preferred by both small and large organizations.

They help them understand their customers, products, and other brand offerings in a proper manner.

Surveys can be conducted using various methods, such as online polls, web-based surveys, paper questionnaires, phone calls, or face-to-face interviews. Survey research allows organizations to understand customer opinions, preferences, and behavior, making it crucial for market research and decision-making.

You can watch this quick video to learn more about creating surveys.

Surveys are of two types:

• Cross-Sectional Surveys Cross-sectional surveys are used to collect data from a sample of the target population at a specific point in time. Researchers evaluate various variables simultaneously to understand the relationships and patterns within the data.
• Cross-sectional surveys are popular in retail, small and medium-sized enterprises (SMEs), and healthcare industries, where they assess customer satisfaction, market trends, and product feedback.
• Longitudinal Surveys Longitudinal surveys are conducted over an extended period, observing changes in respondent behavior and thought processes.
• Researchers gather data from the same sample multiple times, enabling them to study trends and developments over time. These surveys are valuable in fields such as medicine, applied sciences, and market trend analysis.

Surveys can be distributed via various channels. Some of the most popular ones are listed below:

• Email: Sending surveys via email is a popular and effective method. People recognize your brand, leading to a higher response rate. With ProProfs Survey Maker’s in-mail survey-filling feature, you can easily send out and collect survey responses.
• Embed on a website: Boost your response rate by embedding the survey on your website. When visitors are already engaged with your brand, they are more likely to take the survey.
• Social media: Take advantage of social media platforms to distribute your survey. People familiar with your brand are likely to respond, increasing your response numbers.
• QR codes: QR codes store your survey’s URL, and you can print or publish these codes in magazines, signs, business cards, or any object to make it easy for people to access your survey.
• SMS survey: Collect a high number of responses quickly with SMS surveys. It’s a time-effective way to reach your target audience.

Read More: 24 Different Types of Survey Methods With Examples

2. Correlational Research:

Correlational research aims to establish relationships between two or more variables.

Researchers use statistical analysis to identify patterns and trends in the data, but it does not determine causality between the variables. This method helps understand how changes in one variable may impact another.

Examples of correlational research questions include studying the relationship between stress and depression, fame and money, or classroom activities and student performance.

3. Causal-Comparative Research:

Causal-comparative research, also known as quasi-experimental research, seeks to determine cause-and-effect relationships between variables.

Researchers analyze how an independent variable influences a dependent variable, but they do not manipulate the independent variable. Instead, they observe and compare different groups to draw conclusions.

Causal-comparative research is useful in situations where it’s not ethical or feasible to conduct true experiments.

Examples of questions for this type of research include analyzing the effect of training programs on employee performance, studying the influence of customer support on client retention, investigating the impact of supply chain efficiency on cost reduction, etc.

4. Experimental Research:

Experimental research is based on testing theories to validate or disprove them. Researchers conduct experiments and manipulate variables to observe their impact on the outcomes.

This type of research is prevalent in natural and social sciences, and it is a powerful method to establish cause-and-effect relationships. By randomly assigning participants to experimental and control groups, researchers can draw more confident conclusions.

Examples of experimental research include studying the effectiveness of a new drug, the impact of teaching methods on student performance, or the outcomes of a marketing campaign.

B. Data collection methodologies

After defining research objectives, the next significant step in primary quantitative research is data collection. This involves using two main methods: sampling and conducting surveys or polls.

Sampling methods:

In quantitative research, there are two primary sampling methods: Probability and Non-probability sampling.

Probability Sampling

In probability sampling, researchers use the concept of probability to create samples from a population. This method ensures that every individual in the target audience has an equal chance of being selected for the sample.

There are four main types of probability sampling:

• Simple random sampling: Here, the elements or participants of a sample are selected randomly, and this technique is used in studies that are conducted over considerably large audiences. It works well for large target populations.
• Stratified random sampling: In this method, the entire population is divided into strata or groups, and the sample members get chosen randomly from these strata only. It is always ensured that different segregated strata do not overlap with each other.
• Cluster sampling: Here, researchers divide the population into clusters, often based on geography or demographics. Then, random clusters are selected for the sample.
• Systematic sampling: In this method, only the starting point of the sample is randomly chosen. All the other participants are chosen using a fixed interval. Researchers calculate this interval by dividing the size of the study population by the target sample size.

Non-probability Sampling

Non-probability sampling is a method where the researcher’s knowledge and experience guide the selection of samples. This approach doesn’t give all members of the target population an equal chance of being included in the sample.

There are five non-probability sampling models:

• Convenience sampling: The elements or participants are chosen on the basis of their nearness to the researcher. The people in close proximity can be studied and analyzed easily and quickly, as there is no other selection criterion involved. Researchers simply choose samples based on what is most convenient for them.
• Consecutive sampling: Similar to convenience sampling, researchers select samples one after another over a significant period. They can opt for a single participant or a group of samples to conduct quantitative research in a consecutive manner for a significant period of time. Once this is over, they can conduct the research from the start.
• Quota sampling: With quota sampling, researchers use their understanding of target traits and personalities to form groups (strata). They then choose samples from each stratum based on their own judgment.
• Snowball sampling: This method is used where the target audiences are difficult to contact and interviewed for data collection. Researchers start with a few participants and then ask them to refer others, creating a snowball effect.
• Judgmental sampling: In judgmental sampling, researchers rely solely on their experience and research skills to handpick samples that they believe will be most relevant to the study.

