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How to write a research plan: Step-by-step guide

Last updated

30 January 2024

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Today’s businesses and institutions rely on data and analytics to inform their product and service decisions. These metrics influence how organizations stay competitive and inspire innovation. However, gathering data and insights requires carefully constructed research, and every research project needs a roadmap. This is where a research plan comes into play.

There’s general research planning; then there’s an official, well-executed research plan. Whatever data-driven research project you’re gearing up for, the research plan will be your framework for execution. The plan should also be detailed and thorough, with a diligent set of criteria to formulate your research efforts. Not including these key elements in your plan can be just as harmful as having no plan at all.

Read this step-by-step guide for writing a detailed research plan that can apply to any project, whether it’s scientific, educational, or business-related.

• What is a research plan?

A research plan is a documented overview of a project in its entirety, from end to end. It details the research efforts, participants, and methods needed, along with any anticipated results. It also outlines the project’s goals and mission, creating layers of steps to achieve those goals within a specified timeline.

Without a research plan, you and your team are flying blind, potentially wasting time and resources to pursue research without structured guidance.

The principal investigator, or PI, is responsible for facilitating the research oversight. They will create the research plan and inform team members and stakeholders of every detail relating to the project. The PI will also use the research plan to inform decision-making throughout the project.

• Why do you need a research plan?

Create a research plan before starting any official research to maximize every effort in pursuing and collecting the research data. Crucially, the plan will model the activities needed at each phase of the research project.

Like any roadmap, a research plan serves as a valuable tool providing direction for those involved in the project—both internally and externally. It will keep you and your immediate team organized and task-focused while also providing necessary definitions and timelines so you can execute your project initiatives with full understanding and transparency.

External stakeholders appreciate a working research plan because it’s a great communication tool, documenting progress and changing dynamics as they arise. Any participants of your planned research sessions will be informed about the purpose of your study, while the exercises will be based on the key messaging outlined in the official plan.

Here are some of the benefits of creating a research plan document for every project:

Project organization and structure

Well-informed participants

All stakeholders and teams align in support of the project

Clearly defined project definitions and purposes

Distractions are eliminated, prioritizing task focus

Timely management of individual task schedules and roles

Costly reworks are avoided

• What should a research plan include?

The different aspects of your research plan will depend on the nature of the project. However, most official research plan documents will include the core elements below. Each aims to define the problem statement, devising an official plan for seeking a solution.

Specific project goals and individual objectives

Ideal strategies or methods for reaching those goals

Required resources

Descriptions of the target audience, sample sizes, demographics, and scopes

Key performance indicators (KPIs)

Project background

Research and testing support

Preliminary studies and progress reporting mechanisms

Cost estimates and change order processes

Depending on the research project’s size and scope, your research plan could be brief—perhaps only a few pages of documented plans. Alternatively, it could be a fully comprehensive report. Either way, it’s an essential first step in dictating your project’s facilitation in the most efficient and effective way.

• How to write a research plan for your project

When you start writing your research plan, aim to be detailed about each step, requirement, and idea. The more time you spend curating your research plan, the more precise your research execution efforts will be.

Account for every potential scenario, and be sure to address each and every aspect of the research.

Consider following this flow to develop a great research plan for your project:

Define your project’s purpose

Start by defining your project’s purpose. Identify what your project aims to accomplish and what you are researching. Remember to use clear language.

Thinking about the project’s purpose will help you set realistic goals and inform how you divide tasks and assign responsibilities. These individual tasks will be your stepping stones to reach your overarching goal.

Additionally, you’ll want to identify the specific problem, the usability metrics needed, and the intended solutions.

Know the following three things about your project’s purpose before you outline anything else:

What you’re doing

Why you’re doing it

What you expect from it

Identify individual objectives

With your overarching project objectives in place, you can identify any individual goals or steps needed to reach those objectives. Break them down into phases or steps. You can work backward from the project goal and identify every process required to facilitate it.

Be mindful to identify each unique task so that you can assign responsibilities to various team members. At this point in your research plan development, you’ll also want to assign priority to those smaller, more manageable steps and phases that require more immediate or dedicated attention.

Select research methods

Research methods might include any of the following:

User interviews: this is a qualitative research method where researchers engage with participants in one-on-one or group conversations. The aim is to gather insights into their experiences, preferences, and opinions to uncover patterns, trends, and data.

Field studies: this approach allows for a contextual understanding of behaviors, interactions, and processes in real-world settings. It involves the researcher immersing themselves in the field, conducting observations, interviews, or experiments to gather in-depth insights.

Card sorting: participants categorize information by sorting content cards into groups based on their perceived similarities. You might use this process to gain insights into participants’ mental models and preferences when navigating or organizing information on websites, apps, or other systems.

Focus groups: use organized discussions among select groups of participants to provide relevant views and experiences about a particular topic.

Diary studies: ask participants to record their experiences, thoughts, and activities in a diary over a specified period. This method provides a deeper understanding of user experiences, uncovers patterns, and identifies areas for improvement.

Five-second testing: participants are shown a design, such as a web page or interface, for just five seconds. They then answer questions about their initial impressions and recall, allowing you to evaluate the design’s effectiveness.

Surveys: get feedback from participant groups with structured surveys. You can use online forms, telephone interviews, or paper questionnaires to reveal trends, patterns, and correlations.

Tree testing: tree testing involves researching web assets through the lens of findability and navigability. Participants are given a textual representation of the site’s hierarchy (the “tree”) and asked to locate specific information or complete tasks by selecting paths.

Usability testing: ask participants to interact with a product, website, or application to evaluate its ease of use. This method enables you to uncover areas for improvement in digital key feature functionality by observing participants using the product.

Live website testing: research and collect analytics that outlines the design, usability, and performance efficiencies of a website in real time.

There are no limits to the number of research methods you could use within your project. Just make sure your research methods help you determine the following:

What do you plan to do with the research findings?

What decisions will this research inform? How can your stakeholders leverage the research data and results?

Recruit participants and allocate tasks

Next, identify the participants needed to complete the research and the resources required to complete the tasks. Different people will be proficient at different tasks, and having a task allocation plan will allow everything to run smoothly.

Prepare a thorough project summary

Every well-designed research plan will feature a project summary. This official summary will guide your research alongside its communications or messaging. You’ll use the summary while recruiting participants and during stakeholder meetings. It can also be useful when conducting field studies.

Ensure this summary includes all the elements of your research project. Separate the steps into an easily explainable piece of text that includes the following:

An introduction: the message you’ll deliver to participants about the interview, pre-planned questioning, and testing tasks.

Interview questions: prepare questions you intend to ask participants as part of your research study, guiding the sessions from start to finish.

An exit message: draft messaging your teams will use to conclude testing or survey sessions. These should include the next steps and express gratitude for the participant’s time.

Create a realistic timeline

While your project might already have a deadline or a results timeline in place, you’ll need to consider the time needed to execute it effectively.

Realistically outline the time needed to properly execute each supporting phase of research and implementation. And, as you evaluate the necessary schedules, be sure to include additional time for achieving each milestone in case any changes or unexpected delays arise.

For this part of your research plan, you might find it helpful to create visuals to ensure your research team and stakeholders fully understand the information.

