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Exploratory Research – Types, Methods and Examples

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Exploratory Research

Definition:

Exploratory research is a type of research design that is used to investigate a research question when the researcher has limited knowledge or understanding of the topic or phenomenon under study.

The primary objective of exploratory research is to gain insights and gather preliminary information that can help the researcher better define the research problem and develop hypotheses or research questions for further investigation.

Exploratory Research Methods

There are several types of exploratory research, including:

Literature Review

This involves conducting a comprehensive review of existing published research, scholarly articles, and other relevant literature on the research topic or problem. It helps to identify the gaps in the existing knowledge and to develop new research questions or hypotheses.

Pilot Study

A pilot study is a small-scale preliminary study that helps the researcher to test research procedures, instruments, and data collection methods. This type of research can be useful in identifying any potential problems or issues with the research design and refining the research procedures for a larger-scale study.

This involves an in-depth analysis of a particular case or situation to gain insights into the underlying causes, processes, and dynamics of the issue under investigation. It can be used to develop a more comprehensive understanding of a complex problem, and to identify potential research questions or hypotheses.

Focus Groups

Focus groups involve a group discussion that is conducted to gather opinions, attitudes, and perceptions from a small group of individuals about a particular topic. This type of research can be useful in exploring the range of opinions and attitudes towards a topic, identifying common themes or patterns, and generating ideas for further research.

Expert Opinion

This involves consulting with experts or professionals in the field to gain their insights, expertise, and opinions on the research topic. This type of research can be useful in identifying the key issues and concerns related to the topic, and in generating ideas for further research.

Observational Research

Observational research involves gathering data by observing people, events, or phenomena in their natural settings to gain insights into behavior and interactions. This type of research can be useful in identifying patterns of behavior and interactions, and in generating hypotheses or research questions for further investigation.

Open-ended Surveys

Open-ended surveys allow respondents to provide detailed and unrestricted responses to questions, providing valuable insights into their attitudes, opinions, and perceptions. This type of research can be useful in identifying common themes or patterns, and in generating ideas for further research.

Data Analysis Methods

Exploratory Research Data Analysis Methods are as follows:

Content Analysis

This method involves analyzing text or other forms of data to identify common themes, patterns, and trends. It can be useful in identifying patterns in the data and developing hypotheses or research questions. For example, if the researcher is analyzing social media posts related to a particular topic, content analysis can help identify the most frequently used words, hashtags, and topics.

Thematic Analysis

This method involves identifying and analyzing patterns or themes in qualitative data such as interviews or focus groups. The researcher identifies recurring themes or patterns in the data and then categorizes them into different themes. This can be helpful in identifying common patterns or themes in the data and developing hypotheses or research questions. For example, a thematic analysis of interviews with healthcare professionals about patient care may identify themes related to communication, patient satisfaction, and quality of care.

Cluster Analysis

This method involves grouping data points into clusters based on their similarities or differences. It can be useful in identifying patterns in large datasets and grouping similar data points together. For example, if the researcher is analyzing customer data to identify different customer segments, cluster analysis can be used to group similar customers together based on their demographic, purchasing behavior, or preferences.

Network Analysis

This method involves analyzing the relationships and connections between data points. It can be useful in identifying patterns in complex datasets with many interrelated variables. For example, if the researcher is analyzing social network data, network analysis can help identify the most influential users and their connections to other users.

Grounded Theory

This method involves developing a theory or explanation based on the data collected during the exploratory research process. The researcher develops a theory or explanation that is grounded in the data, rather than relying on pre-existing theories or assumptions. This can be helpful in developing new theories or explanations that are supported by the data.

Applications of Exploratory Research

Exploratory research has many practical applications across various fields. Here are a few examples:

• Marketing Research : In marketing research, exploratory research can be used to identify consumer needs, preferences, and behavior. It can also help businesses understand market trends and identify new market opportunities.
• Product Development: In product development, exploratory research can be used to identify customer needs and preferences, as well as potential design flaws or issues. This can help companies improve their product offerings and develop new products that better meet customer needs.
• Social Science Research: In social science research, exploratory research can be used to identify new areas of study, as well as develop new theories and hypotheses. It can also be used to identify potential research methods and approaches.
• Healthcare Research : In healthcare research, exploratory research can be used to identify new treatments, therapies, and interventions. It can also be used to identify potential risk factors or causes of health problems.
• Education Research: In education research, exploratory research can be used to identify new teaching methods and approaches, as well as identify potential areas of study for further research. It can also be used to identify potential barriers to learning or achievement.

Examples of Exploratory Research

Here are some more examples of exploratory research from different fields:

• Social Science : A researcher wants to study the experience of being a refugee, but there is limited existing research on this topic. The researcher conducts exploratory research by conducting in-depth interviews with refugees to better understand their experiences, challenges, and needs.
• Healthcare : A medical researcher wants to identify potential risk factors for a rare disease but there is limited information available. The researcher conducts exploratory research by reviewing medical records and interviewing patients and their families to identify potential risk factors.
• Education : A teacher wants to develop a new teaching method to improve student engagement, but there is limited information on effective teaching methods. The teacher conducts exploratory research by reviewing existing literature and interviewing other teachers to identify potential approaches.
• Technology : A software developer wants to develop a new app, but is unsure about the features that users would find most useful. The developer conducts exploratory research by conducting surveys and focus groups to identify user preferences and needs.
• Environmental Science : An environmental scientist wants to study the impact of a new industrial plant on the surrounding environment, but there is limited existing research. The scientist conducts exploratory research by collecting and analyzing soil and water samples, and conducting interviews with residents to better understand the impact of the plant on the environment and the community.

How to Conduct Exploratory Research

Here are the general steps to conduct exploratory research:

• Define the research problem: Identify the research problem or question that you want to explore. Be clear about the objective and scope of the research.
• Review existing literature: Conduct a review of existing literature and research on the topic to identify what is already known and where gaps in knowledge exist.
• Determine the research design : Decide on the appropriate research design, which will depend on the nature of the research problem and the available resources. Common exploratory research designs include case studies, focus groups, interviews, and surveys.
• Collect data: Collect data using the chosen research design. This may involve conducting interviews, surveys, or observations, or collecting data from existing sources such as archives or databases.
• Analyze data: Analyze the data collected using appropriate qualitative or quantitative techniques. This may include coding and categorizing qualitative data, or running descriptive statistics on quantitative data.
• I nterpret and report findings: Interpret the findings of the analysis and report them in a way that is clear and understandable. The report should summarize the findings, discuss their implications, and make recommendations for further research or action.
• Iterate : If necessary, refine the research question and repeat the process of data collection and analysis to further explore the topic.

When to use Exploratory Research

Exploratory research is appropriate in situations where there is limited existing knowledge or understanding of a topic, and where the goal is to generate insights and ideas that can guide further research. Here are some specific situations where exploratory research may be particularly useful:

• New product development: When developing a new product, exploratory research can be used to identify consumer needs and preferences, as well as potential design flaws or issues.
• Emerging technologies: When exploring emerging technologies, exploratory research can be used to identify potential uses and applications, as well as potential challenges or limitations.
• Developing research hypotheses: When developing research hypotheses, exploratory research can be used to identify potential relationships or patterns that can be further explored through more rigorous research methods.
• Understanding complex phenomena: When trying to understand complex phenomena, such as human behavior or societal trends, exploratory research can be used to identify underlying patterns or factors that may be influencing the phenomenon.
• Developing research methods : When developing new research methods, exploratory research can be used to identify potential issues or limitations with existing methods, and to develop new methods that better capture the phenomena of interest.

Purpose of Exploratory Research

The purpose of exploratory research is to gain insights and understanding of a research problem or question where there is limited existing knowledge or understanding. The objective is to explore and generate ideas that can guide further research, rather than to test specific hypotheses or make definitive conclusions.

Exploratory research can be used to:

• Identify new research questions: Exploratory research can help to identify new research questions and areas of inquiry, by providing initial insights and understanding of a topic.
• Develop hypotheses: Exploratory research can help to develop hypotheses and testable propositions that can be further explored through more rigorous research methods.
• Identify patterns and trends : Exploratory research can help to identify patterns and trends in data, which can be used to guide further research or decision-making.
• Understand complex phenomena: Exploratory research can help to provide a deeper understanding of complex phenomena, such as human behavior or societal trends, by identifying underlying patterns or factors that may be influencing the phenomena.
• Generate ideas: Exploratory research can help to generate new ideas and insights that can be used to guide further research, innovation, or decision-making.

Characteristics of Exploratory Research

The following are the main characteristics of exploratory research:

• Flexible and open-ended : Exploratory research is characterized by its flexible and open-ended nature, which allows researchers to explore a wide range of ideas and perspectives without being constrained by specific research questions or hypotheses.
• Qualitative in nature : Exploratory research typically relies on qualitative methods, such as in-depth interviews, focus groups, or observation, to gather rich and detailed data on the research problem.
• Limited scope: Exploratory research is generally limited in scope, focusing on a specific research problem or question, rather than attempting to provide a comprehensive analysis of a broader phenomenon.
• Preliminary in nature : Exploratory research is preliminary in nature, providing initial insights and understanding of a research problem, rather than testing specific hypotheses or making definitive conclusions.
• I terative process : Exploratory research is often an iterative process, where the research design and methods may be refined and adjusted as new insights and understanding are gained.
• I nductive approach : Exploratory research typically takes an inductive approach to data analysis, seeking to identify patterns and relationships in the data that can guide further research or hypothesis development.

Advantages of Exploratory Research

The following are some advantages of exploratory research:

• Provides initial insights: Exploratory research is useful for providing initial insights and understanding of a research problem or question where there is limited existing knowledge or understanding. It can help to identify patterns, relationships, and potential hypotheses that can guide further research.
• Flexible and adaptable : Exploratory research is flexible and adaptable, allowing researchers to adjust their methods and approach as they gain new insights and understanding of the research problem.
• Qualitative methods : Exploratory research typically relies on qualitative methods, such as in-depth interviews, focus groups, and observation, which can provide rich and detailed data that is useful for gaining insights into complex phenomena.
• Cost-effective : Exploratory research is often less costly than other research methods, such as large-scale surveys or experiments. It is typically conducted on a smaller scale, using fewer resources and participants.
• Useful for hypothesis generation : Exploratory research can be useful for generating hypotheses and testable propositions that can be further explored through more rigorous research methods.
• Provides a foundation for further research: Exploratory research can provide a foundation for further research by identifying potential research questions and areas of inquiry, as well as providing initial insights and understanding of the research problem.

Limitations of Exploratory Research

The following are some limitations of exploratory research:

• Limited generalizability: Exploratory research is typically conducted on a small scale and uses non-random sampling techniques, which limits the generalizability of the findings to a broader population.
• Subjective nature: Exploratory research relies on qualitative methods and is therefore subject to researcher bias and interpretation. The findings may be influenced by the researcher’s own perceptions, beliefs, and assumptions.
• Lack of rigor: Exploratory research is often less rigorous than other research methods, such as experimental research, which can limit the validity and reliability of the findings.
• Limited ability to test hypotheses: Exploratory research is not designed to test specific hypotheses, but rather to generate initial insights and understanding of a research problem. It may not be suitable for testing well-defined research questions or hypotheses.
• Time-consuming : Exploratory research can be time-consuming and resource-intensive, particularly if the researcher needs to gather data from multiple sources or conduct multiple rounds of data collection.
• Difficulty in interpretation: The open-ended nature of exploratory research can make it difficult to interpret the findings, particularly if the researcher is unable to identify clear patterns or relationships in the data.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Exploratory Research: Types & Characteristics

Consider a scenario where a juice bar owner feels that increasing the variety of juices will enable an increase in customers. However, he is not sure and needs more information. The owner intends to conduct exploratory research to find out; hence, he decides to do exploratory research to find out if expanding their juices selection will enable him to get more customers or if there is a better idea.