Read More: Data Collection Methods: Definition, Types & Examples

C. Data analysis techniques

To analyze the quantitative data accurately, you’ll need to use specific statistical methods such as:

• SWOT Analysis: This stands for Strengths, Weaknesses, Opportunities, and Threats analysis. Organizations use SWOT analysis to evaluate their performance internally and externally. It helps develop effective improvement strategies.
• Conjoint Analysis: This market research method uncovers how individuals make complex purchasing decisions. It involves considering trade-offs in their daily activities when choosing from a list of product/service options.
• Cross-tabulation: A preliminary statistical market analysis method that reveals relationships, patterns, and trends within various research study parameters.
• TURF Analysis: Short for Totally Unduplicated Reach and Frequency Analysis, this method helps analyze the reach and frequency of favorable communication sources. It provides insights into the potential of a target market.
• By using these statistical techniques and inferential statistics methods like confidence intervals and margin of error, you can draw meaningful insights from your primary quantitative research that you can use in making informed decisions.

II. Secondary Quantitative Research Methods

• Secondary quantitative research, also known as desk research, is a valuable method that uses existing data, called secondary data.
• Instead of collecting new data, researchers analyze and combine already available information to enhance their research. This approach involves gathering quantitative data from various sources such as the internet, government databases, libraries, and research reports.
• Secondary quantitative research plays a crucial role in validating data collected through primary quantitative research. It helps reinforce or challenge existing findings.

Here are five commonly used secondary quantitative research methods:

A. Data Available on the Internet:

The Internet has become a vast repository of data, making it easier for researchers to access a wealth of information. Online databases, websites, and research repositories provide valuable quantitative data for researchers to analyze and validate their primary research findings.

B. Government and Non-Government Sources:

Government agencies and non-government organizations often conduct extensive research and publish reports. These reports cover a wide range of topics, providing researchers with reliable and comprehensive data for quantitative analysis.

C. Public Libraries:

While less commonly used in the digital age, public libraries still hold valuable research reports, historical data, and publications that can contribute to quantitative research.

D. Educational Institutions:

Educational institutions frequently conduct research on various subjects. Their research reports and publications can serve as valuable sources of information for researchers, validating and supporting primary quantitative research outcomes.

E. Commercial Information Sources:

Commercial sources such as local newspapers, journals, magazines, and media outlets often publish relevant data on economic trends, market research, and demographic analyses. Researchers can access this data to supplement their own findings and draw better conclusions.

Advantages of Quantitative Research Methods

Quantitative research data is often standardized and can be easily used to generalize findings for making crucial business decisions and uncover insights to supplement the qualitative research findings.

Here are some core benefits this research methodology offers.

Direct Result Comparison

As the studies can be replicated for different cultural settings and different times, even with different groups of participants, they tend to be extremely useful. Researchers can compare the results of different studies in a statistical manner and arrive at comprehensive conclusions for a broader understanding.

Replication

Researchers can repeat the study by using standardized data collection protocols over well-structured data sets. They can also apply tangible definitions of abstract concepts to arrive at different conclusions for similar research objectives with minor variations.

Large Samples

As the research data comes from large samples, the researchers can process and analyze the data via highly reliable and consistent analysis procedures. They can arrive at well-defined conclusions that can be used to make the primary research more thorough and reliable.

Hypothesis Testing

This research methodology follows standardized and established hypothesis testing procedures. So, you have to be careful while reporting and analyzing your research data , and the overall quality of results gets improved.

Proven Examples of Quantitative Research Methods

Below, we discuss two excellent examples of quantitative research methods that were used by highly distinguished business and consulting organizations. Both examples show how different types of analysis can be performed with qualitative approaches and how the analysis is done once the data is collected.

1. STEP Project Global Consortium / KPMG 2019 Global Family Business survey

This research utilized quantitative methods to identify ways that kept the family businesses sustainably profitable with time.

The study also identified the ways in which the family business behavior changed with demographic changes and had “why” and “how” questions. Their qualitative research methods allowed the KPMG team to dig deeper into the mindsets and perspectives of the business owners and uncover unexpected research avenues as well.

It was a joint effort in which STEP Project Global Consortium collected 26 cases, and KPMG collected 11 cases.

The research reached the stage of data analysis in 2020, and the analysis process spanned over 4 stages.

The results, which were also the reasons why family businesses tend to lose their strength with time, were found to be:

• Family governance
• Family business legacy

2. EY Seren Teams Research 2020

This is yet another commendable example of qualitative research where the EY Seren Team digs into the unexplored depths of human behavior and how it affected their brand or service expectations.

The research was done across 200+ sources and involved in-depth virtual interviews with people in their homes, exploring their current needs and wishes. It also involved diary studies across the entire UK customer base to analyze human behavior changes and patterns.

The study also included interviews with professionals and design leaders from a wide range of industries to explore how COVID-19 transformed their industries. Finally, quantitative surveys were conducted to gain insights into the EY community after every 15 days.

The insights and results were:

• A culture of fear, daily resilience, and hopes for a better world and a better life – these were the macro trends.
• People felt massive digitization to be a resourceful yet demanding aspect as they have to adapt every day.
• Some people wished to have a new world with lots of possibilities, and some were looking for a new purpose.

Enhance Your Quantitative Research With Cutting-Edge Software

While no single research methodology can produce 100% reliable results, you can always opt for a hybrid research method by opting for the methods that are most relevant to your objective.