Determine how to present your results

A research plan must also describe how you intend to present your results. Depending on the nature of your project and its goals, you might dedicate one team member (the PI) or assume responsibility for communicating the findings yourself.

In this part of the research plan, you’ll articulate how you’ll share the results. Detail any materials you’ll use, such as:

Presentations and slides

A project report booklet

A project findings pamphlet

Documents with key takeaways and statistics

Graphic visuals to support your findings

• Format your research plan

As you create your research plan, you can enjoy a little creative freedom. A plan can assume many forms, so format it how you see fit. Determine the best layout based on your specific project, intended communications, and the preferences of your teams and stakeholders.

Find format inspiration among the following layouts:

Written outlines

Narrative storytelling

Visual mapping

Graphic timelines

Remember, the research plan format you choose will be subject to change and adaptation as your research and findings unfold. However, your final format should ideally outline questions, problems, opportunities, and expectations.

• Research plan example

Imagine you’ve been tasked with finding out how to get more customers to order takeout from an online food delivery platform. The goal is to improve satisfaction and retain existing customers. You set out to discover why more people aren’t ordering and what it is they do want to order or experience. 

You identify the need for a research project that helps you understand what drives customer loyalty. But before you jump in and start calling past customers, you need to develop a research plan—the roadmap that provides focus, clarity, and realistic details to the project.

Here’s an example outline of a research plan you might put together:

Project title

Project members involved in the research plan

Purpose of the project (provide a summary of the research plan’s intent)

Objective 1 (provide a short description for each objective)

Objective 2

Objective 3

Proposed timeline

Audience (detail the group you want to research, such as customers or non-customers)

Budget (how much you think it might cost to do the research)

Risk factors/contingencies (any potential risk factors that may impact the project’s success)

Remember, your research plan doesn’t have to reinvent the wheel—it just needs to fit your project’s unique needs and aims.

Customizing a research plan template

Some companies offer research plan templates to help get you started. However, it may make more sense to develop your own customized plan template. Be sure to include the core elements of a great research plan with your template layout, including the following:

Introductions to participants and stakeholders

Background problems and needs statement

Significance, ethics, and purpose

Research methods, questions, and designs

Preliminary beliefs and expectations

Implications and intended outcomes

Realistic timelines for each phase

Conclusion and presentations

How many pages should a research plan be?

Generally, a research plan can vary in length between 500 to 1,500 words. This is roughly three pages of content. More substantial projects will be 2,000 to 3,500 words, taking up four to seven pages of planning documents.

What is the difference between a research plan and a research proposal?

A research plan is a roadmap to success for research teams. A research proposal, on the other hand, is a dissertation aimed at convincing or earning the support of others. Both are relevant in creating a guide to follow to complete a project goal.

What are the seven steps to developing a research plan?

While each research project is different, it’s best to follow these seven general steps to create your research plan:

Defining the problem

Identifying goals

Choosing research methods

Recruiting participants

Preparing the brief or summary

Establishing task timelines

Defining how you will present the findings

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FLEET LIBRARY | Research Guides

Rhode island school of design, create a research plan: research plan.

• Research Plan
• Literature Review
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• Related Guides

A research plan is a framework that shows how you intend to approach your topic. The plan can take many forms: a written outline, a narrative, a visual/concept map or timeline. It's a document that will change and develop as you conduct your research. Components of a research plan

1. Research conceptualization - introduces your research question

2. Research methodology - describes your approach to the research question

3. Literature review, critical evaluation and synthesis - systematic approach to locating,

    reviewing and evaluating the work (text, exhibitions, critiques, etc) relating to your topic

4. Communication - geared toward an intended audience, shows evidence of your inquiry

Research conceptualization refers to the ability to identify specific research questions, problems or opportunities that are worthy of inquiry. Research conceptualization also includes the skills and discipline that go beyond the initial moment of conception, and which enable the researcher to formulate and develop an idea into something researchable ( Newbury 373).

Research methodology refers to the knowledge and skills required to select and apply appropriate methods to carry through the research project ( Newbury 374) .

Method describes a single mode of proceeding; methodology describes the overall process.

Method - a way of doing anything especially according to a defined and regular plan; a mode of procedure in any activity

Methodology - the study of the direction and implications of empirical research, or the sustainability of techniques employed in it; a method or body of methods used in a particular field of study or activity *Browse a list of research methodology books  or this guide on Art & Design Research

Literature Review, critical evaluation & synthesis

A literature review is a systematic approach to locating, reviewing, and evaluating the published work and work in progress of scholars, researchers, and practitioners on a given topic.

Critical evaluation and synthesis is the ability to handle (or process) existing sources. It includes knowledge of the sources of literature and contextual research field within which the person is working ( Newbury 373).

Literature reviews are done for many reasons and situations. Here's a short list:

Sources to consult while conducting a literature review:

Online catalogs of local, regional, national, and special libraries

meta-catalogs such as worldcat , Art Discovery Group , europeana , world digital library or RIBA

subject-specific online article databases (such as the Avery Index, JSTOR, Project Muse)

digital institutional repositories such as Digital Commons @RISD ; see Registry of Open Access Repositories

Open Access Resources recommended by RISD Research LIbrarians

works cited in scholarly books and articles

print bibliographies

the internet-locate major nonprofit, research institutes, museum, university, and government websites

search google scholar to locate grey literature & referenced citations

trade and scholarly publishers

fellow scholars and peers

Communication                              

Communication refers to the ability to

• structure a coherent line of inquiry
• communicate your findings to your intended audience
• make skilled use of visual material to express ideas for presentations, writing, and the creation of exhibitions ( Newbury 374)

Research plan framework: Newbury, Darren. "Research Training in the Creative Arts and Design." The Routledge Companion to Research in the Arts . Ed. Michael Biggs and Henrik Karlsson. New York: Routledge, 2010. 368-87. Print.

About the author

Except where otherwise noted, this guide is subject to a Creative Commons Attribution license

source document

  Routledge Companion to Research in the Arts

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• Last Updated: Sep 20, 2023 5:05 PM
• URL: https://risd.libguides.com/researchplan

• Research Guides
• Begin Your Research
• Outline and Plan

Begin Your Research: Outline and Plan

• Research Process
• Background Info
• Research Questions

Outlining and Planning Ahead: Confining or Comforting?

Creating a plan and outline before starting your research paper can lead to a more successful and satisfying writing process. Contrary to concerns about stifling creativity, planning ahead actually frees your mind from cluttered thoughts and allows for creativity to flourish within the boundaries of your rough plan. Just like various aspects of the natural and man-made world, successful creations often begin with some form of structure or boundary. Outlines serve as recipes for your paper, while research plans function as shopping lists, helping you organize your ideas and check your progress once you've completed your work.

Why Create an Outline?

According to the Purdue OWL's Writing Process guide , using an outline is helpful when wanting to "show the hierarchical relationship or logical ordering of information. For research papers, an outline may help you keep track of large amounts of information." Outlines even help those that are preparing a speech or presentation to deliver in front of an audience. Therefore, an outline has many benefits in aiding your writing, organizing your thoughts, keeping your material in logical structures, and giving your writing a boundary within which to keep focus. Making any kind of outline, no matter how rough or polished, will benefit you.