Another example of exploratory research is a podcast survey template that can be used to collect feedback about the podcast consumption metrics both from existing listeners as well as other podcast listeners that are currently not subscribed to this channel. This helps the author of the podcast create curated content that will gain a larger audience. Let’s explore this topic.

LEARN ABOUT: Research Process Steps

Content Index

Exploratory research: Definition

Primary research methods, secondary research methods, exploratory research: steps to conduct a research, characteristics of exploratory research, advantages of exploratory research, disadvantages of exploratory research, importance of exploratory research.

Exploratory research is defined as a research used to investigate a problem which is not clearly defined. It is conducted to have a better understanding of the existing research problem , but will not provide conclusive results. For such a research, a researcher starts with a general idea and uses this research as a medium to identify issues, that can be the focus for future research. An important aspect here is that the researcher should be willing to change his/her direction subject to the revelation of new data or insight. Such a research is usually carried out when the problem is at a preliminary stage. It is often referred to as grounded theory approach or interpretive research as it used to answer questions like what, why and how.

Types and methodologies of Exploratory research

While it may sound difficult to research something that has very little information about it, there are several methods which can help a researcher figure out the best research design, data collection methods and choice of subjects. There are two ways in which research can be conducted namely primary and secondary.. Under these two types, there are multiple methods which can used by a researcher. The data gathered from these research can be qualitative or quantitative . Some of the most widely used research designs include the following:

LEARN ABOUT: Best Data Collection Tools

Primary research is information gathered directly from the subject.  It can be through a group of people or even an individual. Such a research can be carried out directly by the researcher himself or can employ a third party to conduct it on their behalf. Primary research is specifically carried out to explore a certain problem which requires an in-depth study.

• Surveys/polls : Surveys /polls are used to gather information from a predefined group of respondents. It is one of the most important quantitative method. Various types of surveys  or polls can be used to explore opinions, trends, etc. With the advancement in technology, surveys can now be sent online and can be very easy to access. For instance, use of a survey app through tablets, laptops or even mobile phones. This information is also available to the researcher in real time as well. Nowadays, most organizations offer short length surveys and rewards to respondents, in order to achieve higher response rates.

LEARN ABOUT: Live polls for Classroom Experience

For example: A survey is sent to a given set of audience to understand their opinions about the size of mobile phones when they purchase one. Based on such information organization can dig deeper into the topic and make business related decision.

• Interviews: While you may get a lot of information from public sources, but sometimes an in person interview can give in-depth information on the subject being studied. Such a research is a qualitative research method . An interview with a subject matter expert can give you meaningful insights that a generalized public source won’t be able to provide. Interviews are carried out in person or on telephone which have open-ended questions to get meaningful information about the topic.

For example: An interview with an employee can give you more insights to find out the degree of job satisfaction, or an interview with a subject matter expert of quantum theory can give you in-depth information on that topic.

• Focus groups: Focus group is yet another widely used method in exploratory research. In such a method a group of people is chosen and are allowed to express their insights on the topic that is being studied. Although, it is important to make sure that while choosing the individuals in a focus group they should have a common background and have comparable experiences.

For example: A focus group helps a research identify the opinions of consumers if they were to buy a phone. Such a research can help the researcher understand what the consumer value while buying a phone. It may be screen size, brand value or even the dimensions. Based on which the organization can understand what are consumer buying attitudes, consumer opinions, etc.

• Observations: Observational research can be qualitative observation or quantitative observation . Such a research is done to observe a person and draw the finding from their reaction to certain parameters. In such a research, there is no direct interaction with the subject.

For example: An FMCG company wants to know how it’s consumer react to the new shape of their product. The researcher observes the customers first reaction and collects the data, which is then used to draw inferences from the collective information.

LEARN ABOUT: Causal Research

Secondary research is gathering information from previously published primary research. In such a research you gather information from sources likes case studies, magazines, newspapers, books, etc.

• Online research: In today’s world, this is one of the fastest way to gather information on any topic. A lot of data is readily available on the internet and the researcher can download it whenever he needs it. An important aspect to be noted for such a research is the genuineness and authenticity of the source websites that the researcher is gathering the information from.

For example: A researcher needs to find out what is the percentage of people that prefer a specific brand phone. The researcher just enters the information he needs in a search engine and gets multiple links with related information and statistics.

• Literature research : Literature research is one of the most inexpensive method used for discovering a hypothesis. There is tremendous amount of information available in libraries, online sources, or even commercial databases. Sources can include newspapers, magazines, books from library, documents from government agencies, specific topic related articles, literature, Annual reports, published statistics from research organizations and so on.

However, a few things have to be kept in mind while researching from these sources. Government agencies have authentic information but sometimes may come with a nominal cost. Also, research from educational institutions is generally overlooked, but in fact educational institutions carry out more number of research than any other entities.

Furthermore, commercial sources provide information on major topics like political agendas, demographics, financial information, market trends and information, etc.

For example: A company has low sales. It can be easily explored from available statistics and market literature if the problem is market related or organization related or if the topic being studied is regarding financial situation of the country, then research data can be accessed through government documents or commercial sources.

• Case study research: Case study research can help a researcher with finding more information through carefully analyzing existing cases which have gone through a similar problem. Such exploratory data analysis are very important and critical especially in today’s business world. The researcher just needs to make sure he analyses the case carefully in regards to all the variables present in the previous case against his own case. It is very commonly used by business organizations or social sciences sector or even in the health sector.

LEARN ABOUT: Level of Analysis

For example: A particular orthopedic surgeon has the highest success rate for performing knee surgeries. A lot of other hospitals or doctors have taken up this case to understand and benchmark the method in which this surgeon does the procedure to increase their success rate.

• Identify the problem : A researcher identifies the subject of research and the problem is addressed by carrying out multiple methods to answer the questions.
• Create the hypothesis : When the researcher has found out that there are no prior studies and the problem is not precisely resolved, the researcher will create a hypothesis based on the questions obtained while identifying the problem.
• Further research : Once the data has been obtained, the researcher will continue his study through descriptive investigation. Qualitative methods are used to further study the subject in detail and find out if the information is true or not.

LEARN ABOUT: Descriptive Analysis

• They are not structured studies
• It is usually low cost, interactive and open ended.
• It will enable a researcher answer questions like what is the problem? What is the purpose of the study? And what topics could be studied?
• To carry out exploratory research, generally there is no prior research done or the existing ones do not answer the problem precisely enough.
• It is a time consuming research and it needs patience and has risks associated with it.
• The researcher will have to go through all the information available for the particular study he is doing.
• There are no set of rules to carry out the research per se, as they are flexible, broad and scattered.
• The research needs to have importance or value. If the problem is not important in the industry the research carried out is ineffective.
• The research should also have a few theories which can support its findings as that will make it easier for the researcher to assess it and move ahead in his study
• Such a research usually produces qualitative data , however in certain cases quantitative data can be generalized for a larger sample through use of surveys and experiments.

LEARN ABOUT: Action Research

• The researcher has a lot of flexibility and can adapt to changes as the research progresses.
• It is usually low cost.
• It helps lay the foundation of a research, which can lead to further research.
• It enables the researcher understand at an early stage, if the topic is worth investing the time and resources  and if it is worth pursuing.
• It can assist other researchers to find out possible causes for the problem, which can be further studied in detail to find out, which of them is the most likely cause for the problem.
• Even though it can point you in the right direction towards what is the answer, it is usually inconclusive.
• The main disadvantage of exploratory research is that they provide qualitative data. Interpretation of such information can be judgmental and biased.
• Most of the times, exploratory research involves a smaller sample , hence the results cannot be accurately interpreted for a generalized population.
• Many a times, if the data is being collected through secondary research, then there is a chance of that data being old and is not updated.

LEARN ABOUT: Projective Techniques & Conformity Bias

Exploratory research is carried out when a topic needs to be understood in depth, especially if it hasn’t been done before. The goal of such a research is to explore the problem and around it and not actually derive a conclusion from it. Such kind of research will enable a researcher to  set a strong foundation for exploring his ideas, choosing the right research design and finding variables that actually are important for the in-depth analysis . Most importantly, such a research can help organizations or researchers save up a lot of time and resources, as it will enable the researcher to know if it worth pursuing.

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Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods.

EDA helps determine how best to manipulate data sources to get the answers you need, making it easier for data scientists to discover patterns, spot anomalies, test a hypothesis, or check assumptions.

EDA is primarily used to see what data can reveal beyond the formal modeling or hypothesis testing task and provides a provides a better understanding of data set variables and the relationships between them. It can also help determine if the statistical techniques you are considering for data analysis are appropriate. Originally developed by American mathematician John Tukey in the 1970s, EDA techniques continue to be a widely used method in the data discovery process today.

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The main purpose of EDA is to help look at data before making any assumptions. It can help identify obvious errors, as well as better understand patterns within the data, detect outliers or anomalous events, find interesting relations among the variables.

Data scientists can use exploratory analysis to ensure the results they produce are valid and applicable to any desired business outcomes and goals. EDA also helps stakeholders by confirming they are asking the right questions. EDA can help answer questions about standard deviations, categorical variables, and confidence intervals. Once EDA is complete and insights are drawn, its features can then be used for more sophisticated data analysis or modeling, including machine learning .

Specific statistical functions and techniques you can perform with EDA tools include:

• Clustering and dimension reduction techniques, which help create graphical displays of high-dimensional data containing many variables.
• Univariate visualization of each field in the raw dataset, with summary statistics.
• Bivariate visualizations and summary statistics that allow you to assess the relationship between each variable in the dataset and the target variable you’re looking at.
• Multivariate visualizations, for mapping and understanding interactions between different fields in the data.
• K-means Clustering is a clustering method in unsupervised learning where data points are assigned into K groups, i.e. the number of clusters, based on the distance from each group’s centroid. The data points closest to a particular centroid will be clustered under the same category. K-means Clustering is commonly used in market segmentation, pattern recognition, and image compression.
• Predictive models, such as linear regression, use statistics and data to predict outcomes.

There are four primary types of EDA:

• Univariate non-graphical. This is simplest form of data analysis, where the data being analyzed consists of just one variable. Since it’s a single variable, it doesn’t deal with causes or relationships. The main purpose of univariate analysis is to describe the data and find patterns that exist within it.
• Stem-and-leaf plots, which show all data values and the shape of the distribution.
• Histograms, a bar plot in which each bar represents the frequency (count) or proportion (count/total count) of cases for a range of values.
• Box plots, which graphically depict the five-number summary of minimum, first quartile, median, third quartile, and maximum.
• Multivariate nongraphical: Multivariate data arises from more than one variable. Multivariate non-graphical EDA techniques generally show the relationship between two or more variables of the data through cross-tabulation or statistics.
• Multivariate graphical: Multivariate data uses graphics to display relationships between two or more sets of data. The most used graphic is a grouped bar plot or bar chart with each group representing one level of one of the variables and each bar within a group representing the levels of the other variable.

Other common types of multivariate graphics include:

• Scatter plot, which is used to plot data points on a horizontal and a vertical axis to show how much one variable is affected by another.
• Multivariate chart, which is a graphical representation of the relationships between factors and a response.
• Run chart, which is a line graph of data plotted over time.
• Bubble chart, which is a data visualization that displays multiple circles (bubbles) in a two-dimensional plot.
• Heat map, which is a graphical representation of data where values are depicted by color.

Some of the most common data science tools used to create an EDA include:

• Python: An interpreted, object-oriented programming language with dynamic semantics. Its high-level, built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for rapid application development, as well as for use as a scripting or glue language to connect existing components together. Python and EDA can be used together to identify missing values in a data set, which is important so you can decide how to handle missing values for machine learning.
• R: An open-source programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians in data science in developing statistical observations and data analysis.

For a deep dive into the differences between these approaches, check out " Python vs. R: What's the Difference? "

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Learn the importance and the role of EDA and data visualization techniques to find data quality issues and for data preparation, relevant to building ML pipelines.

Learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.