This understanding comes gradually as you learn how to implement the correct combination of qualitative and quantitative research methods for your research projects. For the best results, we recommend investing in smart, efficient, and scalable research tools that come with delightful reporting and advanced analytics to make every research initiative a success.

These software tools, such as ProProfs Survey Maker, come with pre-built survey templates and question libraries and allow you to create a high-converting survey in just a few minutes.

So, choose the best research partner, create the right research plan, and gather insights that drive sustainable growth for your business.

About the author

Emma David is a seasoned market research professional with 8+ years of experience. Having kick-started her journey in research, she has developed rich expertise in employee engagement, survey creation and administration, and data management. Emma believes in the power of data to shape business performance positively. She continues to help brands and businesses make strategic decisions and improve their market standing through her understanding of research methodologies.

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• Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on 6 May 2022 by Pritha Bhandari . Revised on 10 October 2022.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs surveys, questionnaire methods, open-ended vs closed-ended questions, question wording, question order, step-by-step guide to design, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyse data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives, placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleaning and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalise your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimising these will help you avoid sampling bias .

Prevent plagiarism, run a free check.

Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

• Cost-effective
• Easy to administer for small and large groups
• Anonymous and suitable for sensitive topics

But they may also be:

• Unsuitable for people with limited literacy or verbal skills
• Susceptible to a nonreponse bias (most people invited may not complete the questionnaire)
• Biased towards people who volunteer because impersonal survey requests often go ignored

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents.

Researcher-administered questionnaires can:

• Help you ensure the respondents are representative of your target audience
• Allow clarifications of ambiguous or unclear questions and answers
• Have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

• Costly and time-consuming to perform
• More difficult to analyse if you have qualitative responses
• Likely to contain experimenter bias or demand characteristics
• Likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions, or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalisable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert-type questions collect ordinal data using rating scales with five or seven points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio data, you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer ‘multiracial’ for the question on race rather than selecting from a restricted list.

• How do you feel about open science?
• How would you describe your personality?
• In your opinion, what is the biggest obstacle to productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarising responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorise answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counterargument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

• The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favour flexible work-from-home policies even after it’s safe to return to offices?
• Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barrelled questions. Double-barrelled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

You can organise the questions logically, with a clear progression from simple to complex. Alternatively, you can randomise the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioural or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

• How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
• Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
• Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimise order effects because they can be a source of systematic error or bias in your study.

Randomisation

Randomisation involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomisation, order effects will be minimised in your dataset. But a randomised order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Follow this step-by-step guide to design your questionnaire.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

• What topics or experiences are you studying?
• What specifically do you want to find out?
• Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalise your variables of interest into questionnaire items. Operationalising concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

• Are the respondents familiar with the language and terms used in your questions?
• Would any of the questions insult, confuse, or embarrass them?
• Do the response items for any closed-ended questions capture all possible answers?
• Are the response items mutually exclusive?
• Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivised or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomise questions. Randomising questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis.

You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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Quantitative Research Questions Examples & Types

• Post author By Andrew Chornyy
• Post date Feb 02, 2024
• No Comments on Quantitative Research Questions Examples & Types

Quantitative research questions form the backbone of solid data analysis , a crucial step in understanding market trends and consumer behavior. As we delve into the art of crafting precise, measurable questions, remember: the clarity of your inquiry directly impacts the quality of your findings. It’s not just about asking; it’s about asking right. Here at Plerdy, where data-driven insights are paramount, we recognize the power of well-structured questions in revealing actionable truths. In this article, we’ll guide you through shaping questions that bring clear, objective results, ensuring your research strikes the perfect balance between depth and simplicity. Discover the keys of effective quantitative inquiry and transform your data analysis with Plerdy.

Understanding Quantitative Research Questions

Quantitative research questions are the gateway to unlocking a world of data-driven insights. Central to effective research, these questions help us quantify variables, compare groups, and establish relationships in a structured, objective manner.

Definition: At their core, quantitative research questions seek measurable, numeric answers. They are designed to collect data that can be statistically analyzed, ensuring precise, objective outcomes. This approach is ideal for studies that require definitive results rather than subjective interpretations.

Characteristics:

• Specificity: They are clear and focused, aiming at specific variables or groups.
• Measurability: These questions ensure that responses can be quantified in numerical terms.
• Objectivity: They maintain neutrality, avoiding any bias in phrasing.
• Identifying Trends: By quantifying responses, these questions help in spotting patterns and trends in data.
• Making Comparisons: They allow for the comparison of different groups or variables.
• Predicting Outcomes: They assist in forecasting future trends based on current data.

Quantitative research questions are a vital tool for researchers and analysts. They provide a structured path to gaining valuable insights, crucial for making informed decisions. Whether you’re exploring market dynamics or investigating social trends, crafting these questions with precision is key to obtaining reliable, actionable data. As we journey through the nuances of these questions, keep in mind their potential to transform your understanding of the world around us.

Types of Quantitative Research Questions

In the realm of data analysis, understanding the types of quantitative research questions is pivotal for conducting robust research. These questions are classified based on their objective, leading to distinct approaches in data collection and interpretation.

Descriptive Questions:

• Objective: These questions aim to describe characteristics or functions.
• Structure: Often begin with “What is” or “How many.”
• What is the average income of a family in a specific region?
• How many hours per week do teenagers spend on social media ?

Comparative Questions:

• Objective: Designed to compare two or more groups or variables.
• Structure: Typically structured as “How does X compare to Y?”
• How does the customer satisfaction level differ between Brand A and Brand B?
• What is the difference in test scores between students who study online and those who attend traditional classes?