What is an Outline?

An outline is a structured document that lists the main parts of your research paper, essay, presentation, or report. It provides a roadmap for your planned writing, utilizing numbered lists to indicate the larger and nested structures.

• You can further divide your subtopics as needed using Arabic numerals, but there should always be more than one.
• Further subdivision
• Subtopic of First Part (more specific in relationship to the First Part heading)
• Subtopic of First Part (more specific in relationship to the heading above)
• Subtopic of First Part (there should always be more than one subtopic of each main part)

Unless required to use a certain outline template, you have the freedom to choose the type of outline that suits you best, whether it is rough or structured with full sentences, phrases, and alphanumeric ordered lists. Any kind of outline can be effective in aiding your writing process. In conclusion, outlining is a valuable tool for successful writing, allowing you to organize your thoughts and achieve your goals efficiently. By creating a clear plan, you can enhance your creativity and produce a more cohesive and well-structured piece of work.

Please open Purdue OWL's Writing Process guide  or separate PDF which provides examples of full sentence and alphanumeric outlines.

• Research Outline Template (RTF file)
• Research Outline Template (PDF File)

Creating a Research Plan

Your final step in the beginning stages of your research journey is making a plan for the rest of your research and writing steps. Treat it like a schedule or shopping list, utilizing a short to-do list or a detailed schedule. Remember, this plan you devise is not restrictive; it's a guide to set achievable goals within one overall process. Here's what to include:

What should you include in a research plan?

As stated above, you don't need to fill out an entire research plan right now, *but as you learn more throughout this "How to Research" guide series. The following items are recommended items to put in your research plan:

• The research topic you have chosen and explored
• The research question or thesis statement you have drafted
• Any important assignment due dates, especially if you have to turn anything in at different stages (topic selection, annotated bibliography, rough draft, final draft)
• The kind of information you are interested in including (supporting or contrasting perspectives, definitions, analysis, facts, background, or statistics)*
• The search terms you have brainstormed and planned in the form of keywords, phrases, or search strings*
• The places you will go to look for information (library searchable databases, websites, physical libraries)*
• If there are any limitations or prohibited sources (no website or encyclopedias, for example)

You can use the provided templates to create your research plan as you progress through the "How to Research" guide series.

• Research Plan Template (RTF File)
• Research Plan Template (PDF File)

Congratulations on completing the initial steps of your research journey, and now you're ready to explore different types of information and sources.

• Learn the Types of Research Sources
• Find Research Sources

Image Source

Unless otherwise indicated, all images are courtesy of Adobe Stock. Paul J. Meyer quote image made in Canva, courtesy of Kristen Cook. The Research Outline Template was adapted from EasyBib.com.

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The Research Plan

Where to start with scholarly research, expectations for research, scholarly vs. popular sources, grey literature, primary vs. secondary sources, preliminary research.

• Create a Plan

A good essay is grounded in good research, which requires clear direction, patience and persistence.

Research helps you to focus your topic, formulate and refine your thesis, and discover details, opinions, and facts to support your overall argument. You are better equipped to search for and sort sources when you have made decisions about your topic and developed a working thesis.

It is important that your research be accurate, reliable, relevant, and, for many disciplines, recent. The quality of your research determines the efficacy of your argument and your instructor’s assessment of your work.

Maintaining your academic integrity is an important factor that is assessed by your professors. The sources you use must be properly documented, accurately communicated, and clearly explained in relation to your topic and thesis. You are less likely to copy the text word for word or paraphrase too closely if you have spent some time thinking about how the research will inform your thesis and if you think carefully about your research process

Types of Sources

Many assignments will require you to focus primarily on scholarly, peer-reviewed sources. Check with your professor or the assignment instructions for guidance on using popular sources. 

Scholarly sources are supported by the peer review process, which means they are sources that have been evaluated by other experts in the same field.

Scholarly sources:

• Are written by and for academics
• Ensure that data is thoroughly checked
• Cite all evidence
• Make arguments which are supported by research
• Meet conventions of scholarship in the discipline
• Are written in formal, academic language

Popular sources are written for a wider, general audience and are more informal in tone. Sources like newspaper articles, documentaries and corporate websites are not scholarly, but they can offer useful information that you can include in your analysis alongside evidence presented by scholarly sources.

Grey literature is produced by entities whose main task is NOT publishing. Industry, think tanks, government departments, scholarly societies and associations can all produce grey literature. Grey literature can include reports, working papers, newsletters, government documents, speeches, white papers, and urban plans. Grey literature also includes newsletters, emails, blogs and other social networking sites. In addition to scholarly sources, grey literature can offer valuable evidence to your essay, but be sure to consider whether its use is appropriate for the discipline, the course, or the assignment.

In some disciplines, such as history, philosophy, or English literature, it is important to distinguish between primary and secondary sources.

Primary sources are original, first-hand materials. A primary source may be a government document, census data, a short story, old letters, or a piece of art.

Secondary source s are articles, editorials, textbooks, books, and other published materials that may interpret data, works of literature, ideas or events.

You may need to do preliminary research to find or refine a topic. Some early reading can help you narrow your focus, establish research questions, and avoid the frustration of directionless research.

Places to Start  

• Begin with course materials. The syllabus, required or recommended readings, textbooks and lecture notes will often provide ideas for a topic, while focusing on the major themes of your course.
• During the early stages of research, you can use reference works, such as discipline-specific textbooks, encyclopedias and dictionaries, or Wikipedia, for an introduction to your topic. Use the library subject guide to find useful reference works in your subject. Be sure that only material from your scholarly research, not Wikipedia , is used and cited in your paper.

The materials found during the preliminary research stage can help you to identify main concepts, key terminology, and important literature on the topic.

Planning your Research

A plan establishes research goals and clarifies direction.

A clear direction and plan for research helps you assess the quality and relevance of sources. 

Creating a Research Plan

In advance of beginning a search for evidence, take time to make a plan.

• Develop specific questions about your topic: what do you want to know and how does it relate to your thesis?
• Create a list of key words and synonyms for your search. Include specific and more general terms; establish parameters for your search (place, time, theory, field, species) but be open to related materials.
• Identify types of evidence you are required to use (research requirements of the assignment) and you will find informative for your topic. Think about where you can find these types of sources.

Look to your course content to identify the types of sources commonly used in the discipline; here are some examples:

• Peer-Reviewed scholarship: Argumentative articles, clinical trials, empirical articles (use library databases, google scholar)
• Numerical and financial data: export data, quality of life measures (see library subject guides
• Visual records (maps, old photographs, film)
• NGO documents: Stakeholder reports, Best practice documents
• Government documents: laws, legislation, reports

Research Plan worksheet - Accessible version (Word doc)

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• Knowledge Base

Methodology

• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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The value of a good research plan

A research plan is a guiding framework that can make or break the efficiency and success of your research project. Oftentimes teams avoid them because they’ve earned a reputation as a dry or actionless document — however, this doesn’t have to be the case.

In this article, we’ll go over the most important aspects of a good research plan and show you how they can be visual and actionable with monday.com Work OS.

Don’t miss more quality content!