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Exploratory Research: Definition, Types, Examples

Appinio Research · 12.10.2023 · 28min read

Are you ready to unlock the power of exploration in research? In this guide, we'll navigate the fascinating realm of exploratory research, demystifying its techniques and shedding light on its real-world applications.

Whether you're a seasoned researcher seeking to broaden your methodological toolkit or a novice embarking on your first research endeavor, this guide will equip you with the knowledge and insights to harness the full potential of exploratory research. Join us as we dive deep into the intricacies of understanding, planning, conducting, and reporting exploratory research, with real-life examples illuminating the way.

What is Exploratory Research?

Exploratory Research is an investigative method used in the early stages of a research project to delve into a topic when little to no existing knowledge or information is available. It is a dynamic and flexible approach aimed at gaining insights, uncovering trends, and generating initial hypotheses. The primary purposes of exploratory research are:

• Understanding Complexity: Exploratory research helps researchers understand the intricate and multifaceted nature of a research topic, especially when the subject matter is not well-defined.
• Idea Generation: It serves as a fertile ground for generating new ideas, hypotheses, and research questions that can guide more focused studies in the future.
• Problem Identification: It helps identify research problems or gaps in existing knowledge, allowing researchers to refine their research objectives.
• Decision Support: Exploratory research provides valuable information for making informed decisions about the direction and scope of a research project.

Importance of Exploratory Research

Exploratory research holds immense significance in the world of research and problem-solving for several reasons:

• Risk Reduction: By exploring a topic before committing to a specific research path, exploratory research helps reduce the risk of pursuing unproductive or irrelevant research.
• Informed Research: It lays the groundwork for subsequent phases of research, ensuring that subsequent studies are well-informed and more likely to yield meaningful results.
• Creative Exploration: It encourages creative and open-minded exploration of topics, making it particularly useful when dealing with novel or emerging issues.
• Adaptability: Exploratory research methods are adaptable and can be tailored to the unique characteristics of a research question or problem.

Types of Exploratory Research

Exploratory research encompasses various methodologies, each designed to suit specific research objectives and contexts. Let's explore these types in more detail:

Literature Review

Literature Review involves a systematic examination of existing research, publications, and sources related to a specific topic. It serves as a comprehensive exploration of the current state of knowledge.

• Purpose: To identify existing theories, concepts, and gaps in the literature related to a research topic.
• Methods: Researchers review academic papers, books, articles, and other scholarly sources. They synthesize and analyze the findings and theories presented in these sources.
• Benefits: A literature review provides a solid foundation for understanding the historical context and key debates surrounding a topic. It helps researchers identify areas where further investigation is needed.

Pilot Studies

Pilot Studies are small-scale research projects conducted before a full-scale study. They serve as test runs to assess the feasibility of research methods and data collection tools.

• Purpose: To test research procedures, instruments, and methodologies in a controlled environment.
• Methods: Researchers select a smaller sample and conduct data collection and analysis as if it were a full study.
• Benefits: Pilot studies help identify potential problems, refine research designs, and improve the quality of data collection.

Case Studies

Case Studies involve an in-depth examination of a specific individual, group, organization, or event. They offer a holistic view of a particular phenomenon.

• Purpose: To explore real-life contexts and understand complex, unique situations.
• Methods: Researchers gather data through interviews, observations, and document analysis, providing rich, contextual insights.
• Benefits: Case studies provide a deep understanding of specific instances, allowing researchers to extract valuable lessons or generate hypotheses for broader research.

Focus Groups

Focus Groups bring together a small group of participants to engage in open and structured discussions about a particular topic.

• Purpose: To explore group dynamics, collective opinions, and shared perceptions on a specific subject.
• Methods: Researchers facilitate group discussions with carefully designed questions, encouraging participants to express their thoughts and experiences.
• Benefits: Focus groups reveal diverse perspectives, uncover latent issues, and provide qualitative data for further investigation.

In-depth Interviews

In-depth Interviews involve one-on-one conversations between a researcher and a participant, allowing for detailed exploration of experiences, opinions, and perceptions.

• Purpose: To gain in-depth insights into individual perspectives and experiences.
• Methods: Researchers use open-ended questions to guide interviews, creating a conversational and exploratory atmosphere.
• Benefits: In-depth interviews provide rich, nuanced data and are well-suited for studying sensitive topics or personal experiences.

Observational Research

Observational Research entails the systematic observation and recording of behaviors, events, or phenomena in their natural settings.

• Purpose: To understand behavior or phenomena as they naturally occur in their real-world context.
• Methods: Researchers select settings, define variables, and record data through direct observations.
• Benefits: Observational research captures authentic behavior and context, offering insights that might be missed in controlled environments.

Content Analysis

Content Analysis is a method for analyzing textual, visual, or audio content to uncover patterns, themes, or trends.

• Purpose: To explore and understand the content and communication surrounding a particular topic or media.
• Methods: Researchers define coding categories, code content based on these categories, and analyze the frequency and patterns of codes.
• Benefits: Content analysis provides quantitative and qualitative insights into the content of documents, media, or communication channels.

These various types of exploratory research methods offer researchers a versatile toolkit for diving into the unknown and gaining valuable insights, setting the stage for further investigation and discovery.

How to Plan and Design Exploratory Research?

In the planning and design phase of exploratory research, careful consideration of key elements is crucial to ensure the research objectives are met effectively. Let's delve into these elements:

1. Research Objectives

Before embarking on exploratory research, it's essential to define clear and specific research objectives.

• Purpose: Research objectives should clarify what you aim to achieve through your exploratory study. Are you looking to understand a phenomenon, generate hypotheses, identify research gaps, or explore new concepts?
• Specificity: Objectives should be well-defined, leaving no room for ambiguity. They should guide your research process and serve as a benchmark for success.
• Alignment: Ensure that your research objectives align with the broader goals of your research project and contribute to the generation of valuable insights.

2. Data Collection Methods

Selecting appropriate data collection methods is a critical step in planning exploratory research.

The choice of methods should align with your research objectives.

• Method Suitability: Consider the nature of your research question. Qualitative methods like interviews and focus groups are ideal for exploring subjective experiences, while quantitative methods may be more suitable for gathering numerical data.
• Data Sources: Identify the sources of data you will tap into, whether it's primary data (collected directly) or secondary data (existing sources).
• Data Collection Tools: Determine the specific tools and instruments you will use for data collection. This may include interview guides, questionnaires, or observation protocols.

3. Sampling Techniques

Choosing the proper sampling techniques is crucial to ensure that your exploratory research represents the target population or context effectively.

• Purposeful Sampling: When using qualitative methods like interviews and focus groups, purposeful or selective sampling helps identify participants who can provide valuable insights based on specific criteria, such as expertise or experience.
• Random Sampling: If your exploratory research involves quantitative data collection, consider random sampling methods to ensure that your sample is representative of the larger population.
• Snowball Sampling: In cases where it's challenging to identify participants through traditional methods, snowball sampling allows initial participants to refer others, creating a chain of referrals.

4. Data Analysis Approaches

Determining the data analysis approaches is essential for making sense of the information collected during exploratory research.

• Qualitative Data Analysis: For qualitative data, approaches like thematic analysis , content analysis, or narrative analysis help identify patterns, themes, and trends within the data.
• Quantitative Data Analysis: If you have quantitative data, statistical analysis and data visualization techniques can reveal trends, correlations, and significant findings.
• Mixed-Methods Analysis: In cases where both qualitative and quantitative data are collected, a mixed-methods analysis approach can provide a more comprehensive understanding.

5. Ethical Considerations

Ethical considerations are paramount in exploratory research, as they ensure the well-being and rights of participants are protected.

• Informed Consent: Obtain informed consent from participants, explaining the purpose of the research, their role, and the potential risks and benefits. Consent forms should be clear and voluntary.
• Privacy and Anonymity: Protect the confidentiality and anonymity of participants by avoiding disclosing personal or sensitive information without explicit consent.
• Data Security: Safeguard research data to prevent unauthorized access or breaches of confidentiality.
• Conflict of Interest: Disclose any conflicts of interest or potential biases that may affect the research process or findings.
• Compliance: Adhere to ethical guidelines and regulations established by relevant institutions or governing bodies, such as institutional review boards (IRBs).

With a well-planned approach that includes clearly defined research objectives, appropriate data collection methods, thoughtful sampling techniques, robust data analysis approaches, and ethical considerations, you can set the stage for a successful exploratory research endeavor.

How to Conduct Exploratory Research?

In this section, we will delve into the practical aspects of conducting exploratory research, which involves data collection and analysis. These steps are vital to uncover insights and generate hypotheses. Let's explore each component in detail:

Data Collection

Effective data collection is the cornerstone of exploratory research. Here are various methods you can use to collect data:

1. Literature Review Process

Literature review is the process of systematically searching, reviewing, and summarizing existing academic literature related to your research topic. This step is crucial as it provides a foundation for understanding the current state of knowledge and identifying research gaps:

• Identify Relevant Sources: Begin by searching for relevant academic papers, books, articles, and reports. Online databases like PubMed, Google Scholar, and academic library catalogs are excellent resources.
• Synthesize Information: Summarize the essential findings and ideas from the sources you've collected. Create a literature review matrix or summary to organize your results and identify common themes.
• Identify Research Gaps: As you review the literature, pay attention to areas where there's a lack of research or conflicting findings. These gaps can inform your exploratory research objectives.

2. Conducting Pilot Studies

Pilot studies are small-scale research projects designed to test and refine your research methods and instruments. They provide valuable insights and help identify potential issues before embarking on a full-scale study.

• Define Objectives: Clearly define the objectives of your pilot study. What specific aspects of your research design are you testing? What do you hope to learn from the pilot?
• Select Sample: Choose a small, representative sample for your pilot study. This sample should reflect your target population as closely as possible.
• Collect Data: Implement your research methods on the selected sample. Pay close attention to any challenges or issues that arise during data collection.
• Analyze Results: After collecting data, analyze the results. Look for any anomalies or unexpected findings that may require adjustments to your research design.

3. Running Case Studies

Case studies involve in-depth investigations into specific individuals, groups, organizations, or events. They provide rich, contextual data.

• Select a Case: Choose a relevant case that aligns with your research objectives. Consider cases that offer unique insights or perspectives on your topic.
• Gather Data: Collect data through a combination of interviews, observations, and document analysis. Triangulate your data sources for a comprehensive view.
• Analyze Data: Analyze the collected data to identify patterns, themes, and insights. Use coding or thematic analysis to categorize information.

4. Organizing Focus Groups

Focus groups bring together a small group of participants to engage in open and structured discussions about a particular topic.

• Recruit Participants: Recruit a diverse group of participants who can provide valuable insights into your research questions. Ensure that the group dynamics are conducive to open discussion.
• Design Questions: Prepare a set of open-ended questions that guide the discussion. Encourage participants to share their perspectives and experiences.
• Conduct the Session: Facilitate the focus group session, making sure everyone has an opportunity to speak. Take detailed notes and consider using audio or video recording.
• Analyze Findings: Transcribe and analyze the focus group discussions. Look for common themes, opinions, and areas of agreement or disagreement among participants.

5. Performing In-depth Interviews

In-depth interviews involve one-on-one conversations between a researcher and a participant, allowing for detailed exploration of experiences, opinions, and perceptions.

• Prepare Interview Guide: Develop a structured interview guide with open-ended questions that align with your research objectives. The guide provides a framework for the interview.
• Select Participants: Choose participants who can offer in-depth insights into your research questions. Establish rapport and build trust during the interviews.
• Conduct Interviews: Conduct one-on-one interviews, following the interview guide but allowing for flexibility to explore unexpected topics. Encourage participants to share their thoughts and experiences.
• Transcribe and Analyze: Transcribe the interviews and analyze the responses. Look for common themes, patterns, and noteworthy quotes that support your research objectives.

6. Observational Research Techniques

Observational research involves the systematic observation and recording of behaviors, events, or phenomena in their natural settings.