Relationship-based Questions:

• Objective: Explore the relationship between variables.
• Structure: Often phrased as “What is the relationship between X and Y?”
• What is the relationship between diet and heart health?
• How does exercise frequency relate to stress levels in working adults?

These types of questions are the bedrock of quantitative research, providing a clear path to analyze and interpret data. Descriptive questions lay the foundation by establishing basic facts. Comparative questions build on this by highlighting differences or similarities, while relationship-based questions delve deeper into how variables interact and influence each other.

To effectively employ these questions, researchers must be clear and precise in their phrasing, ensuring each question aligns with their specific research goals. By mastering these types, you can unlock a wealth of information and insights , critical for making informed decisions in any field. Remember that quantitative research may simplify complex data into usable knowledge.

Crafting Effective Quantitative Research Questions

Crafting effective quantitative research questions is a crucial step in any data-driven study, setting the stage for meaningful and reliable results. To ensure precision and clarity , following a structured approach is essential.

• Identifying Variables: Start by pinpointing the independent and dependent variables. The dependent variable is measured, while the independent variable is changed. For example, in a study on education, “teaching methods” could be your independent variable, and “student performance” could be the dependent variable. Understanding these variables helps in formulating a focused question.
• Question Structure: A well-structured question is clear and to the point. It directly addresses the relationship or comparison you’re investigating. Use phrases like “What impact does…,” “How does…,” or “What is the correlation between…” to structure your question. Keep it concise to avoid confusion.
• Ensuring Clarity and Precision: Avoid ambiguity. Your question should be understandable to someone outside your field. This means avoiding technical jargon and being as specific as possible about what you are investigating.

For instance:

• Unclear: How does technology affect learning?
• Clear: What is the impact of interactive digital textbooks on high school students’ math test scores?

Crafting effective quantitative research questions involves a balance of specificity, clarity, and structure. Begin by identifying your variables, then structure your question in a way that clearly conveys your investigative aim. Finally, ensure the wording is precise and free from ambiguity. This approach will not only refine your research focus but also enhance the comprehensibility and relevancy of your study, making it a valuable contribution to your field.

Real-world Examples of Quantitative Research Questions

Exploring quantitative research problems in real-world settings shows their practicality across fields. These examples not only demonstrate the diversity of these questions but also provide insight into how they drive specific, measurable outcomes.

• Education: In the educational sector, a common focus is on evaluating teaching methods and their effectiveness. An example question could be, “What is the impact of blended learning on the mathematics achievement of high school students compared to traditional teaching methods?” This question targets a specific teaching approach and measurable student performance .
• Healthcare: Healthcare research often revolves around patient outcomes and treatment efficacy. A question like, “How does a 6-week physical therapy program affect the recovery rate of post-operative knee surgery patients?” precisely addresses a treatment duration and a measurable patient outcome.
• Social Sciences: In social sciences, research questions might explore societal trends or behaviors. An example could be, “What is the correlation between social media usage and anxiety levels among young adults in urban areas?” This question is aimed at understanding the relationship between a widespread modern habit and a specific psychological condition.

Some real-world quantitative research questions on marketing strategy and social media monitoring:

Marketing Strategy Research Questions

• “How does varying the headline of an online advertisement influence its CTR?”
• “What impact does the use of different images in ads have on viewer engagement rates?”
• “Does incorporating video content in ads increase the conversion rate compared to static images?”
• “How does the integration of user testimonials in ad layouts affect viewer response rates?”
• “What effect does changing the color palette of an ad have on viewer attention span?”
• “Does the use of brighter colors in ads lead to an increased number of views and interactions?”
• “How does modifying the length and tone of ad copy influence the time users spend on the corresponding landing page?”
• “What is the effect of using direct vs. suggestive call-to-actions in ad texts on the user response rate?”
• “How does the positioning of an ad on a webpage influence the advertising cost per click?”
• “Does the placement of ads above the fold result in better engagement compared to below the fold?”
• “What is the effect of using demographic-based targeting on the total number of ad impressions?”
• “How does altering location targeting in digital ads influence the audience reach and diversity?”

Social Media Monitoring Research Questions

• “How frequently is our brand mentioned on social media platforms within a given time frame?”
• “What is the ratio of positive to negative brand mentions on social media during product launch periods?”
• “Which types of social media posts (images, videos, text) generate the highest engagement for our brand?”
• “What are the prevalent themes in user-generated content related to our brand on social platforms?”
• “How does the introduction of a new hashtag influence engagement and sharing rates on our social media channels?”
• “What impact do social media promotional campaigns have on follower growth and interaction rates?”

Advanced Ad Analysis Questions:

• “What is the click-through rate for ads with interactive elements like quizzes or polls compared to standard ads?”
• “How does the inclusion of interactive features in ads influence the time spent by users on the website?”
• “How do ad engagement rates vary during different seasons or major holidays?”
• “What impact does season-specific ad theming have on conversion rates?”
• “What is the optimal frequency for displaying retargeting ads to maximize conversions without causing ad fatigue?”
• “How does the timing of ad displays (time of day/week) affect user engagement and click rates?”