Why is the research plan pivotal to a research project.

A research plan is pivotal to a research project because it identifies and helps define your focus, method, and goals while also outlining the research project from start to finish.

This type of plan is often necessary to:

• Apply for grants or internal company funding.
• Discover possible research partners or business partners.
• Take your research from an idea into reality.

It will also control the entire journey of the research project through every stage by defining crucial research questions and the hypothesis (theory) that you’ll strive to prove or disprove.

What goes into a research plan?

The contents of a thorough research plan should include a hypothesis, methodology, and more. There is some variation between academic and commercial research, but these are common elements:

• Hypothesis:  the problem you are trying to solve and the basis for a theoretical solution. For example, if I reduce my intake of calories, I’ll lose weight.
• Research questions: research questions help guide your investigation into particular issues. If you were looking into the potential impact of outsourcing production, you might ask something like: how would outsourcing impact our production costs?
• Research method: the method you’ll use to get the data for your research. For example, a case study, survey, interviews, a clinical trial, or user tests.
• Definitions: a glossary for the research plan, explaining the terminology that you use throughout the document.
• Conceptual frameworks:  a conceptual framework helps illustrate what you think you’ll discover with your research. In a sense, it’s a visual representation of a more complex hypothesis.

For commercial plans, there will also likely be a budget and timeline estimate, as well as concrete hypothetical benefits for the company (such as how much money the project should save you).

OK, so you’ve got a handle on the building blocks of a research plan, but how should you actually write it?

How do you write a research plan on monday.com?

The first, and perhaps most crucial part of having a good research plan is having the right medium for creating and sharing it. Using a pre-defined template can also make it much easier to get started.

On monday.com, you can choose from several templates like the Project Proposal Template or better yet the Research Power Tools Template to manage all aspects of your project including important communication with internal and external stakeholders and teammates.

Use your template to:

• Create workdocs
• Upload assets
• Provide feedback
• Assign task owners
• Automate communication

The next step in writing a research plan is choosing the topic. To pick the right topic, focus on these factors:

• What are the priorities of the potential funder/employer, such as the company or institution?
• Are there any relevant recent studies with results you can build on and explore with further research?
• Can you creatively adapt your experience — whether post-grad or professional — to make you the natural candidate? They don’t just need to believe in the research project, but also in your ability to manage it successfully.

Do your research, no pun intended. Once you’ve got the topic, you need to work on fleshing out the core ideas with the building blocks we mentioned above.

• Get specific with your research questions and goals. Don’t go with, “how can we revolutionize our HR practices?” Instead use, “what is the economic and environmental impact of only accepting digital CVs?”
• Use clear language aimed at gatekeepers.  If it’s a CTO (Chief Technology Officer) or a lab committee, you can use well-known technical terms. If they aren’t technical experts, adjust accordingly.
• Include preliminary data or highlight similar studies.  For companies, showing that a similar approach helped a competitor is a better argument than an empty assertion.

The recommended length of the plan depends on who you’re sending it to and their expectations. If possible, look at successful examples or directly ask your potential employers about their preferences. Not only do you need the right idea, but you also need to present it in the right way for your research project to have a fighting chance.

What is a good research plan?

A good research plan is one that gets accepted and funded to start doing the research.

If you want to plan a pivotal study, it’s not enough to consider the problem in a vacuum. You also need to evaluate how you can best communicate the value of your project to the gatekeepers.

Consider the entirety of your current situation and what that means for your project.

For example, inputs like funding, staff, IP, and how the scale of the project lines up with your company’s research budget. Or how it aligns with the goals of a University program. If the primary goal of the research is to impact a company or government agency directly, you should consider these stages of research engagement.

( Image Source )

• Inputs: anything from funding and staff to company IP that you need to both run the project and implement any results. Does this line up with the budget?
• Activities: case studies, trials, surveys, the actual research.
• Outputs: the final reports, any publications, and raw data.
• Outcome: how will it directly impact the company, organization, or larger society?
• Impacts: what are the indirect benefits or downsides?

In an internal research proposal, you can outline these aspects in separate sections. That allows different execs or managers to focus on the details that matter most to them. You must also work to engage stakeholders  and make sure that they understand the importance of your project.

Frequently asked questions

What are the 5 purposes of research.

The 2 primary purposes of research are to gather information or test an existing theory. When broken down further, you can see 5 more specific purposes:

• Exploratory research  is an early-stage inquiry that explores a topic for further study down the line, like exploring the deep ocean with a submersible vehicle.
• Descriptive research  aims to explore and describe a specific substance, person, or phenomenon.
• Explanatory research  is about figuring out the causal relationship, why something happens.
• Predictive research  is all about trying to predict what might happen in specific situations based on the properties of the research object.
• Meta-research  looks for overarching insights from multiple sources and tests the validity of common hypotheses.

What is a research work plan?

A research work plan is another name for a research plan, which is a critical component of any research proposal. Universities, labs, and companies use them to evaluate research projects before they decide to accept them.

As a researcher, it’s essential when targeting a funding opportunity of any kind.

What are the methods of research?

There are many research methods ranging from a simple online survey to a high-budget clinical study. Here are some examples of popular data collection methods:

• Clinical trials
• Experiments
• Case studies
• Observations

Which one is right for your plan depends on your hypothesis, goals, industry regulations, and more.

Create a dynamic research plan

If you want to turn your research project into a reality, you need to go beyond the academic and into management mode.

With a template from monday.com, you can plan out a research project from start to finish. Including goals and objectives, budget estimates, milestones, and more.

Send this article to someone who’d like it.

6.3 Steps in a Successful Marketing Research Plan

Learning outcomes.

By the end of this section, you will be able to:

• 1 Identify and describe the steps in a marketing research plan.
• 2 Discuss the different types of data research.
• 3 Explain how data is analyzed.
• 4 Discuss the importance of effective research reports.

Define the Problem

There are seven steps to a successful marketing research project (see Figure 6.3 ). Each step will be explained as we investigate how a marketing research project is conducted.

The first step, defining the problem, is often a realization that more information is needed in order to make a data-driven decision. Problem definition is the realization that there is an issue that needs to be addressed. An entrepreneur may be interested in opening a small business but must first define the problem that is to be investigated. A marketing research problem in this example is to discover the needs of the community and also to identify a potentially successful business venture.

Many times, researchers define a research question or objectives in this first step. Objectives of this research study could include: identify a new business that would be successful in the community in question, determine the size and composition of a target market for the business venture, and collect any relevant primary and secondary data that would support such a venture. At this point, the definition of the problem may be “Why are cat owners not buying our new cat toy subscription service?”

Additionally, during this first step we would want to investigate our target population for research. This is similar to a target market, as it is the group that comprises the population of interest for the study. In order to have a successful research outcome, the researcher should start with an understanding of the problem in the current situational environment.

Develop the Research Plan

Step two is to develop the research plan. What type of research is necessary to meet the established objectives of the first step? How will this data be collected? Additionally, what is the time frame of the research and budget to consider? If you must have information in the next week, a different plan would be implemented than in a situation where several months were allowed. These are issues that a researcher should address in order to meet the needs identified.