• Select the Setting: Choose a setting that allows for unobtrusive observation of the behavior or phenomena you're studying. Ensure that your presence does not influence the behavior.
• Define Variables: Clearly define the behaviors or phenomena you're observing. Create an observation checklist or coding scheme to record data systematically.
• Record Data: Systematically record your observations, either in real-time or through video/audio recordings. Be objective and avoid making interpretations during the observation.
• Analyze Data: After data collection, analyze the recorded observations to identify patterns, trends, and any noteworthy behaviors. Consider interrater reliability if multiple observers are involved.

7. Content Analysis Methods

Content analysis is a method for systematically analyzing textual, visual, or audio content to uncover patterns, themes, or trends.

• Define Coding Categories: Determine the coding categories or themes that align with your research objectives. Create a coding scheme that can be applied consistently.
• Code Content: Apply the coding scheme to the content you're analyzing. This may involve categorizing text passages, images, or audio segments based on predefined criteria.
• Record and Analyze Data: Record the coded data systematically and analyze it to identify patterns, trends, or recurring themes. Consider using software tools to assist in content analysis.

Data Analysis

After collecting data through the various methods, it's essential to analyze it effectively to extract meaningful insights:

1. Qualitative Data Analysis

Qualitative data analysis involves the examination of non-numeric data, such as text, interviews, and observations.

• Data Coding: Begin by coding the qualitative data, which involves categorizing information into themes or codes. This step helps organize the data for analysis.
• Thematic Analysis: Conduct thematic analysis to identify recurring themes, patterns, and trends within the data. Look for connections and relationships between themes.
• Constant Comparison: Use constant comparison, where you compare new data with existing codes and themes to refine your understanding of the data.
• Interpretation: Interpret the qualitative data in the context of your research objectives. Explore the implications of your findings and consider how they contribute to your research goals.

2. Quantitative Data Analysis

Quantitative data analysis involves the examination of numerical data gathered through surveys, experiments, or other structured methods.

• Data Cleaning: Begin by cleaning the data and addressing any missing values, outliers, or inconsistencies. Ensure that the data is in a usable format for analysis.
• Descriptive Analysis: Perform descriptive analysis to summarize the main characteristics of the data. This includes calculating measures like mean, median, and standard deviation.
• Inferential Analysis: If applicable, conduct inferential analysis to test hypotheses or determine relationships between variables. Common statistical tests include t-tests, ANOVA, and regression analysis.
• Data Visualization: Create visual representations of your quantitative data using charts, graphs, and tables to illustrate key findings.

3. Identifying Patterns and Themes

Across both qualitative and quantitative data analysis, the process of identifying patterns and themes is essential.

• Pattern Recognition: Look for recurring patterns, trends, or regularities in the data. These patterns may be related to your research objectives or unexpected discoveries.
• Theme Identification: In qualitative data analysis, identify themes or categories that emerge from the data. Themes represent commonalities in participants' responses or behaviors.
• Cross-Referencing Data: Compare findings from different data collection methods (e.g., interviews, surveys) to triangulate your results and gain a more comprehensive understanding.
• Iterative Process: Data analysis is often an iterative process. You may revisit and refine your analysis as you uncover new insights or refine your research questions.

By effectively collecting and analyzing data, you can extract meaningful insights, identify trends, and generate hypotheses that will guide your exploratory research and inform future research endeavors.

How to Report and Present Exploratory Research Findings?

Effectively reporting and presenting exploratory research findings is vital to communicate insights and guide future actions. Let's explore the components of this phase in more detail.

Structure of Research Reports

Creating a well-structured research report ensures that your exploratory findings are communicated clearly and effectively.

• Title Page: Begin with a title page that includes the title of the report, your name, affiliation, and the date of publication.
• Executive Summary: Provide a concise summary of the research objectives, methods, key findings, and recommendations. This section should be informative yet brief.
• Table of Contents: Include a table of contents to help readers navigate through the report easily.
• Introduction: Introduce the research topic, objectives, and the importance of exploratory research in addressing your research questions.
• Methodology: Describe the methods used for data collection, including sampling techniques, data analysis approaches, and ethical considerations.
• Findings: Present your research findings, organized by research method (e.g., literature review, pilot study, focus groups, interviews, etc.).
• Discussion: Interpret your findings, discuss their implications, and relate them to your research objectives. Consider addressing any limitations.
• Recommendations: Offer recommendations based on your exploratory research. What actions or further research should be pursued?
• Conclusion: Summarize the key points of your study, emphasizing its significance.
• Appendices: Include any supplementary materials, such as interview transcripts, survey questionnaires, or additional data.
• References: Cite all the sources you referenced in your report using a consistent citation style (e.g., APA, MLA).

Visualizing Data

Effective data visualization enhances the understanding of your exploratory findings.

• Tables: Organize data in tabular format for easy comparison.
• Charts and Graphs: Use bar charts, line graphs, pie charts, or scatter plots to represent quantitative data.
• Infographics: Create visual summaries of key findings using infographics.
• Images and Visuals: Include relevant images, photographs, or screenshots to illustrate points.

Interpreting Results

Interpreting your exploratory research results involves:

• Contextualizing Findings: Explain the significance of your findings within the broader context of your research objectives.
• Discussing Implications: Consider the practical implications of your findings. How do they impact the research area or field?
• Addressing Limitations: Acknowledge any limitations or constraints in your study, such as sample size or data collection challenges.
• Comparing with Hypotheses: If applicable, compare your findings with any initial hypotheses you may have developed during the exploratory phase.
• Suggesting Future Research: Identify areas where further research is needed, building upon the insights gained in your exploratory study.

Making Recommendations

Based on your exploratory research, provide actionable recommendations.

• Practical Steps: Offer specific actions or decisions that can be made based on your findings.
• Policy Recommendations: If relevant, suggest changes or improvements to policies or practices.
• Further Research: Highlight areas where more in-depth research is required to build upon your exploratory findings.
• Implementation Plan: Outline a plan for implementing the recommendations, if applicable.

Remember that the clarity of your report and the persuasiveness of your recommendations are crucial in making your exploratory research valuable to your audience. Effective communication ensures that your insights lead to informed decisions and further exploration in your field of study.

Exploratory Research Advantages and Limitations

Exploratory research offers valuable insights into various aspects of a research topic, but it also comes with its own set of advantages and limitations. Understanding these factors is essential for making informed decisions about using exploratory research in your projects. Let's explore both sides of the coin.

Exploratory Research Advantages

• Insight Generation: Exploratory research excels at discovering the unknown. It allows you to explore and uncover new phenomena, trends, or perspectives that may have been previously unknown or overlooked.
• Hypothesis Generation: By investigating a topic with an open mind, you can generate hypotheses and research questions that can guide more focused research in the future. These initial hypotheses can serve as a valuable starting point.
• Flexibility: Exploratory research is well-suited for complex and multifaceted topics where a structured approach may not be appropriate. It provides the flexibility to adapt to evolving research objectives.
• Qualitative Understanding: Methods like interviews, focus groups, and content analysis provide rich qualitative data. This qualitative understanding is crucial for exploring nuances and complexities in human experiences and behaviors.
• Contextual Understanding: Exploratory research often takes place in real-world contexts. Case studies and observational research, for example, allow you to understand how phenomena operate in their natural environments, providing valuable context.
• Pilot Testing: Exploratory research, including pilot studies, helps in refining research methodologies and instruments. By uncovering potential issues early on, it reduces errors in subsequent studies.

Exploratory Research Limitations

• Lack of Generalizability: Exploratory research often uses small, non-representative samples. This makes it challenging to generalize findings to larger populations or broader contexts. The insights gained may be specific to the participants or conditions involved.
• Subjectivity: The qualitative nature of many exploratory research methods can introduce subjectivity in data analysis and interpretation. Researchers' biases and perspectives may influence the findings.
• Time and Resource Intensive: Some exploratory research methods, such as in-depth interviews or case studies, can be time-consuming and resource-intensive. This can limit the scalability of exploratory studies.
• Limited Quantitative Data: If your research requires precise numerical data, exploratory research may not be sufficient. It primarily focuses on qualitative insights and quantitative data may be limited in scope.
• Potential for Bias: The choice of research methods and participants can introduce bias into your findings. For example, purposive sampling in qualitative research may inadvertently select participants with similar perspectives.
• Incomplete Picture: Exploratory research may provide an insufficient or preliminary picture of a topic. It often requires further investigation for validation and a more comprehensive understanding.
• Ethical Challenges: The open-ended nature of exploratory research can raise ethical challenges, especially in sensitive research areas. Ensuring participant consent and privacy is essential.

Understanding these advantages and limitations is crucial for researchers to make informed decisions about when and how to apply exploratory research methods. It's essential to carefully consider these factors in the context of your research objectives and the specific challenges and opportunities presented by your research topic.

Exploratory Research Examples

Exploratory research is a versatile approach employed across various fields to gain insights, uncover trends, and generate hypotheses. Let's explore real-world examples of how different exploratory research methods have been applied effectively:

1. Real-Life Case Studies

Facebook's emotional contagion study.

Background: In 2014, Facebook conducted a controversial exploratory research study to investigate emotional contagion. The study involved manipulating the content that appeared in users' newsfeeds to measure how emotional content impacted their own posts.

Method: Facebook used large-scale data analysis to conduct this study, which involved over 689,000 users. They manipulated the visibility of positive and negative posts to examine whether emotional states could be influenced online.

Findings: The study found that when users saw fewer positive posts in their newsfeeds, they tended to post fewer positive updates themselves, and vice versa for negative posts. This research sparked discussions about ethical considerations in online experimentation and the power of social media platforms to influence emotions.

Harvard Business School's Airbnb Case Study

Background: Harvard Business School conducted an exploratory case study on Airbnb, a disruptive platform in the hospitality industry. The goal was to understand how Airbnb disrupted traditional lodging markets and its impact on the hotel industry.

Method: Researchers collected data from various sources, including interviews with Airbnb hosts, surveys of travelers, and publicly available data on Airbnb listings and hotel occupancy rates. They analyzed the data to identify trends and insights.

Findings: The study found that Airbnb significantly impacted the hotel industry by offering unique, affordable, and personalized lodging options. It also highlighted challenges such as regulatory issues and concerns about safety and quality control.

2. Focus Groups

Apple's product development.

Background: Apple Inc. frequently conducts exploratory research through focus groups to gather insights and opinions from potential users before launching new products or features.

Method: Apple assembles small groups of potential users and conducts moderated discussions. Participants are encouraged to share their thoughts, preferences, and concerns about prototypes or concepts.

Findings: Apple gains valuable feedback about user preferences and pain points by engaging with focus groups. For example, before launching the Apple Watch, focus groups provided insights into desired features like health tracking and customization.

Political Campaign Strategy

Background: In politics, campaign teams often use focus groups to explore voters' opinions, reactions to candidates, and key campaign issues.

Method: Focus groups consist of a diverse set of voters who engage in discussions about campaign messages, policies, and candidate attributes. Campaign teams use these insights to tailor their strategies.

Findings: Focus groups help political campaigns understand which messages resonate with different voter demographics. For instance, a focus group may reveal that a candidate's stance on a specific policy particularly appeals to a specific age group, influencing campaign messaging.

3. Content Analysis

Climate change discourse in media.

Background: Exploratory content analysis has been employed to study media coverage of climate change. Researchers aim to understand how different media outlets frame climate change issues.

Method: Researchers collect articles and news reports from various sources and then analyze the content to identify recurring themes, framing, and the use of language. This helps determine how climate change is portrayed in the media.

Findings: Content analysis has revealed that media outlets may use different frames when discussing climate change, such as "economic impact," "environmental consequences," or "scientific consensus." These frames can influence public perception and policy discussions.

Social Media Sentiment Analysis

Background: Companies and organizations use content analysis of social media posts to gauge public sentiment and gather insights into customer opinions and preferences.