Deep Dive into Social Media Dynamics Questions:

• “What is the change in brand mentions and engagement rates after collaborating with social media influencers?”
• “How does influencer marketing affect the demographic profile of the brand’s social media followers?”
• “What is the average time spent by users on our social media pages before and after specific campaign launches?”
• “Which types of content (live videos, stories, posts) lead to the highest user interaction rates on our social media platforms?”
• “How does the engagement rate for our brand differ across various social media platforms?”
• “What are the differences in audience demographics and interaction patterns across different social media channels?”
• “What is the overall sentiment (positive, negative, neutral) expressed in user comments on our social media posts?”
• “How do product launches or service updates influence the sentiment of discussions around the brand on social media?”

Optimizing Digital Presence Questions:

• “How does social media traffic contribute to user behavior and conversion rates on the company’s website?”
• “What is the correlation between social media activity and lead generation on the company’s digital platforms?”
• “Which content strategies lead to the highest growth in followers and engagement on our social media channels?”
• “How does the frequency and type of content posted on social media influence brand perception and customer loyalty?”

These quantitative research questions are designed to provide concrete data that can help businesses refine their marketing strategies and social media presence for maximum effectiveness and engagement.

These real-world examples demonstrate the value of concise, targeted, and measurable quantitative research topics. By following this approach, researchers can effectively investigate and draw significant conclusions in their respective fields. Whether it’s understanding educational techniques, medical treatments, or societal behaviors, well-structured quantitative research questions are instrumental in uncovering valuable insights and contributing to informed decision-making .

Common Mistakes to Avoid

In the process of formulating quantitative research questions, certain common mistakes can significantly hinder the effectiveness of your study. Being aware of these pitfalls is essential for conducting meaningful research.

• Vague Wording: Ambiguity is the enemy of clarity. Questions like “How does social media influence behavior?” are too broad. Instead, specify the aspect of behavior, such as “How does social media use impact the attention span of teenagers?”
• Over-complicating Questions: Simplicity is key. Avoid convoluted questions that might confuse respondents. For instance, instead of asking “What are the various factors that affect the decision-making process of consumers purchasing technological gadgets?” simplify it to “What key factors influence consumer decisions when buying technological gadgets?”

Crafting clear, concise, and focused quantitative research questions is crucial. Avoid vague wording and over-complication. By steering clear of these common mistakes, you ensure that your research questions are robust and yield valuable, actionable data. This approach not only enhances the quality of your research but also increases its relevance and applicability to your target audience.

Quantitative research question writing is essential for gaining insights in any discipline. Through clarity, specificity, and focus, these questions become powerful tools in your analytical arsenal. Remember, the precision of your inquiry shapes the depth of your understanding. As we’ve explored various facets of quantitative questioning, the potential for data-driven decision-making becomes evident. For more insights and strategies to elevate your research, explore other articles on the Plerdy blog. Ready to dive deeper into data analytics ? Plerdy offers an array of tools to enhance your digital strategy. Check out Plerdy’s solutions for your next project – a step towards transforming data into actionable insights.

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Home » Quantitative Research – Methods, Types and Analysis

Quantitative Research – Methods, Types and Analysis

Table of Contents

Quantitative Research

Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.

Quantitative Research Methods

Quantitative Research Methods are as follows:

Descriptive Research Design

Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.

Correlational Research Design

Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.

Quasi-experimental Research Design

Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.

Survey Research

Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.

Quantitative Research Analysis Methods

Here are some commonly used quantitative research analysis methods:

Statistical Analysis

Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.

Regression Analysis

Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.

Factor Analysis

Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.

Structural Equation Modeling

Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.

Time Series Analysis

Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.

Multilevel Modeling

Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.

Applications of Quantitative Research

Quantitative research has many applications across a wide range of fields. Here are some common examples:

• Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
• Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
• Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
• Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
• Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.

Characteristics of Quantitative Research

Here are some key characteristics of quantitative research:

• Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
• Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
• Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
• Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
• Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
• Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
• Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.

Examples of Quantitative Research

Here are some examples of quantitative research in different fields:

• Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
• Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
• Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
• Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
• Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
• Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
• Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.

How to Conduct Quantitative Research

Here is a general overview of how to conduct quantitative research:

• Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
• Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
• Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
• Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
• Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
• Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.

When to use Quantitative Research

Here are some situations when quantitative research can be appropriate:

• To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
• To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
• To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
• To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
• To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.

Purpose of Quantitative Research

The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:

• Description : To provide a detailed and accurate description of a particular phenomenon or population.
• Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
• Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
• Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.

Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.

Advantages of Quantitative Research

There are several advantages of quantitative research, including:

• Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
• Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
• Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
• Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
• Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
• Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.

Limitations of Quantitative Research

There are several limitations of quantitative research, including:

• Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
• Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
• Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
• Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
• Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
• Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Designing and validating a research questionnaire - Part 1

Priya ranganathan.

Department of Anaesthesiology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India

Carlo Caduff

1 Department of Global Health and Social Medicine, King’s College London, London, United Kingdom

Questionnaires are often used as part of research studies to collect data from participants. However, the information obtained through a questionnaire is dependent on how it has been designed, used, and validated. In this article, we look at the types of research questionnaires, their applications and limitations, and how a new questionnaire is developed.

INTRODUCTION

In research studies, questionnaires are commonly used as data collection tools, either as the only source of information or in combination with other techniques in mixed-method studies. However, the quality and accuracy of data collected using a questionnaire depend on how it is designed, used, and validated. In this two-part series, we discuss how to design (part 1) and how to use and validate (part 2) a research questionnaire. It is important to emphasize that questionnaires seek to gather information from other people and therefore entail a social relationship between those who are doing the research and those who are being researched. This social relationship comes with an obligation to learn from others , an obligation that goes beyond the purely instrumental rationality of gathering data. In that sense, we underscore that any research method is not simply a tool but a situation, a relationship, a negotiation, and an encounter. This points to both ethical questions (what is the relationship between the researcher and the researched?) and epistemological ones (what are the conditions under which we can know something?).