Research is often classified as coming from one of two types of data: primary and secondary. Primary data is unique information that is collected by the specific researcher with the current project in mind. This type of research doesn’t currently exist until it is pulled together for the project. Examples of primary data collection include survey, observation, experiment, or focus group data that is gathered for the current project.

Secondary data is any research that was completed for another purpose but can be used to help inform the research process. Secondary data comes in many forms and includes census data, journal articles, previously collected survey or focus group data of related topics, and compiled company data. Secondary data may be internal, such as the company’s sales records for a previous quarter, or external, such as an industry report of all related product sales. Syndicated data , a type of external secondary data, is available through subscription services and is utilized by many marketers. As you can see in Table 6.1 , primary and secondary data features are often opposite—the positive aspects of primary data are the negative side of secondary data.

There are four research types that can be used: exploratory, descriptive, experimental, and ethnographic research designs (see Figure 6.4 ). Each type has specific formats of data that can be collected. Qualitative research can be shared through words, descriptions, and open-ended comments. Qualitative data gives context but cannot be reduced to a statistic. Qualitative data examples are categorical and include case studies, diary accounts, interviews, focus groups, and open-ended surveys. By comparison, quantitative data is data that can be reduced to number of responses. The number of responses to each answer on a multiple-choice question is quantitative data. Quantitative data is numerical and includes things like age, income, group size, and height.

Exploratory research is usually used when additional general information in desired about a topic. When in the initial steps of a new project, understanding the landscape is essential, so exploratory research helps the researcher to learn more about the general nature of the industry. Exploratory research can be collected through focus groups, interviews, and review of secondary data. When examining an exploratory research design, the best use is when your company hopes to collect data that is generally qualitative in nature. 7

For instance, if a company is considering a new service for registered users but is not quite sure how well the new service will be received or wants to gain clarity of exactly how customers may use a future service, the company can host a focus group. Focus groups and interviews will be examined later in the chapter. The insights collected during the focus group can assist the company when designing the service, help to inform promotional campaign options, and verify that the service is going to be a viable option for the company.

Descriptive research design takes a bigger step into collection of data through primary research complemented by secondary data. Descriptive research helps explain the market situation and define an “opinion, attitude, or behavior” of a group of consumers, employees, or other interested groups. 8 The most common method of deploying a descriptive research design is through the use of a survey. Several types of surveys will be defined later in this chapter. Descriptive data is quantitative in nature, meaning the data can be distilled into a statistic, such as in a table or chart.

Again, descriptive data is helpful in explaining the current situation. In the opening example of LEGO , the company wanted to describe the situation regarding children’s use of its product. In order to gather a large group of opinions, a survey was created. The data that was collected through this survey allowed the company to measure the existing perceptions of parents so that alterations could be made to future plans for the company.

Experimental research , also known as causal research , helps to define a cause-and-effect relationship between two or more factors. This type of research goes beyond a correlation to determine which feature caused the reaction. Researchers generally use some type of experimental design to determine a causal relationship. An example is A/B testing, a situation where one group of research participants, group A, is exposed to one treatment and then compared to the group B participants, who experience a different situation. An example might be showing two different television commercials to a panel of consumers and then measuring the difference in perception of the product. Another example would be to have two separate packaging options available in different markets. This research would answer the question “Does one design sell better than the other?” Comparing that to the sales in each market would be part of a causal research study. 9

The final method of collecting data is through an ethnographic design. Ethnographic research is conducted in the field by watching people interact in their natural environment. For marketing research, ethnographic designs help to identify how a product is used, what actions are included in a selection, or how the consumer interacts with the product. 10

Examples of ethnographic research would be to observe how a consumer uses a particular product, such as baking soda. Although many people buy baking soda, its uses are vast. So are they using it as a refrigerator deodorizer, a toothpaste, to polish a belt buckle, or to use in baking a cake?

Select the Data Collection Method

Data collection is the systematic gathering of information that addresses the identified problem. What is the best method to do that? Picking the right method of collecting data requires that the researcher understand the target population and the design picked in the previous step. There is no perfect method; each method has both advantages and disadvantages, so it’s essential that the researcher understand the target population of the research and the research objectives in order to pick the best option.

Sometimes the data desired is best collected by watching the actions of consumers. For instance, how many cars pass a specific billboard in a day? What website led a potential customer to the company’s website? When are consumers most likely to use the snack vending machines at work? What time of day has the highest traffic on a social media post? What is the most streamed television program this week? Observational research is the collecting of data based on actions taken by those observed. Many data observations do not require the researched individuals to participate in the data collection effort to be highly valuable. Some observation requires an individual to watch and record the activities of the target population through personal observations .

Unobtrusive observation happens when those being observed aren’t aware that they are being watched. An example of an unobtrusive observation would be to watch how shoppers interact with a new stuffed animal display by using a one-way mirror. Marketers can identify which products were handled more often while also determining which were ignored.

Other methods can use technology to collect the data instead. Instances of mechanical observation include the use of vehicle recorders, which count the number of vehicles that pass a specific location. Computers can also assess the number of shoppers who enter a store, the most popular entry point for train station commuters, or the peak time for cars to park in a parking garage.

When you want to get a more in-depth response from research participants, one method is to complete a one-on-one interview . One-on-one interviews allow the researcher to ask specific questions that match the respondent’s unique perspective as well as follow-up questions that piggyback on responses already completed. An interview allows the researcher to have a deeper understanding of the needs of the respondent, which is another strength of this type of data collection. The downside of personal interviews it that a discussion can be very time-consuming and results in only one respondent’s answers. Therefore, in order to get a large sample of respondents, the interview method may not be the most efficient method.

Taking the benefits of an interview and applying them to a small group of people is the design of a focus group . A focus group is a small number of people, usually 8 to 12, who meet the sample requirements. These individuals together are asked a series of questions where they are encouraged to build upon each other’s responses, either by agreeing or disagreeing with the other group members. Focus groups are similar to interviews in that they allow the researcher, through a moderator, to get more detailed information from a small group of potential customers (see Figure 6.5 ).

Link to Learning

Focus groups.

Focus groups are a common method for gathering insights into consumer thinking and habits. Companies will use this information to develop or shift their initiatives. The best way to understand a focus group is to watch a few examples or explanations. TED-Ed has this video that explains how focus groups work.

You might be asking when it is best to use a focus group or a survey. Learn the differences, the pros and cons of each, and the specific types of questions you ask in both situations in this article .

Preparing for a focus group is critical to success. It requires knowing the material and questions while also managing the group of people. Watch this video to learn more about how to prepare for a focus group and the types of things to be aware of.

One of the benefits of a focus group over individual interviews is that synergy can be generated when a participant builds on another’s ideas. Additionally, for the same amount of time, a researcher can hear from multiple respondents instead of just one. 11 Of course, as with every method of data collection, there are downsides to a focus group as well. Focus groups have the potential to be overwhelmed by one or two aggressive personalities, and the format can discourage more reserved individuals from speaking up. Finally, like interviews, the responses in a focus group are qualitative in nature and are difficult to distill into an easy statistic or two.