Method: Automated tools are used to collect and analyze social media posts, comments, and mentions related to a specific brand, product, or topic. Natural language processing techniques identify sentiment (positive, negative, neutral) and key themes.

Findings: By analyzing social media content, companies can identify customer complaints, emerging trends, or public sentiment shifts in real time. For example, a restaurant chain may use sentiment analysis to track customer reactions to new menu items.

4. Observational Research

Supermarket shopping behavior.

Background: Observational research is frequently used in the retail industry to understand consumer behavior. One example is studying how shoppers navigate supermarkets.

Method: Researchers observe shoppers in a supermarket, noting their paths through the store, product choices, and interactions with displays. This data helps retailers optimize store layouts and product placement.

Findings: Observational research has shown that shoppers tend to follow predictable patterns in supermarkets, such as starting with fresh produce. Retailers use this data to design store layouts that encourage specific shopping behaviors and maximize sales.

Child Development Studies

Background: Observational research is crucial in child development studies to understand how children learn and develop through their interactions with the environment.

Method: Researchers use video recordings or live observations to document children's behaviors in various settings, such as classrooms or homes. They analyze these observations to identify developmental milestones and learning patterns.

Findings: Observational research in child development has contributed to our understanding of how children acquire language, social skills, and cognitive abilities. For example, it has revealed how peer interactions influence language development in preschoolers.

These real-world examples illustrate the diverse applications of exploratory research methods, from understanding user preferences for tech giants like Apple to analyzing media discourse on critical issues like climate change. Exploratory research empowers organizations and researchers with valuable insights that inform decision-making and shape future research directions.

Exploratory research is a dynamic tool that opens doors to discovery. It helps us uncover hidden insights, generate fresh ideas, and better understand the world around us. By delving into the unknown and embracing its flexibility, we can embark on journeys of exploration that enrich our knowledge and inform future endeavors.

So, whether you're exploring uncharted territories in academia, industry, or any field, remember that the spirit of curiosity and the methods of exploratory research can be your compass. With the right strategies and ethical considerations, you'll not only navigate the challenges but also uncover the treasures of knowledge that await. As you embark on your own exploratory research adventures, may you find answers to your questions, ignite new inquiries, and, above all, revel in the joy of discovery.

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Exploratory Research

Exploratory research, as the name implies, intends merely to explore the research questions and does not intend to offer final and conclusive solutions to existing problems. This type of research is usually conducted to study a problem that has not been clearly defined yet. Conducted in order to determine the nature of the problem, exploratory research is not intended to provide conclusive evidence, but helps us to have a better understanding of the problem.

When conducting exploratory research, the researcher ought to be willing to change his/her direction as a result of revelation of new data and new insights. [1] Accordingly, exploratory studies are often conducted using interpretive research methods and they answer to questions such as what, why and how.

Exploratory research design does not aim to provide the final and conclusive answers to the research questions, but merely explores the research topic with varying levels of depth. It has been noted that “exploratory research is the initial research, which forms the basis of more conclusive research. It can even help in determining the research design, sampling methodology and data collection method” [2] . Exploratory research “tends to tackle new problems on which little or no previous research has been done” [3] .

Unstructured interviews are the most popular primary data collection method with exploratory studies. Additionally, surveys , focus groups and observation methods can be used to collect primary data for this type of studies.

Examples of Exploratory Research Design

The following are some examples for studies with exploratory research design in business studies:

• A study into the role of social networking sites as an effective marketing communication channel
• An investigation into the ways of improvement of quality of customer services within hospitality sector in London
• An assessment of the role of corporate social responsibility on consumer behaviour in pharmaceutical industry in the USA

Differences between Exploratory and Conclusive Research

The difference between exploratory and conclusive research is drawn by Sandhursen (2000) [4] in a way that exploratory studies result in a range of causes and alternative options for a solution of a specific problem, whereas, conclusive studies identify the final information that is the only solution to an existing research problem.

In other words, exploratory research design simply explores the research questions, leaving room for further researches, whereas conclusive research design is aimed to provide final findings for the research.

Moreover, it has been stated that “an exploratory study may not have as rigorous as methodology as it is used in conclusive studies, and sample sizes may be smaller. But it helps to do the exploratory study as methodically as possible, if it is going to be used for major decisions about the way we are going to conduct our next study” [5] (Nargundkar, 2003, p.41).

Exploratory studies usually create scope for future research and the future research may have a conclusive design. For example, ‘a study into the implications of COVID-19 pandemic into the global economy’ is an exploratory research. COVID-19 pandemic is a recent phenomenon and the study can generate an initial knowledge about economic implications of the phenomenon.

A follow-up study, building on the findings of this research ‘a study into the effects of COVID-19 pandemic on tourism revenues in Morocco’ is a causal conclusive research. The second research can produce research findings that can be of a practical use for decision making.

Advantages of Exploratory Research

• Lower costs of conducting the study
• Flexibility and adaptability to change
• Exploratory research is effective in laying the groundwork that will lead to future studies.
• Exploratory studies can potentially save time by determining at the earlier stages the types of research that are worth pursuing

Disadvantages of Exploratory Research

• Inclusive nature of research findings
• Exploratory studies generate qualitative information and interpretation of such type of information is subject to bias
• These types of studies usually make use of a modest number of samples that may not adequately represent the target population. Accordingly, findings of exploratory research cannot be generalized to a wider population.
• Findings of such type of studies are not usually useful in decision making in a practical level.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research designs. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited

[2] Singh, K. (2007) “Quantitative Social Research Methods” SAGE Publications, p.64

[3] Brown, R.B. (2006) “Doing Your Dissertation in Business and Management: The Reality of Research and Writing” Sage Publications, p.43

[4] Sandhusen, R.L. (2000) “Marketing” Barrons

[5] Nargundkar, R. (2008) “Marketing Research: Text and Cases” 3 rd edition, p.38

Exploratory Research: Definition, Types, Examples

What is Exploratory Research or Exploratory Studies?

Exploratory research (exploratory study) is a small-scale study of relatively short duration, undertaken when little is known about a situation or problem. An exploratory study helps a researcher to

• Diagnose a problem;
• Search for alternatives;
• Discover new ideas;
• Develop and sharpen his concepts more clearly;
• Establish priority among several alternatives;
• Identify variables of interest;
• Set research questions and objectives;
• Formulate hypotheses;
• Develop an operational definition of variables;
• Improve his final research design.

The exploratory study helps to save time and money. If the problem appears not as important at first sight, a research project may be abandoned at the initial stage.

Exploratory study progressively narrows down the scope of the research topic and transforms the undefined problems into defined ones, incorporating specific research objectives.

An exploratory study comes to an end when the researcher is fully convinced that he has established the major dimension of the research, and no additional research is needed to conduct the larger study.

Examples of Exploratory Research

Tribal people in Bangladesh have some peculiar and uncommon background characteristics that distinguish them from the rest of the population.

Sporadic information suggests that they have a large family size, low age at marriage, and high mortality.

Because of the fact that researchers in the past did not have easy access to this population, the above conjectures could not be examined scientifically.

A small-scale study was planned to examine these in the face of these peculiarities to launch a large-scale survey.

The planned study is explorative, which will help the researchers to formulate objectives and hypotheses, keeping in view the above peculiarities regarding their distinct demographic characteristics.

The government-supplied oral contraceptive pills (OCP) and condoms are provided free of charge through government field workers and clinics.

Even then, why a significant proportion of women in the lowest quintile prefer to purchase contraceptives produced by Social Marketing Company (SMC) rather than availing of free services is very critical and valuable information for SMC. To explore this, the SMC wants to conduct a study.

They intend to prepare a profile of the SMC brand contraceptive users of the poorest and poor quintile to gather their perception of SMC product and their views on the govt, supplied contraceptives.

We cite one more example from business research (Saleh, 1995)

Nowadays, entrepreneurship has become a focal point in the business community in both government and non-government agencies and in business education in Bangladesh.

This has led to a greatly accelerated effort among researchers to undertake studies on entrepreneurship and small business growth and development.

Although there has been quite a good number of studies focusing on entrepreneurs’ characteristics, there is still a great deal of mystery about women in business, and queries remain about their entrepreneurial characteristics, motivation, and business success.

An exploratory study, therefore, is planned to be conducted with the sole objective of identifying the motivation of women entrepreneurs for business and assessing their entrepreneurial skills.

Types of Exploratory Research Methods

Secondary data analysis, experience survey, pilot study, focus group discussion.

The exploratory study offers an opportunity to obtain insights into the problem in major ways:

• Analyzing any existing documents or studies. This is secondary data analysis;
• Sharing experiences with knowledgeable individuals. This is an experience survey;
• Investigating the situations informally. This falls under a pilot study;
• Conducting a case study. The case may be an individual or a group of individuals;
• Designing a focus group.

Electronic data processing dates back to about 50 years, and the large-scale collection and analysis of social science data are not much older.

The most emerging barrier now is the cost of data collection for any scientific study. In recent years, the data processing cost has considerably decreased owing to the availability of increased facilities. This is seriously limiting the research endeavor of the students and professionals.

More and more researchers, however, are overcoming this cost obstacle by engaging in secondary analysis-building research projects around re-analyzing data originally collected by someone else for another purpose.

Secondary data, sometimes also called historical data, are data previously collected and assembled for some project other than one at hand. Studies based on secondary data do not need access to respondents or subjects.

The process thus enables you to avoid the cost of data collection by producing a new set of findings out of old data.

In recent years, survey data are increasingly likely candidates for secondary analysis because of the volume of such data and because of their availability in an inexpensive and well-organized form.

Scientists of various disciplines and students are taking advantage of this abundant database for their research.

The chief advantage of secondary data analysis is that data for such studies are almost always less expensive to collect than acquiring primary data.

Also, secondary analysis can be completed relatively more quickly since it involves less time in the collection procedure. These data are very often available on soft copies.

Studies based on secondary data can help you to explore and decide what further research needs to be done. It further contributes to enriching your research proposal with specific references and citations.

Analysis of available records may often be the only way to obtain quantitative data about the past.

As more and more survey data accumulate, trend studies comparing responses to similar survey questions asked over many years become more practical and valuable for testing or developing theory.

Secondary analysis can often be the basis for an important pilot study.

Before embarking on an extensive and costly study, researchers may use secondary analysis of past research to assess the soundness of their research design, pretest the plausibility of their hypotheses, and determine the strengths and weaknesses of formerly used indicators and question wordings.

More importantly, a secondary study may be used as the sole basis for a research study since in many research situations, one cannot conduct primary research because of physical, legal, or cost constraints.

The most important limitation of secondary analysis is that the information may not meet your specific needs. The most common problems are;

• The data may be outdated;
• There may be variations in the operational definition of terms;
• The units of measurement may be different;
• The research design and sampling design may not be known or may be inappropriate;
• There may be no codebook available for re-analyzing the data.

Although the objectives of an exploratory study may be accomplished with both qualitative and quantitative techniques, yet it relies more heavily on qualitative techniques.

When studies based on secondary data become difficult, researchers may well profit by seeking information from persons experienced in the area of study, tapping into their collective memories and experiences.

A survey involving such persons is referred to as an experience survey.

In essence, they are the key informants (KI) with abundant experience in their area, and the interview with them is known as the key informant interview (K1I).

The purpose of surveying such experts and seeking their opinions is to help sharpen the research problems and clarifying concepts rather than develop conclusive evidence. The outcome of an experience survey may result in a new hypothesis, discarding the old one, or may give information about the practicality of doing the study.

Sharing experiences with the experts may indicate whether certain facilities are available or not, what factors need to be controlled, and who is supposed to cooperate in the study.

An experienced survey is usually informal and involves a small number of people who have been carefully selected. The investigating format to be used in the survey should be flexible enough so that we can explore various avenues that emerge during the interview.

A case study is an exploratory social research methodology aimed at intensively investigating one or a few situations identical to the researcher’s problem situations.

Rather than using random samples and following a rigid protocol (strict set of rules) to examine a limited number of variables, case study methods involve an in-depth, longitudinal examination of a single instance or event: a case.