At the start of any kind of research project, it is crucial to select the right methodological approach. What is the research question, what is the research object, and what can a questionnaire realistically achieve? Not every research question and not every research object are suitable to the questionnaire as a method. Questionnaires can only provide certain kinds of empirical evidence and it is thus important to be aware of the limitations that are inherent in any kind of methodology.

WHAT IS A RESEARCH QUESTIONNAIRE?

A research questionnaire can be defined as a data collection tool consisting of a series of questions or items that are used to collect information from respondents and thus learn about their knowledge, opinions, attitudes, beliefs, and behavior and informed by a positivist philosophy of the natural sciences that consider methods mainly as a set of rules for the production of knowledge; questionnaires are frequently used instrumentally as a standardized and standardizing tool to ask a set of questions to participants. Outside of such a positivist philosophy, questionnaires can be seen as an encounter between the researcher and the researched, where knowledge is not simply gathered but negotiated through a distinct form of communication that is the questionnaire.

STRENGTHS AND LIMITATIONS OF QUESTIONNAIRES

A questionnaire may not always be the most appropriate way of engaging with research participants and generating knowledge that is needed for a research study. Questionnaires have advantages that have made them very popular, especially in quantitative studies driven by a positivist philosophy: they are a low-cost method for the rapid collection of large amounts of data, even from a wide sample. They are practical, can be standardized, and allow comparison between groups and locations. However, it is important to remember that a questionnaire only captures the information that the method itself (as the structured relationship between the researcher and the researched) allows for and that the respondents are willing to provide. For example, a questionnaire on diet captures what the respondents say they eat and not what they are eating. The problem of social desirability emerges precisely because the research process itself involves a social relationship. This means that respondents may often provide socially acceptable and idealized answers, particularly in relation to sensitive questions, for example, alcohol consumption, drug use, and sexual practices. Questionnaires are most useful for studies investigating knowledge, beliefs, values, self-understandings, and self-perceptions that reflect broader social, cultural, and political norms that may well diverge from actual practices.

TYPES OF RESEARCH QUESTIONNAIRES

Research questionnaires may be classified in several ways:

Depending on mode of administration

Research questionnaires may be self-administered (by the research participant) or researcher administered. Self-administered (also known as self-reported or self-completed) questionnaires are designed to be completed by respondents without assistance from a researcher. Self-reported questionnaires may be administered to participants directly during hospital or clinic visits, mailed through the post or E-mail, or accessed through websites. This technique allows respondents to answer at their own pace and simplifies research costs and logistics. The anonymity offered by self-reporting may facilitate more accurate answers. However, the disadvantages are that there may be misinterpretations of questions and low response rates. Significantly, relevant context information is missing to make sense of the answers provided. Researcher-reported (or interviewer-reported) questionnaires may be administered face-to-face or through remote techniques such as telephone or videoconference and are associated with higher response rates. They allow the researcher to have a better understanding of how the data are collected and how answers are negotiated, but are more resource intensive and require more training from the researchers.

The choice between self-administered and researcher-administered questionnaires depends on various factors such as the characteristics of the target audience (e.g., literacy and comprehension level and ability to use technology), costs involved, and the need for confidentiality/privacy.

Depending on the format of the questions

Research questionnaires can have structured or semi-structured formats. Semi-structured questionnaires allow respondents to answer more freely and on their terms, with no restrictions on their responses. They allow for unusual or surprising responses and are useful to explore and discover a range of answers to determine common themes. Typically, the analysis of responses to open-ended questions is more complex and requires coding and analysis. In contrast, structured questionnaires provide a predefined set of responses for the participant to choose from. The use of standard items makes the questionnaire easier to complete and allows quick aggregation, quantification, and analysis of the data. However, structured questionnaires can be restrictive if the scope of responses is limited and may miss potential answers. They also may suggest answers that respondents may not have considered before. Respondents may be forced to fit their answers into the predetermined format and may not be able to express personal views and say what they really want to say or think. In general, this type of questionnaire can turn the research process into a mechanical, anonymous survey with little incentive for participants to feel engaged, understood, and taken seriously.

STRUCTURED QUESTIONS: FORMATS

Some examples of close-ended questions include:

e.g., Please indicate your marital status:

• Prefer not to say.

e.g., Describe your areas of work (circle or tick all that apply):

• Clinical service
• Administration
• Strongly agree
• Strongly disagree.
• Numerical scales: Please rate your current pain on a scale of 1–10 where 1 is no pain and 10 is the worst imaginable pain
• Symbolic scales: For example, the Wong-Baker FACES scale to rate pain in older children
• Ranking: Rank the following cities as per the quality of public health care, where 1 is the best and 5 is the worst.

A matrix questionnaire consists of a series of rows with items to be answered with a series of columns providing the same answer options. This is an efficient way of getting the respondent to provide answers to multiple questions. The EORTC QLQ-C30 is an example of a matrix questionnaire.[ 1 ]

For a more detailed review of the types of research questions, readers are referred to a paper by Boynton and Greenhalgh.[ 2 ]

USING PRE-EXISTING QUESTIONNAIRES VERSUS DEVELOPING A NEW QUESTIONNAIRE

Before developing a questionnaire for a research study, a researcher can check whether there are any preexisting-validated questionnaires that might be adapted and used for the study. The use of validated questionnaires saves time and resources needed to design a new questionnaire and allows comparability between studies.