Combining a variety of questions on one instrument is called a survey or questionnaire . Collecting primary data is commonly done through surveys due to their versatility. A survey allows the researcher to ask the same set of questions of a large group of respondents. Response rates of surveys are calculated by dividing the number of surveys completed by the total number attempted. Surveys are flexible and can collect a variety of quantitative and qualitative data. Questions can include simplified yes or no questions, select all that apply, questions that are on a scale, or a variety of open-ended types of questions. There are four types of surveys (see Table 6.2 ) we will cover, each with strengths and weaknesses defined.

Let’s start off with mailed surveys —surveys that are sent to potential respondents through a mail service. Mailed surveys used to be more commonly used due to the ability to reach every household. In some instances, a mailed survey is still the best way to collect data. For example, every 10 years the United States conducts a census of its population (see Figure 6.6 ). The first step in that data collection is to send every household a survey through the US Postal Service (USPS). The benefit is that respondents can complete and return the survey at their convenience. The downside of mailed surveys are expense and timeliness of responses. A mailed survey requires postage, both when it is sent to the recipient and when it is returned. That, along with the cost of printing, paper, and both sending and return envelopes, adds up quickly. Additionally, physically mailing surveys takes time. One method of reducing cost is to send with bulk-rate postage, but that slows down the delivery of the survey. Also, because of the convenience to the respondent, completed surveys may be returned several weeks after being sent. Finally, some mailed survey data must be manually entered into the analysis software, which can cause delays or issues due to entry errors.

Phone surveys are completed during a phone conversation with the respondent. Although the traditional phone survey requires a data collector to talk with the participant, current technology allows for computer-assisted voice surveys or surveys to be completed by asking the respondent to push a specific button for each potential answer. Phone surveys are time intensive but allow the respondent to ask questions and the surveyor to request additional information or clarification on a question if warranted. Phone surveys require the respondent to complete the survey simultaneously with the collector, which is a limitation as there are restrictions for when phone calls are allowed. According to Telephone Consumer Protection Act , approved by Congress in 1991, no calls can be made prior to 8:00 a.m. or after 9:00 p.m. in the recipient’s time zone. 12 Many restrictions are outlined in this original legislation and have been added to since due to ever-changing technology.

In-person surveys are when the respondent and data collector are physically in the same location. In-person surveys allow the respondent to share specific information, ask questions of the surveyor, and follow up on previous answers. Surveys collected through this method can take place in a variety of ways: through door-to-door collection, in a public location, or at a person’s workplace. Although in-person surveys are time intensive and require more labor to collect data than some other methods, in some cases it’s the best way to collect the required data. In-person surveys conducted through a door-to-door method is the follow-up used for the census if respondents do not complete the mailed survey. One of the downsides of in-person surveys is the reluctance of potential respondents to stop their current activity and answer questions. Furthermore, people may not feel comfortable sharing private or personal information during a face-to-face conversation.

Electronic surveys are sent or collected through digital means and is an opportunity that can be added to any of the above methods as well as some new delivery options. Surveys can be sent through email, and respondents can either reply to the email or open a hyperlink to an online survey (see Figure 6.7 ). Additionally, a letter can be mailed that asks members of the survey sample to log in to a website rather than to return a mailed response. Many marketers now use links, QR codes, or electronic devices to easily connect to a survey. Digitally collected data has the benefit of being less time intensive and is often a more economical way to gather and input responses than more manual methods. A survey that could take months to collect through the mail can be completed within a week through digital means.

Design the Sample

Although you might want to include every possible person who matches your target market in your research, it’s often not a feasible option, nor is it of value. If you did decide to include everyone, you would be completing a census of the population. Getting everyone to participate would be time-consuming and highly expensive, so instead marketers use a sample , whereby a portion of the whole is included in the research. It’s similar to the samples you might receive at the grocery store or ice cream shop; it isn’t a full serving, but it does give you a good taste of what the whole would be like.

So how do you know who should be included in the sample? Researchers identify parameters for their studies, called sample frames . A sample frame for one study may be college students who live on campus; for another study, it may be retired people in Dallas, Texas, or small-business owners who have fewer than 10 employees. The individual entities within the sampling frame would be considered a sampling unit . A sampling unit is each individual respondent that would be considered as matching the sample frame established by the research. If a researcher wants businesses to participate in a study, then businesses would be the sampling unit in that case.

The number of sampling units included in the research is the sample size . Many calculations can be conducted to indicate what the correct size of the sample should be. Issues to consider are the size of the population, the confidence level that the data represents the entire population, the ease of accessing the units in the frame, and the budget allocated for the research.

There are two main categories of samples: probability and nonprobability (see Figure 6.8 ). Probability samples are those in which every member of the sample has an identified likelihood of being selected. Several probability sample methods can be utilized. One probability sampling technique is called a simple random sample , where not only does every person have an identified likelihood of being selected to be in the sample, but every person also has an equal chance of exclusion. An example of a simple random sample would be to put the names of all members of a group into a hat and simply draw out a specific number to be included. You could say a raffle would be a good example of a simple random sample.

Another probability sample type is a stratified random sample , where the population is divided into groups by category and then a random sample of each category is selected to participate. For instance, if you were conducting a study of college students from your school and wanted to make sure you had all grade levels included, you might take the names of all students and split them into different groups by grade level—freshman, sophomore, junior, and senior. Then, from those categories, you would draw names out of each of the pools, or strata.

A nonprobability sample is a situation in which each potential member of the sample has an unknown likelihood of being selected in the sample. Research findings that are from a nonprobability sample cannot be applied beyond the sample. Several examples of nonprobability sampling are available to researchers and include two that we will look at more closely: convenience sampling and judgment sampling.

The first nonprobability sampling technique is a convenience sample . Just like it sounds, a convenience sample is when the researcher finds a group through a nonscientific method by picking potential research participants in a convenient manner. An example might be to ask other students in a class you are taking to complete a survey that you are doing for a class assignment or passing out surveys at a basketball game or theater performance.

A judgment sample is a type of nonprobability sample that allows the researcher to determine if they believe the individual meets the criteria set for the sample frame to complete the research. For instance, you may be interested in researching mothers, so you sit outside a toy store and ask an individual who is carrying a baby to participate.

Collect the Data

Now that all the plans have been established, the instrument has been created, and the group of participants has been identified, it is time to start collecting data. As explained earlier in this chapter, data collection is the process of gathering information from a variety of sources that will satisfy the research objectives defined in step one. Data collection can be as simple as sending out an email with a survey link enclosed or as complex as an experiment with hundreds of consumers. The method of collection directly influences the length of this process. Conducting personal interviews or completing an experiment, as previously mentioned, can add weeks or months to the research process, whereas sending out an electronic survey may allow a researcher to collect the necessary data in a few days. 13

Analyze and Interpret the Data

Once the data has been collected, the process of analyzing it may begin. Data analysis is the distillation of the information into a more understandable and actionable format. The analysis itself can take many forms, from the use of basic statistics to a more comprehensive data visualization process. First, let’s discuss some basic statistics that can be used to represent data.

The first is the mean of quantitative data. A mean is often defined as the arithmetic average of values. The formula is:

A common use of the mean calculation is with exam scores. Say, for example, you have earned the following scores on your marketing exams: 72, 85, 68, and 77. To find the mean, you would add up the four scores for a total of 302. Then, in order to generate a mean, that number needs to be divided by the number of exam scores included, which is 4. The mean would be 302 divided by 4, for a mean test score of 75.5. Understanding the mean can help to determine, with one number, the weight of a particular value.