They provide a systematic way of looking at events, collecting data, analyzing data, and reporting the results.

As a result, the researcher may gain a sharpened understanding of why the instance happened as it did, and what might become important to look at more extensively in future research.

Case studies lend themselves to both generating and testing hypotheses.

When selecting a case for the case study, researchers often use information-oriented sampling instead of random sampling. This is because the average case is often not the richest in the information.

Extreme or atypical cases reveal more information because they activate more basic mechanisms and more actors in the situation studied.

Since a case study places emphasis on detail, it provides valuable insight for problem-solving, evaluation, and strategy. In the case of studies, researchers are not trying to establish a representative probability sample, and no attempt is made to meet the minimum design requirements.

Despite these limitations, case studies have a significant scientific role.

A single, well-designed case study can provide a major challenge to theory and provide a source of new hypotheses and direction of research.

When discussed in the context of an exploratory study, a pilot study refers to a small-scale research study that uses sampling but does not apply the rigorous standard. A pilot study generates primary data, usually for qualitative analysis.

This feature distinguishes a pilot study from secondary data analysis, which gathers background information. A pilot study is a tentative study using relatively unstructured interviews of a handful of respondents or subjects who are similar to those who will be the target of the later survey.

A pilot study is often compared to a theatrical dress rehearsal before a final theatre is staged. These studies are intended to allow the researchers to try out various possibilities before deciding which ones to adopt.

A pilot study nearly always results in a considerable improvement to the survey documents leading to a general increase in the efficiency of the research design.

Such studies can often stimulate new lines of inquiry, prompted by the researchers or unsolicited responses of the respondents or subjects.

They can also suggest new types of data that should be collected, point out and resolve ambiguities in the way that questions are being asked indicate modifications needed in the order of topic covered and help to eliminate fruitless lines of inquiry.

A well- planned pilot study offers an opportunity to the researchers based on its results, as to whether the main study is still worth to carry out or not. Any investigator, who contemplates an exclusive survey, should conduct the pilot study as an opportunity to discover and correct mistakes before they become serious and incurable.

A focus group discussion (FGD) is a way of reducing the amount of time and personnel required for conducting and analyzing in-depth study and yet getting detailed qualitative information by interviewing a panel of a relatively large number of respondents.

The focus group interview has become so popular that many researchers now consider it to be the only exploratory research tool.

Typically, the panel is made up of 6 to 10 respondents.

The panel is led by a trained moderator or facilitator who meets for 90 minutes to 2 hours at a designated time. The moderator uses group dynamics principles to focus or guide the group in an exchange of ideas, feelings, and experiences on a single topic.

The moderator introduces the topic using a general discussion guide and encourages the group members to discuss the subjects.

In ideal situations, the group discussion will proceed uninterrupted.

Depending on the subject matter of discussion, forming separate groups for different population subsets is often rewarding. This type of homogeneous grouping tends to promote more intense and freer discussions.

It may also be conducted by telephone as an alternative to the face-to-face focus group discussion. This is particularly effective when;

• It is difficult to reach the target group, particularly when the group members represent experts, professionals, high-level executives, etc.
• When the target group members are rarely found, and
• When the group members are so sensitive that anonymity is warranted.

The primary advantage of the focus group interview as an exploratory research tool is its relative flexibility and its ability to quickly and inexpensively understand the core issue of the topic, especially when compared with the rigidity of a formal study.

However, because they are qualitative devices with limitations of sampling accuracy, results from focus group discussions should not be considered a replacement for quantitative analyses.

Exploratory research is conducted when little is known about a situation or problem. Its main purpose is to diagnose problems, search for alternatives, discover new ideas, sharpen concepts, and improve the final research design.

How does exploratory research assist in the research process?

Exploratory research helps in narrowing down the scope of the research topic, transforming undefined problems into defined ones, and determining the major dimensions of the research. It can lead to the decision of whether to proceed with a larger study or abandon a research project at an early stage.

What are the main methods utilized in exploratory research?

The primary methods in exploratory research include secondary data analysis, experience surveys, pilot studies, case studies, and focus group discussions.

What is the role of a case study in exploratory research?

A case study offers an in-depth, longitudinal examination of a specific instance or event. It provides a systematic way to observe events, gather and analyze data, and report results, leading to insights for problem-solving, evaluation, and strategy formulation .

How does a focus group discussion function in exploratory research?

A focus group discussion involves interviewing a panel of 6 to 10 respondents to gain detailed qualitative insights. Led by a trained moderator, the group discusses a single topic, sharing ideas, feelings, and experiences. It’s a flexible method that quickly provides core insights into a topic.

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Exploratory Research – Guide, Definition & Examples

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Exploratory research deals with undiscovered or unfamiliar issues, frequently making up the foundation for further structured research. Within research methodology , it can be identified by its open-ended and flexible approach with the goal to explore new horizons, create ideas, or bringing clarity to debatable topics. Exploratory research does not test hypotheses but rather asks questions and collects first data, where further valuable and more in-depth investigations can be conducted.

Inhaltsverzeichnis

• 1 Exploratory Research – In a Nutshell
• 2 Definition: Exploratory research
• 3 The usage of exploratory research
• 4 Exploratory research questions
• 5 Exploratory research data collection
• 6 The five steps of exploratory research with examples
• 7 Exploratory vs. explanatory research
• 8 Advantages vs. disadvantages

Exploratory Research – In a Nutshell

• Exploratory research investigates issues that don’t have thorough studies yet.
• It provides an onset of an existing problem to explore further.
• It is usually structured as qualitative research and refers to a primary source.

Definition: Exploratory research

Exploratory research is a study methodology that explores an issue that has not been extensively studied in the past or a new topic or subject. It explores specific elements of an existing phenomenon and gets more insight into it.

Your university library is considering adding an alternative medicine section to it. However, the institution is hesitant because of concerns that the decision may cause backlash from students, which may lead to unrest in the school. Therefore, the plan will only proceed if there is concrete proof that the reception from the students will be positive.

The usage of exploratory research

This method is often applied when the study issue is novel or when the data collection process for the study issue is challenging. You can also use this method if you have a general notion about a subject or a specific question that you would like to explore, but there is no existing knowledge with which to explore it.

Exploratory research questions

Academic studies usually begin with research questions. These questions are usually constructed to assist you to understand more about a particular subject. Therefore, they help you put together notions to master the footing of your investigation without adding any predetermined philosophies or assumptions.

• What elements influence drug use in university students?
• What effect does using digital learning tools have on the attention span of undergraduates?
• What outcomes are connected with the gentle parenting style?

Exploratory research data collection

Data collection in this form of research is challenging because it involves working with a previously unexplored subject. However, exploratory research allows you to narrow down your subject of interest and come up with a distinct premise and problem statement.

You can use primary and secondary research questions to gather data. Primary research collects data directly from primary sources. Some examples of these sources are:

• Focus groups

On the other hand, secondary research collects data from existing materials. Examples of secondary research data collection techniques are:

• Case studies
• Literature review
• Online polls

The five steps of exploratory research with examples

The way you conduct this research usually depends on your chosen data collection method. However, this research features five standard steps.

You teach English to non-native speakers. Your current oral proficiency technique focuses on reducing your student’s foreign accent. However, you suspect that a foreign accent does not affect intelligibility. So, you want to shift your attention to increasing intelligibility. Nevertheless, there is no pre-existing research on the link between accent and intelligibility. Therefore, you decide to develop an exploratory research design to explore this issue.

Step 1 of exploratory research: Problem identification

The first step is narrowing down the problem and determining if using an exploratory study is an ideal course of action.

You notice that there is no difference in intelligibility between individuals that speak English with a foreign accent and those with a native accent. Also, you realize that trying to eliminate a student’s accent is not suitable because it is part of their identity. Unfortunately, all current teaching approaches focus on accent reduction.

Step 2 of exploratory research: Hypothesize a solution

The next step is establishing a solution to the challenge you are investigating. This involves articulating a hypothetical statement that will guide your study.

You anticipate that foreign English students would benefit from focusing on promoting intelligibility instead of reducing their accent. You think that it would be wiser to have an oral proficiency technique that echoes this.

Step 3 of exploratory research: Methodology design

This is where you conceptualize your data collection and analysis techniques and use them to develop a research design.

You choose to conduct formal interviews with other English teachers. You design interview questions that focus on issues to do with training oral proficiency. You ensure that the questions focus on the link between accent and intelligibility.

Step 4 of exploratory research: Data collection and analysis

Now you collect and analyze your data from the third step. Next, you can decide if your pilot results support your hypothesis. This research technique allows you to change your hypothesis depending on your findings.

Because of the interview analysis, you conclude that other teachers have similar thoughts as your hypothesis.

Step 5 of exploratory research: Avenues for future research

At this stage, you can determine if you would like to pursue the topic further. If you choose to do so, you will need to switch to another research design, like quantitative research with a larger sample size. Note that exploratory research does not usually give conclusive or generalizable results.

Your pilot outcomes prove your expectations to be right. However, you decide to pursue the study further with a more extensive study. So, you choose an experiment where subjects listen to audio samples of non-English speakers with foreign accents in different degrees. Ask the subjects to note mistakes in the transcript and use the data to determine if your hypothesis is correct.

Exploratory vs. explanatory research

Exploratory research explores research questions that have not been studied extensively in the past. The preliminary outcomes form the foundation for future explorations of the subject. In contrast, explanatory research questions focus on the ‘whys’ and ‘hows’.

Advantages vs. disadvantages

Here are the pros and cons of exploratory research:

What is the main purpose of explanatory research?

This form of research seeks to explore a topic that has not been previously studied in-depth. Its results form the foundation for further studies.

What is the value of exploratory research?

It is easy to conduct and gives more insight into an unexplored issue. It guides further studies on the subject.

What is exploratory research?

Exploratory research is a study methodology that explores an issue that has not been extensively studied in the past or a new topic or subject.

How is exploratory research conducted?

It features five steps: problem identification, hypothesizing, research design, data collection and analysis, and further research.

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• Exploratory Research | Definition, Guide, & Examples

Exploratory Research | Definition, Guide, & Examples

Published on 6 May 2022 by Tegan George . Revised on 20 January 2023.

Exploratory research is a methodology approach that investigates topics and research questions that have not previously been studied in depth.

Exploratory research is often qualitative in nature. However, a study with a large sample conducted in an exploratory manner can be quantitative as well. It is also often referred to as interpretive research or a grounded theory approach due to its flexible and open-ended nature.

Table of contents

When to use exploratory research, exploratory research questions, exploratory research data collection, step-by-step example of exploratory research, exploratory vs explanatory research, advantages and disadvantages of exploratory research, frequently asked questions about exploratory research.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use this type of research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

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Exploratory research questions are designed to help you understand more about a particular topic of interest. They can help you connect ideas to understand the groundwork of your analysis without adding any preconceived notions or assumptions yet.

Here are some examples:

• What effect does using a digital notebook have on the attention span of primary schoolers?
• What factors influence mental health in undergraduates?
• What outcomes are associated with an authoritative parenting style?
• In what ways does the presence of a non-native accent affect intelligibility?
• How can the use of a grocery delivery service reduce food waste in single-person households?

Collecting information on a previously unexplored topic can be challenging. Exploratory research can help you narrow down your topic and formulate a clear hypothesis , as well as giving you the ‘lay of the land’ on your topic.

Data collection using exploratory research is often divided into primary and secondary research methods, with data analysis following the same model.

Primary research

In primary research, your data is collected directly from primary sources : your participants. There is a variety of ways to collect primary data.

Some examples include:

• Survey methodology: Sending a survey out to the student body asking them if they would eat vegan meals
• Focus groups: Compiling groups of 8–10 students and discussing what they think of vegan options for dining hall food
• Interviews: Interviewing students entering and exiting the dining hall, asking if they would eat vegan meals

Secondary research

In secondary research, your data is collected from preexisting primary research, such as experiments or surveys.