However, certain aspects need to be kept in mind: is the population/context/purpose for which the original questionnaire was designed similar to the new study? Is cross-cultural adaptation required? Are there any permission needed to use the questionnaire? In many situations, the development of a new questionnaire may be more appropriate given that any research project entails both methodological and epistemological questions: what is the object of knowledge and what are the conditions under which it can be known? It is important to understand that the standardizing nature of questionnaires contributes to the standardization of objects of knowledge. Thus, the seeming similarity in the object of study across diverse locations may be an artifact of the method. Whatever method one uses, it will always operate as the ground on which the object of study is known.

DESIGNING A NEW RESEARCH QUESTIONNAIRE

Once the researcher has decided to design a new questionnaire, several steps should be considered:

Gathering content

It creates a conceptual framework to identify all relevant areas for which the questionnaire will be used to collect information. This may require a scoping review of the published literature, appraising other questionnaires on similar topics, or the use of focus groups to identify common themes.

Create a list of questions

Questions need to be carefully formulated with attention to language and wording to avoid ambiguity and misinterpretation. Table 1 lists a few examples of poorlyworded questions that could have been phrased in a more appropriate manner. Other important aspects to be noted are:

Examples of poorly phrased questions in a research questionnaire

• Provide a brief introduction to the research study along with instructions on how to complete the questionnaire
• Allow respondents to indicate levels of intensity in their replies, so that they are not forced into “yes” or “no” answers where intensity of feeling may be more appropriate
• Collect specific and detailed data wherever possible – this can be coded into categories. For example, age can be captured in years and later classified as <18 years, 18–45 years, 46 years, and above. The reverse is not possible
• Avoid technical terms, slang, and abbreviations. Tailor the reading level to the expected education level of respondents
• The format of the questionnaire should be attractive with different sections for various subtopics. The font should be large and easy to read, especially if the questionnaire is targeted at the elderly
• Question sequence: questions should be arranged from general to specific, from easy to difficult, from facts to opinions, and sensitive topics should be introduced later in the questionnaire.[ 3 ] Usually, demographic details are captured initially followed by questions on other aspects
• Use contingency questions: these are questions which need to be answered only by a subgroup of the respondents who provide a particular answer to a previous question. This ensures that participants only respond to relevant sections of the questionnaire, for example, Do you smoke? If yes, then how long have you been smoking? If not, then please go to the next section.

TESTING A QUESTIONNAIRE

A questionnaire needs to be valid and reliable, and therefore, any new questionnaire needs to be pilot tested in a small sample of respondents who are representative of the larger population. In addition to validity and reliability, pilot testing provides information on the time taken to complete the questionnaire and whether any questions are confusing or misleading and need to be rephrased. Validity indicates that the questionnaire measures what it claims to measure – this means taking into consideration the limitations that come with any questionnaire-based study. Reliability means that the questionnaire yields consistent responses when administered repeatedly even by different researchers, and any variations in the results are due to actual differences between participants and not because of problems with the interpretation of the questions or their responses. In the next article in this series, we will discuss methods to determine the reliability and validity of a questionnaire.

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6 Main Qualitative Questions Examples

Qualitative vs. quantitative research, the importance of qualitative questions, key elements of effective qualitative research questions, role in the research design, 6 types and examples of qualitative questions, how to choose qualitative research questions, start collecting qualitative data right now, fullsession pricing plans.

• FAQs about Qualitative Research Questions

Qualitative research uncovers the details of human behavior, beliefs, and feelings. It gives us insights that numbers can’t always tell.

These research questions help us understand the “how” and “why” of things. 

In this article, we’ll look at six examples of good qualitative questions. We aim to highlight how picking the right questions can improve your study.

It is important to understand the differences between qualitative and quantitative research.

Qualitative research questions aim to explore concepts, experiences, and perspectives. They offer the qualitative research expert an in-depth insight into the subject.

On the other hand, quantitative research questions focus on measurable aspects. They seek statistical comparisons to reach factual conclusions.

Both quantitative and qualitative questions have important roles in research. They serve unique purposes and provide different types of data.

Unlike quantitative research, qualitative questions aren’t about numbers and statistical analysis. It’s about understanding the reason behind data from a focus group.

Why pick qualitative research? When conducting qualitative research, you want to know why someone does something, not just count how many times they do it.

You ask, and you listen. That’s the power of qualitative research. The right question is a key that unlocks valuable knowledge.

Effective qualitative research aims to unveil hidden truths. But how do you achieve it? With thought-provoking questions.

Here are the elements of the qualitative research questions for an in-depth exploration:

Open-ended and Exploratory

Qualitative research questions aim to understand the “how” and “why” of a topic. They invite people to share their views and stories.

Open-ended and exploratory questions help researchers grasp complex issues. These questions allow for diverse and detailed answers to a particular subject.

Clarity and Focus

Qualitative research questions need to be clear, focused, and brief. They help ensure the research meets its goals. 

Being specific guides data collection and analysis, leading to valuable findings.

Relationships and Personal Experiences

Qualitative research questions examine how different factors relate to personal experiences and seek to understand why people act in certain ways. 

They also explore how people respond to their surroundings, including culture and workplace rules.

Ethical Considerations

When creating qualitative research questions, it’s important to think about ethics. Questions need to respect participants’ dignity, privacy, and independence.