Another commonly used statistic is median. The median is often referred to as the middle number. To generate a median, all the numeric answers are placed in order, and the middle number is the median. Median is a common statistic when identifying the income level of a specific geographic region. 14 For instance, the median household income for Albuquerque, New Mexico, between 2015 and 2019 was $52,911. 15 In this case, there are just as many people with an income above the amount as there are below.

Mode is another statistic that is used to represent data of all types, as it can be used with quantitative or qualitative data and represents the most frequent answer. Eye color, hair color, and vehicle color can all be presented with a mode statistic. Additionally, some researchers expand on the concept of mode and present the frequency of all responses, not just identifying the most common response. Data such as this can easily be presented in a frequency graph, 16 such as the one in Figure 6.9 .

Additionally, researchers use other analyses to represent the data rather than to present the entirety of each response. For example, maybe the relationship between two values is important to understand. In this case, the researcher may share the data as a cross tabulation (see Figure 6.10 ). Below is the same data as above regarding social media use cross tabulated with gender—as you can see, the data is more descriptive when you can distinguish between the gender identifiers and how much time is spent per day on social media.

Not all data can be presented in a graphical format due to the nature of the information. Sometimes with qualitative methods of data collection, the responses cannot be distilled into a simple statistic or graph. In that case, the use of quotations, otherwise known as verbatims , can be used. These are direct statements presented by the respondents. Often you will see a verbatim statement when reading a movie or book review. The critic’s statements are used in part or in whole to represent their feelings about the newly released item.

Infographics

As they say, a picture is worth a thousand words. For this reason, research results are often shown in a graphical format in which data can be taken in quickly, called an infographic .

Check out this infographic on what components make for a good infographic. As you can see, a good infographic needs four components: data, design, a story, and the ability to share it with others. Without all four pieces, it is not as valuable a resource as it could be. The ultimate infographic is represented as the intersection of all four.

Infographics are particularly advantageous online. Refer to this infographic on why they are beneficial to use online .

Prepare the Research Report

The marketing research process concludes by sharing the generated data and makes recommendations for future actions. What starts as simple data must be interpreted into an analysis. All information gathered should be conveyed in order to make decisions for future marketing actions. One item that is often part of the final step is to discuss areas that may have been missed with the current project or any area of further study identified while completing it. Without the final step of the marketing research project, the first six steps are without value. It is only after the information is shared, through a formal presentation or report, that those recommendations can be implemented and improvements made. The first six steps are used to generate information, while the last is to initiate action. During this last step is also when an evaluation of the process is conducted. If this research were to be completed again, how would we do it differently? Did the right questions get answered with the survey questions posed to the respondents? Follow-up on some of these key questions can lead to additional research, a different study, or further analysis of data collected.

Methods of Quantifying Marketing Research

One of the ways of sharing information gained through marketing research is to quantify the research . Quantifying the research means to take a variety of data and compile into a quantity that is more easily understood. This is a simple process if you want to know how many people attended a basketball game, but if you want to quantify the number of students who made a positive comment on a questionnaire, it can be a little more complicated. Researchers have a variety of methods to collect and then share these different scores. Below are some of the most common types used in business.

Is a customer aware of a product, brand, or company? What is meant by awareness? Awareness in the context of marketing research is when a consumer is familiar with the product, brand, or company. It does not assume that the consumer has tried the product or has purchased it. Consumers are just aware. That is a measure that many businesses find valuable. There are several ways to measure awareness. For instance, the first type of awareness is unaided awareness . This type of awareness is when no prompts for a product, brand, or company are given. If you were collecting information on fast-food restaurants, you might ask a respondent to list all the fast-food restaurants that serve a chicken sandwich. Aided awareness would be providing a list of products, brands, or companies and the respondent selects from the list. For instance, if you give a respondent a list of fast-food restaurants and ask them to mark all the locations with a chicken sandwich, you are collecting data through an aided method. Collecting these answers helps a company determine how the business location compares to those of its competitors. 17

Customer Satisfaction (CSAT)

Have you ever been asked to complete a survey at the end of a purchase? Many businesses complete research on buying, returning, or other customer service processes. A customer satisfaction score , also known as CSAT, is a measure of how satisfied customers are with the product, brand, or service. A CSAT score is usually on a scale of 0 to 100 percent. 18 But what constitutes a “good” CSAT score? Although what is identified as good can vary by industry, normally anything in the range from 75 to 85 would be considered good. Of course, a number higher than 85 would be considered exceptional. 19

Customer Acquisition Cost (CAC) and Customer Effort Score (CES)

Other metrics often used are a customer acquisition cost (CAC) and customer effort score (CES). How much does it cost a company to gain customers? That’s the purpose of calculating the customer acquisition cost. To calculate the customer acquisition cost , a company would need to total all expenses that were accrued to gain new customers. This would include any advertising, public relations, social media postings, etc. When a total cost is determined, it is divided by the number of new customers gained through this campaign.

The final score to discuss is the customer effort score , also known as a CES. The CES is a “survey used to measure the ease of service experience with an organization.” 20 Companies that are easy to work with have a better CES than a company that is notorious for being difficult. An example would be to ask a consumer about the ease of making a purchase online by incorporating a one-question survey after a purchase is confirmed. If a number of responses come back negative or slightly negative, the company will realize that it needs to investigate and develop a more user-friendly process.

Knowledge Check

It’s time to check your knowledge on the concepts presented in this section. Refer to the Answer Key at the end of the book for feedback.

• Defining the problem
• Developing the research plan
• Selecting a data collection method
• Designing the sample
• you are able to send it to all households in an area
• it is inexpensive
• responses are automatically loaded into the software
• the data comes in quickly
• Primary data
• Secondary data
• Secondary and primary data
• Professional data
• It shows how respondents answered two variables in relation to each other and can help determine patterns by different groups of respondents.
• By presenting the data in the form of a picture, the information is easier for the reader to understand.
• It is an easy way to see how often one answer is selected by the respondents.
• This analysis can used to present interview or focus group data.

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Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/principles-marketing/pages/1-unit-introduction

• Authors: Dr. Maria Gomez Albrecht, Dr. Mark Green, Linda Hoffman
• Publisher/website: OpenStax
• Book title: Principles of Marketing
• Publication date: Jan 25, 2023
• Location: Houston, Texas
• Book URL: https://openstax.org/books/principles-marketing/pages/1-unit-introduction
• Section URL: https://openstax.org/books/principles-marketing/pages/6-3-steps-in-a-successful-marketing-research-plan

© Jan 9, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

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World Leaders in Research-Based User Experience

Planning research with generative ai.

April 5, 2024 2024-04-05

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AI chatbots (like ChatGPT, Google’s Gemini, and Microsoft Copilot) can support UX researchers of all experience levels in planning their research.

In This Article:

What is a research plan, using ai chatbots to write a research plan.

Good research always starts with a plan.

A research plan is a document that outlines the research objectives and how the research will be executed.