Some other examples include:

• Case studies : Health of an all-vegan diet
• Literature reviews : Preexisting research about students’ eating habits and how they have changed over time
• Online polls, surveys, blog posts, or interviews; social media: Have other universities done something similar?

For some subjects, it’s possible to use large- n government data, such as the decennial census or yearly American Community Survey (ACS) open-source data.

How you proceed with your exploratory research design depends on the research method you choose to collect your data. In most cases, you will follow five steps.

We’ll walk you through the steps using the following example.

Therefore, you would like to focus on improving intelligibility instead of reducing the learner’s accent.

Step 1: Identify your problem

The first step in conducting exploratory research is identifying what the problem is and whether this type of research is the right avenue for you to pursue. Remember that exploratory research is most advantageous when you are investigating a previously unexplored problem.

Step 2: Hypothesise a solution

The next step is to come up with a solution to the problem you’re investigating. Formulate a hypothetical statement to guide your research.

Step 3. Design your methodology

Next, conceptualise your data collection and data analysis methods and write them up in a research design.

Step 4: Collect and analyse data

Next, you proceed with collecting and analysing your data so you can determine whether your preliminary results are in line with your hypothesis.

In most types of research, you should formulate your hypotheses a priori and refrain from changing them due to the increased risk of Type I errors and data integrity issues. However, in exploratory research, you are allowed to change your hypothesis based on your findings, since you are exploring a previously unexplained phenomenon that could have many explanations.

Step 5: Avenues for future research

Decide if you would like to continue studying your topic. If so, it is likely that you will need to change to another type of research. As exploratory research is often qualitative in nature, you may need to conduct quantitative research with a larger sample size to achieve more generalisable results.

It can be easy to confuse exploratory research with explanatory research. To understand the relationship, it can help to remember that exploratory research lays the groundwork for later explanatory research.

Exploratory research investigates research questions that have not been studied in depth. The preliminary results often lay the groundwork for future analysis.

Explanatory research questions tend to start with ‘why’ or ‘how’, and the goal is to explain why or how a previously studied phenomenon takes place.

Like any other research design , exploratory research has its trade-offs: it provides a unique set of benefits but also comes with downsides.

• It can be very helpful in narrowing down a challenging or nebulous problem that has not been previously studied.
• It can serve as a great guide for future research, whether your own or another researcher’s. With new and challenging research problems, adding to the body of research in the early stages can be very fulfilling.
• It is very flexible, cost-effective, and open-ended. You are free to proceed however you think is best.

Disadvantages

• It usually lacks conclusive results, and results can be biased or subjective due to a lack of preexisting knowledge on your topic.
• It’s typically not externally valid and generalisable, and it suffers from many of the challenges of qualitative research .
• Since you are not operating within an existing research paradigm, this type of research can be very labour-intensive.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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• Exploratory Research: What are its Method & Examples?

Research is a continuous process that needs improvement as time goes by, and as such is non-exhaustive. Although, a lot of researchers working on novel projects, most researchers work on existing theories or formulations and build on them.

Researchers may decide to work on a problem that has not been studied very clearly to establish priorities, develop operational definitions and improving the final research design. This type of research is what is called exploratory research. 

What is Exploratory Research

Exploratory research is the process of investigating a problem that has not been studied or thoroughly investigated in the past . Exploratory type of research is usually conducted to have a better understanding of the existing problem, but usually doesn’t lead to a conclusive result. 

Researchers use exploratory research when trying to gain familiarity with an existing phenomenon and acquire new insight into it to form a more precise problem. It begins based on a general idea and the outcomes of the research are used to find out related issues with the topic of the research.

In exploratory research, the process of the research varies according to the finding of new data or insight. Also referred to as interpretative research or grounded theory approach, the outcomes of this research provide answers to questions like what, how and why. 

Characteristics of Exploratory Research 

• Exploratory research is inexpensive, highly interactive and open-ended in nature.
• There is usually no prior relevant information available from past researchers.
• It has no predefined structure.
• It answers questions like how and why aiding the researcher to acquire more information about the research.
• The absence of relevant information from past research means the researcher will spend a lot of time studying materials in detail. Therefore, spending so much time conducting exploratory research.
• Since there is no standard for carrying out exploratory research, it is usually flexible and scattered.
• There must a few theories which can verify your outcome.
• Researchers cannot form a conclusion based on exploratory research.
• The research problem must be important and valuable
• Exploratory research mostly deals with qualitative data.

Exploratory Research Methods

There are several exploratory research methods available for data gathering and research. However, exploratory research has been classified into two main methods, namely the primary and secondary research methods . The process of conducting research tends to be more difficult when dealing with a problem that hasn’t been deeply investigated before.

Primary Research Methods

In primary research methods , data is collected directly from the subject of investigation. The subject, in this case, maybe a group of people or an individual. 

It doesn’t matter whether the data is collected by the researcher himself or through a third party, the main purpose of the research should be fulfilled. The purpose of conducting this research is to collect information about the problem which requires in-depth analysis.

Some of the primary research methods used in exploratory research include:

• Observations

In this primary research method, the researcher does not come in close contact with the subject. Rather, the subject is being watched from afar. Subject observation can be done in two ways.

The first is that the subject is aware that he/she is being observed while the second way is that the subject is not aware of it. The latter method is said to gather fairer data because the subject may behave differently when he/she is aware that (s)he is being watched. 

Surveys are used to collect data from a predefined subject(s). It can be used collected to study trends, opinions, and behaviour of a group of people.

Online form builders like Formplus have made it easier to conduct surveys online and reach diverse demography of participants from all over the world. Although, rarely in use these days, researchers can also conduct offline surveys. 

Although more stressful and time-consuming than others, the interview technique is the best in terms of collecting detailed and correct data. Interviews can be conducted in person, via phone call or video call.

Interviews can also be recorded by the researcher in case he/she needs to go back to it and confirm specific information. 

• Focus Groups

Focus group is often used by researchers when trying to collect data from a group of people with similar characteristics. The research can be done using any of the three methods explained above.

For example, a focus group of fresh graduates may be investigated on how they spend their time. 

Secondary Research Methods 

Secondary research method uses existing resources on the subject under study. Existing sources like newspapers, magazines, articles, papers, etc. are what researchers conduct for exploratory research. 

All the resources used must be cited in publications. Some of the secondary research methods used in exploratory research include:

Literature research is the process of conducting old resources like publications, textbooks, articles, magazines, etc. All this information can be gathered in both sift copy and hard copy documents.

For example, an undergraduate student conducting his/her final project research will need to conduct textbooks, publications, papers, articles, etc. 

• Online Sources

With the advent of technology, this research has gained much popularity among millennials. Online research sources are the cheapest and easiest method of research.

With access to the internet and a personal computer or mobile phone, a researcher can browse through as many resources as possible. They can also be downloaded for further use in the future. 

The setback of this method is the difficulty of combing through the many online resources to find genuine information. Researchers face the possibility of ending up with incorrect data because false information may be difficult to identify. 

A researcher might find relevant information on the problem under study by studying existing cases. For example, a mathematician trying to formulate a model to solve the queuing problem in an airport may conduct existing research in similar areas.

A case study could be research that solved the queuing problem in a shopping mall. This research will be studied and modified to suit that of the airport queuing problem. 

A researcher may decide to get more creative by using informal sources like email newsletter subscription, RSS feeds, google alerts, google trends or even design a bot that combs through the large repository of data online.

How To Conduct Exploratory Research

Step 1 – identify the problem.

This is a common starting point for all types of research. Here, the researcher identifies the purpose of the research by answering the “what question”.For example, when investigating a crime scene, the FBI needs to first identify what happened. Was it theft, murder or a case of child abuse? 

Step 2 – Create the hypothesis

After identifying the problem, the researcher goes ahead to check whether there have been prior investigations regarding the subject matter. But when the researcher realizes that there are no previous investigations, he/she arrives at a hypothesis based on the questions obtained while identifying the problem.

If you are investigating a crime scene, an autopsy will be performed on the dead body to answer how he/she was killed. Questions like, Was he in a gang?, Fighting over a business deal? or very rich? will answer the question of why he was killed. 

With this information, the investigator can arrive at a hypothesis. 

Step 3 – Conduct further research 

To conduct further research, the researcher needs to first obtain relevant data that will assist in the research process. Some of the methods of collecting data include interviews, surveys, online sources, etc. 

Once the data has been collected, the researcher will continue the investigation through descriptive methods. This process uses qualitative data. 

Examples of Exploratory Research 

In this section, we shall be considering three examples of exploratory research and will be going through the research process as explained above. 

Exploratory Research Example on Murder Investigation

A fresh or inconclusive murder case will be investigated using exploratory research because it has not been investigated clearly in the past. To gain a better understanding of how exploratory research is used to conduct a murder investigation, let us review this popular crime movie titled Murder on the Orient Express .  

Adapted from Agatha Christie’s novel , we see in this movie that the first thing detective Hercule Poirot did was to identify the problem which is the murder of Ratchett. After that was the question of how he was killed. 

The how consists of the murder weapon, how it was used, the time he was murdered, etc. The last piece of information the detective needed to nail the culprit was the why. 

By discovering why Ratchett was murdered, the detective can easily arrive at a hypothesis on who the murderer is. In the search for why the detective used a primary research approach to collect relevant data that will aid the investigation. 

When an avalanche stops the Orient Express dead in its tracks, the world’s greatest detective–Hercule Poirot–arrives to interrogate all passengers and search for clues before the killer can strike again. After a series of interviews, the detective was able to arrive at a hypothesis on who the killer was. 

The results of any criminal investigation will remain a hypothesis until tried under a court which will either confirm or nullify the hypothesis. The evidence acquired during the investigation is what will assist the court in making a decision. 

Exploratory Research Example on Product Research

Organizations conduct two major research when working on a new product or service. The first one is conducted before developing the product while the second one is conducted after product development. 

Our focus will be on the exploratory research conducted after product development. For tech products, it is called the beta testing stage of product development. 

If a new feature is added to an existing app, for example, product researchers will want to investigate whether the feature will be well received among the users. If the feature added to the app is something that is already in existence, then the research is not exploratory. 

For example, if telegram adds a status feature to its app, the beta research stage of the app is not exploratory. This is because this feature is something that is already in existence, and they can easily get enough information from WhatsApp.

However, if it is a new feature like the Snapchat filters when they just came out, the research is explanatory. In this case, exploratory research is carried out using a focus group of beta testers. 

Trend Analysis

A good example of trend analysis research is studying the relationship between an increased rate of charity and crime rate in a community. Will giving food, clothes, etc. to the people in a community help decrease the rate at which people steal?

This exploratory research may be conducted through observations. A sample crime laden community will be given charity for a certain period, while the crime rate during this period will be observed. 

This kind of research is better carried out when the subject is not aware they are under observation. An alternative to this approach is using the case study method. 

Although this research may not have been done in this specific community, something similar may have been done in the past. If that is the case, the research can be easily carried out by investigating the case study to get relevant information. 

This will make the research process easier and a hypothesis easier to come by. 

How to use Formplus for Exploratory Surveys 

Start creating exploratory surveys with Formplus in three easy steps.

Step 1: Register or Sign up

• Visit www.formpl.us on your desktop or mobile device.
• Sign up through your Email, Google or Facebook in less than 30 seconds.

Step 2: Create Your Exploratory Survey

We will be creating a product research exploratory survey in this guide. Consider a software company that just added some new features to their app. The app is currently in the beta testing stage and they are taking an exploratory survey to get feedback from the beta testers.

Radio Choice Multiple Choice Question

• Click on the Choice Options section of the form builder menu.
• Create Radio multiple choice questions by clicking on the radio tab.
• Edit the question with your preferred stem and choice options.

Open-Ended Question

• Click on the Inputs section of the form builder menu.
• Create a short text open-ended question by clicking on the Short Text tab.

• Edit the label and placeholder text as preferred.