This makes sure that the research does not cause harm or distress. Ethics also matter when explaining and sharing results, as researchers must present data truthfully and with care.

The right qualitative research questions are crucial in the design of research projects for several reasons:

• Guidance on Research Methods: Directs the choice of qualitative research methods. Options include:
• Focus Groups: Small groups discuss topics with a moderator.
• In-Depth Interviews: Offers detailed insights from individual viewpoints.
• Qualitative Surveys: Gathers open-ended responses from a broad audience.
• Ensuring the Right Tools are Used: Matching objectives with the most suitable research tools. Enables thorough investigation and captures the complexity of experiences.
• Facilitating a Clear Understanding: Aims to uncover not just what is happening but why. Explores thoughts, feelings, behaviors, and the effects of various influences.
• Informing the Research Design: Influences all design aspects, including participant selection and analysis framework. Ensures ethical standards guide the research process.

Here are six types of qualitative questions with examples:

1. Descriptive

These questions are aimed at describing the characteristics or features of a product.

• Example 1: How do users describe their initial impressions when they first interact with our new software interface?
• Example 2: What are the specific colors and design elements that users notice about the new smartphone model when they see it for the first time?

2. Exploratory

Exploratory questions are designed to investigate how things work or how users interact with a product.

• Example 1: What strategies do users employ to navigate through the features of our newly launched app?
• Example 2: How do users attempt to solve problems when they encounter errors using our digital service platform?

3. Experiential

These questions focus on the user’s experiences and emotions related to the product.

• Example 1: Can you describe a memorable experience you had while using our product?
• Example 2: What emotions do you feel when using our product under stressful conditions?

4. Comparative

Comparative questions look at differences between products, user groups, or other variables.

• Example 1: How do new users’ experiences with our product compare to those of long-term users?
• Example 2: In what ways does our product perform better or worse than our main competitor’s product in similar conditions?

5. Process-oriented

These questions delve into the processes or sequences of actions related to using the product.

• Example 1: Can you walk me through the process you typically follow when setting up our product for the first time?
• Example 2: What steps do you take when you troubleshoot an issue with our product?

6. Theoretical

Theoretical questions aim to understand the underlying principles or theories that explain user behavior or product dynamics.

• Example 1: What theories can explain why users prefer our product’s design over traditional designs?
• Example 2: Based on your knowledge, what psychological principles might influence how users adapt to our product’s innovative features?

When selecting qualitative questions, the aim is to deeply understand user interactions, perceptions, and experiences with the product. 

Here are some key considerations for choosing good qualitative research questions:

• Define Your Objectives  

Start by clearly defining the research objective of your product testing. What specific aspects of the product are you looking to evaluate? Are you interested in usability, aesthetics, functionality, or user satisfaction? Your objectives will guide the types of questions you need to ask. For example, if user satisfaction is your focus, you might ask about the user’s emotional response to the product.

• Consider the Type of Qualitative Research  

Different types of qualitative methods—such as ethnographic, narrative, phenomenological, or grounded theory—may influence the style and structure of your questions. For instance, narrative research focuses on stories and experiences, so your questions should encourage storytelling about product use.

• Ensure Questions are Open-Ended  

Qualitative questions should be open-ended to allow for detailed responses that can reveal insights not anticipated by the researcher. Instead of asking, “Do you like our product?” which prompts a yes or no answer, ask, “How do you feel about our product?” to encourage a more detailed and nuanced response.

• Be Clear and Concise  

While questions should allow for open-ended answers, they must also be clear and concise to avoid confusing the respondent. Ambiguity can lead to unreliable qualitative data , as different participants might interpret the questions differently.

• Sequence the Questions Logically  

The order in which you ask questions can impact the flow of conversation and the quality of information gathered. Start with more general questions to make the respondent comfortable before moving to more specific or sensitive topics. This sequence helps build rapport and can lead to more honest and detailed responses later in the discussion.

• Consider the Participant  

Tailor your questions to fit the background and experience level of your participants. Questions that are too technical or too basic can frustrate users or fail to elicit useful information. Understanding your audience allows you to frame questions that are appropriately challenging and engaging.

• Pilot Test Your Questions  

Before finalizing your set of questions, conduct a pilot test with a small group of participants. This testing can reveal if any questions are confusing or ineffective at eliciting useful responses. Feedback from this phase can be invaluable in refining your questions.

• Be Prepared to Adapt  

Finally, while it’s important to prepare your questions carefully, also be flexible during actual interactions. The conversation may reveal new paths of inquiry that are worth exploring. Being adaptive can help you capture deep insights that strictly adhering to a prepared list of questions might miss.

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FAQs about Qualitative Research Questions 

What is a qualitative research question.

Qualitative research questions focus on ways to gather deep insights into people’s experiences, beliefs, and perceptions. Such questions invite detailed narrative responses.

Can qualitative research questions change during the study?

It’s not uncommon for qualitative research questions to evolve during the course of a study. As preliminary data is collected and analyzed, new insights may emerge that prompt a qualitative researcher to refine their questions. 

How are qualitative questions used in business?

Businesses use qualitative questions to uncover valuable insights. They can explore customer behavior, employee satisfaction, or market trends. One example could be: “What factors drive consumer loyalty to our brand?”

Are there specific words to use in qualitative research questions?

Yes, use words like “describe,” “explain,” and “how” to frame qualitative questions. These terms promote more detailed and comprehensive answers. They are key to qualitative analysis.

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