Research plans should include:

• The research goals or questions that the research is hoping to achieve or answer
• The method to be used and a description of how it will be carried out
• The tasks or questions that will be given to study participants
• The profile of the target participants
• The screener questionnaire used to recruit participants

Creating a research plan can be time-consuming. Even with a good template, a researcher must generate research questions, select the appropriate method(s), decide how to run sessions, and often create study collateral (like screeners and tasks) from scratch. The good news is that AI can help with many, if not all, of these tasks!

It can be tempting to just ask an AI tool to give you a research plan for a project. Don’t do that.

❌ Bad Prompt : Generate a research plan for a usability test of a food-delivery app.

This kind of request results in a generic, template-like response, partly because AI lacks the context to propose a complete research plan and partly because of how the model has been trained.

To construct a useful research plan, deconstruct the plan into parts and have the AI chatbot tackle each part individually. You can assemble responses in a final research plan.

Don’t expect the AI to ask you the right questions in order to get a comprehensive outcome. View the AI tool as a UX assistant , not as a UX mentor. You need to feed into the AI all the steps and details you want it to consider.

Follow the steps below for the best results.

Step 1: Provide Context

Imagine asking an experienced colleague for recommendations on what research study to run without giving them any context on what project you’re working on and what you’re trying to achieve. They would probably say, "It depends on what you’re trying to learn.” Conversing with AI presents no exception.

Start your conversation with enough context , especially if the AI tool does not already have this information stored about you or your current project. ( ChatGPT 4 allows users to store context for each new conversation.)

The contextual information you share should include who you work for, the scope of your project, and what you’re looking to achieve. Remember that some AI tools may use your conversations to train their models, so share only information you would be comfortable with being in the open domain.

 Prompt Template: I work for [type or organization] . My company provides [what kind of product, service, or experience] . I need to run a user-research study to learn [something about users or a problem] .

Step 2: Generate Research Questions

After providing the AI tool with context, ask it to suggest specific research questions for the study. Here’s an example from a recent study on research repositories that I conducted for NN/g.

Prompt Example: I will run a research study and report on how UX practitioners across different organizations set up and use research repositories. Please generate 10 research questions that would be suitable for this sort of study.

It’s a good idea to ask generative AI tools for more options or ideas than you think you’ll need, because some will not be a good fit.

Microsoft Copilot responded to the prompt above with the 10 research questions below.

10 Research questions generated by Microsoft Copilot

Who are the primary users of the research repository within different organizations? What motivates users to engage with the research repository? How do different teams (design, product, sales, marketing) access and benefit from the research repository? What challenges do practitioners face when contributing to or retrieving information from the repository? What types of research artifacts (reports, raw data, templates) are most commonly stored in the repository? How do organizations structure their research repositories? What tools and templates are commonly used to facilitate research repository management? How do practitioners ensure the quality and accuracy of information in the repository? What impact does the research repository have on decision-making and project outcomes? What strategies can organizations implement to encourage widespread adoption and active participation in the research repository?

To broaden your pool of research questions, ask for further research questions or provide the same prompt in a new session. Repeat this process as many times as you need to generate a list that feels exhaustive of what you’d like to learn.

Some of the research questions Copilot generated for me were appropriate, and others were not. As a result, I had AI generate more research questions to choose from.

Unfortunately, most AI chatbots don’t offer an easy way to dismiss suggestions or combine specific responses and work from only these (a behavior called apple-picking ).

Pulling in generated research questions into an offline document (like a FigJam or Google Doc) allows you to easily group items, remove duplicates, or reword suggested research questions.

Begin a new chat session with your selected and refined set of research questions, so that the unwanted research questions are removed from the chat history.

Step 3: Request Methods

After sharing the context and your chosen research questions, ask the AI tool to identify suitable research methods.

Example Prompt : What study would you suggest to answer these research questions? Please be specific; cite which research questions would be answered by which research method if you suggest multiple methods.

Generative-AI advice is not always good advice. Often, these tools will suggest various methods and suggest you triangulate data from multiple sources. This approach is not always needed. Also, not all methods will be practical or the best fit for your study. Additionally, AI may suggest interviews and focus groups even for research questions better suited to a behavioral research method .

Ask AI chatbots to tell you which research methods would be suited to which research question and why. We also recommend doing some further reading on your own about any methods that are unfamiliar to you.

In response to the prompt above (and given my chosen research questions), ChatGPT recommended a survey, interviews with select UX practitioners, and case studies. These were all my chosen methods, so AI had done well here!

Step 4: Request Inclusion Criteria

AI can create inclusion criteria — a necessary component of your research plan. Do this step only after generating research questions and methods since these will inform who should participate in the research study.

Inclusion criteria (or recruitment criteria) are specific characteristics of the target population that need to be represented in your sample.

Start with inclusion criteria before asking the AI to help you write a screening questionnaire ; AI can only craft an appropriate screener after it “knows” who you’re looking to recruit.

Example Prompt: So that I recruit the right people for my interviews, help me create some inclusion criteria. What characteristics or behaviors should I recruit for?

Step 5: Request Help with Screeners, Interview Questions, and Tasks

Finally, ask the AI to put together:

• Interview questions or an interview guide (if conducting interviews)
• Tasks for a usability test
• Diary-study prompts (if relevant)
• Recruitment confirmation emails or other communication messages.

Unfortunately, there are a lot of bad examples of the above on the web. Conversational AI has been trained on all this data. Therefore, don’t be surprised if it produces poor study collateral on its first attempt! This is a major risk area for new researchers.

One way to mitigate this danger is to give the AI tool advice when crafting any of these outputs . Think of AI as a new research assistant who can learn extremely quickly.

Common mistakes that AI tools make include:

• Using words that appear in the interface in task instructions (priming)
• Creating task instructions that ask users to imagine they are someone that they are not
• Not including a goal or a call to action in the task instruction
• Not including distractor options in screening questionnaires
• Using overenthusiastic marketing language in recruitment materials

It’s not surprising that AI makes these mistakes since UX practitioners also make them!

To improve outputs, feed the AI essential tips, such as:

• When crafting tasks: Do not use the name of words or link labels in the task instruction. Find a natural-language equivalent to explain what the participant should do . (You can ask AI to “read” a website or an image.)
• When crafting recruitment materials: Use neutral and concise language in the recruitment email. Avoid using overly enthusiastic marketing language.
• When crafting a screener: Include multiple-choice questions and answer options that might disguise what the study is about and who I am looking to recruit.

Additionally, when possible, feed the AI with good examples of screener questionnaires, tasks, or interview questions, so it can follow their format or style.

Even with this advice, AI can still make mistakes. If you’re doubting its answers, check primary sources or speak with an experienced researcher for old-fashioned human guidance.

If you have ChatGPT’s Plus Plan, you can use our GPT for planning your research.

With the proper context, examples, and advice, AI tools, like ChatGPT and Microsoft Copilot, can craft helpful research questions, tasks, interview questions, and other study collateral far more quickly than you could if you started from scratch.

Research leads and ResearchOps personnel can support junior researchers and PWDRs (People Who Do Research) by providing examples and advice that can be fed to AI agents. Experienced researchers can benefit from using AI to speed up their research-planning process and obtain further inspiration.

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