Checkbox Multiple Choice Question

• Create a checkbox multiple choice question by clicking on the radio tab.

Matrix Rating Multiple Choice Question

• Click on the Ratings section of the form builder menu.
• Create a matrix rating by clicking on the Matrix tab.
• Edit the table as preferred.

• Save your exploratory survey.

You can also add more questions as preferred. 

Step 3: Customise and Share

This is the final stage where you customise your form and start sharing with respondents.

Feel free to customise your forms as you please. You can also add logic in the settings before sharing.

• Copy the link or click on the “Preview Form” button to see how your form looks like.

Advantages of Exploratory Research

• Exploratory research is inexpensive to perform, especially when using the second method for research.
• Exploratory does not have a standard process and as such is very flexible.
• Information gathered from exploratory research is very useful as it helps lay the foundation for future research.
• It gives researchers more insight into the problem under study.
• Researchers don’t have to waste time conducting irrelevant research when using an exploratory approach. It helps the researcher if the topic is worth investigating at an early stage.

Disadvantages of Exploratory Research

• It produces an inconclusive result.
• Exploratory research provides qualitative data, which may be difficult to interpret. The interpretation of qualitative data may be bias and/or judgemental.
• Many of the data collected through secondary sources may be old and outdated.
• If collected through online sources, the researcher may be prone to collecting false information.
• Exploratory research mostly involves a smaller sample whose results may be incorrect for a larger population.

Conclusion  

Research is built on the incredible inquisitive and resourceful minds of researchers and the urge to solve problems. This stems from the child-like tendency to frequently ask questions like what, why, and how—a trademark of exploratory research. 

Exploratory research is one of the three main objectives of market research, with the other two being descriptive research and causal research. It is commonly used for various applied research projects. 

Applied research is often exploratory because there is a need for flexibility in approaching the problem. Also, there are often data limitations and a need to decide within a short period. 

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• 10 min read

Exploratory Research: Definition & How To Conduct This Research

Updated: Mar 26

If you have a lack of understanding of a topic of interest and nothing is known about it or is a challenging process in data collection. This is where exploratory research comes in.

Table of contents:

What is meant by Exploratory Research?

Exploratory research methods, what is the main purpose of exploratory research, characteristics of exploratory research, advantages of exploratory research, disadvantages of exploratory research.

Examples of Exploratory Research  

How to conduct Exploratory Research

[Disclosure: This post contains affiliate links, meaning we get a commission if you decide to make a purchase through these links at no additional cost to you.]

Exploratory research allows for a better understanding of topics or areas that have limited or no information but will not provide final conclusive evidence for research questions or solutions to issues. This often occurs when phenomena are difficult to measure.

By conducting this kind of research will allow for the subject matter to be more clearly defined, so further research may be carried out that is measured and final. Otherwise, you can explore and understand areas that you are unable to measure such as the atmosphere at an event, looking at things like sound, décor, location, colours and people.

The type of exploratory research methods is split between quantitative research and qualitative research, where the latter is used more often for this type of research. Firstly, quantitative research will be methods like pilot or expert surveys and secondary research (published literature, case studies of similar instances, online sources), while qualitative research will be in-depth interviews, focus groups and observational research. So, as you can see both primary research and secondary research methods are used in exploratory research.

If you want to know more about quantitative and qualitative research methods, this is explained in much more detail in this interesting post – pros and cons of qualitative research vs quantitative research .

Quantitative Research Methods:

Surveys: Using paper or online questionnaires to collect numerical data.

Experiments: Conducting experiments under controlled conditions to observe effects of manipulated variables.

Observational Studies : Observing and recording specific behaviours.

Longitudinal Studies: Long-term studies often conducted over several years or decades.

Cross-sectional Studies: Examines data from a population at a specific point in time.

Correlational Research: Examining relationships between multiple variables.

Causal-comparative Research: Establishing cause-effect relationships among variables.

Secondary research: is a review of existing materials or secondary sources like books, articles, and online resources that give you an insight into the subject of interest and helps build the foundation of further research.

Qualitative Research Methods:

Interviews: Conducting one-on-one or group interviews to gain insights into respondents’ experiences and perspectives.

Focus Groups: Gathering a group of people together to discuss specific topics or issues.

Ethnography: Studying individuals in their natural settings.

Case Studies: In-depth studies of a single individual, group, or event.

The purpose of exploratory research is broken down into three main elements to gain a better understanding of topics or problems that are vague and not clearly defined, to form hypothesises to be examined and test the feasibility of ideas.

The following are 7 reasons for using exploratory research:

1. To identify new opportunities

Exploratory research can help a company to identify new business opportunities. For instance, through exploratory research, a beverage company may discover a growing trend of health-conscious consumers leading them to launch a new line of organic, sugar-free beverages.

2. Understand consumer behaviour

It can also be used to understand consumer behaviour, attitudes, and preferences, enabling organisations to adjust their strategies accordingly. For example, a hotel chain may use exploratory research to find out what amenities or services customers value the most, leading to improvements that increase customer satisfaction and loyalty.

3. Support in diagnosing problems

It can assist in diagnosing a problem in a specific market or business operation. A failing product or a decline in sales might be due to several factors, and exploratory research can help identify those factors. For instance, a tech company witnessing a drop in their software sales might conduct exploratory research and find out that bugs and inefficient customer support are the reasons for the decline.

4. Help to formulate hypotheses

Exploratory research fuels hypothesis generation for future, confirmatory research by revealing tendencies and patterns. For example, researchers might initially explore the effects of social media usage on mental health, noting potential associations which can then be further tested in future research.

5. Assist in market segmentation

It can also aid in market segmentation by exploring customer behaviour and preferences in-depth, companies can identify distinct customer segments and tailor their marketing efforts accordingly. A car manufacturing company, for example, might conduct exploratory research to understand customer preferences regarding electric vehicles. The findings may then be used to segment the market based on environmental awareness, technology inclination, or income levels.

6. Testing feasibility of new ideas

Exploratory research can be used to test the feasibility of new product ideas or concepts before investing significant resources. For example, an e-commerce company might use exploratory research to gauge users’ responses to a proposed new feature before implementing it on their platform. It's also used to identify and explore concepts for different forms of marketing communications .

7. Helps to prepare for large scale research

It often serves as the foundation to larger, more detailed studies. It enables researchers to refine their research questions and select the appropriate research methods for subsequent stages. For example, before launching a nationwide survey on public opinion towards immigration policies, a research organisation might first conduct exploratory research on a smaller scale to fine-tune the survey design and questions.

Offers valuable insights : Exploratory research is frequently utilised to gain valuable insights into the underlying reasons, opinions, and motivations.

Embraces both qualitative and quantitative approaches : This type of research can encompass qualitative techniques such as focus groups and in-depth interviews, as well as quantitative methods like surveys for statistical analysis.

Uncovers fresh perspectives : It is employed to uncover new ideas and hypotheses for future, quantitative research.

Limited knowledge exists : Exploratory research is conducted when there is limited understanding or when a problem area has never been addressed before.

Prone to changes : As the research progresses, the direction and focus of the investigation may undergo significant changes.

Less formal procedures : The procedures used in exploratory research are typically less rigidly structured compared to conclusive research.

Initial phase of research : It usually serves as the first step in the research process, setting the foundation for further studies and experiments.

Utilises smaller sample sizes : Due to its qualitative nature, exploratory research often involves smaller sample sizes.

Not intended for definitive conclusions : The objective of this research type is to explore rather than draw definitive conclusions or make final decisions.

Shapes research questions and hypotheses : The findings of exploratory research are frequently used to define the research questions and hypotheses of larger, more conclusive studies.

1. Helps to uncover new insights

Exploratory research is advantageous because it can uncover new ideas and patterns. For example, a cosmetics company could use this research to discover unexpected trends or attitudes towards skincare among men, helping them develop more targeted marketing strategies and products.

2. Provides flexibility during the research process

This type of research has high flexibility. Researchers can alter their direction based on findings as they progress. For instance, an automobile company might initially be exploring customer preferences for car colours, but upon discovering an interesting trend in preference for electric cars, they might shift their investigation towards this new direction.

3. Gain a deep understanding of motivations and behaviours

Exploratory research dives deep into understanding behaviours and motivations, providing a rich, qualitative perspective. A clothing company could use interviews or focus groups to understand the emotional connections customers have with certain types of clothing.

4. Opportunity to refine research questions

If researchers are unsure what they're looking for, exploratory research allows them to define their research questions more clearly. For example, a tech start-up might start investigating general user behaviour, but through exploration, they can refine their research question to be about user interaction with a specific feature.

1. Can be very time consuming

This research is often open-ended and requires significant time to be spent on data collection and interpretation. For instance, a company studying consumer shopping behaviours might need to collect data over a long period to see trends and patterns.

2. It can lack representativeness of a larger target population

Since exploratory research often involves a smaller sample size, it may not represent the larger target population accurately. For example, a study of coffee preference involving a small, localised group may not accurately reflect the preferences of coffee drinkers nationwide.

3. There can be potential bias drawn from the data

Since this research often requires subjective interpretation from the researcher, it is susceptible to bias. For example, a researcher studying company culture might interpret results based on their own perspective or experiences, skewing the findings.

4. No concrete conclusions

Due to its qualitative and investigative nature, exploratory research often cannot provide definitive answers or statistical proof. For instance, a study exploring why a product is failing in the market might raise several probable reasons, but it may not pinpoint the exact cause.

Examples of Exploratory Research

An example of exploratory research is where a brand is looking to change the packaging for an existing ready meal product to make it more appealing, so gets the thoughts and views from customers and buyers of ready meals in general, on what they think of the current design, things they don’t like, the things they look for or appeal to them and the aesthetics. This is done via focus groups and the feedback from this will help to mock -up new concept designs, which can then be tested in further research in deciding which packaging design to go for.

Another example of exploratory research is in new product development of a new smart phone, where there are a large number of concept ideas that have been drawn up but now need to be scaled down by using both focus groups and an initial pilot survey , so then a couple of popular concepts can then be fully examined and compared in additional research.

This just illustrates the many examples of how exploratory research can be used.

The following are 6 real life examples of exploratory research in practice:

In order to expand and improve its services Airbnb had to conduct exploratory research on potential markets. They looked into different countries and cities, analysing cultural attitudes towards short term rentals, legal constraints, and potential demand. They also researched prospective host communities and their potential needs and concerns. This research was crucial in helping Airbnb identify new markets, understand how they could be competitive, and find ways to ensure their service was attractive to both hosts and guests.

When Spotify wanted to create a personalised playlist feature, ‘Discover Weekly,’ they used exploratory research to understand the listening behaviours and preferences of their users. They analysed listener’s habits, genres, and artists popularity, and song frequency to develop a unique, customized algorithm. This research allowed Spotify to create a highly successful feature that significantly increased user engagement.

3. Coca Cola

Coca Cola has used exploratory research numerous times to develop new products and marketing strategies. For example, in an effort to appeal to a younger demographic, they conducted research on youth lifestyle trends, tastes, and preferences. This research led to the development of Coca Cola Zero, a drink aimed specifically at millennials and Gen Z.

Toyota conducted exploratory research when it was planning to develop and launch its hybrid vehicle, the Prius. The company needed to understand if there was a market for a car that used a different form of technology. They explored consumer concerns about the environment and energy costs, government regulations, and the development in technology. This research enabled Toyota to launch the first mass-produced hybrid vehicle, which was a great success.

5. Facebook

When Facebook planned to introduce the 'Like' button, they used exploratory research to anticipate how it might be received by users. They conducted surveys and interviews, observing how people interacted with the platform and they explored their feelings about different features. This research helped Facebook in refining the 'Like' button concept and eventually in launching it effectively and successfully.

6. Microsoft

Microsoft frequently uses exploratory research to develop and improve its products. For instance, when creating their adaptive controller for the Xbox, they carried out research into how people with mobility limitations interact with technology. They invited people with a range of physical disabilities to participate in trials, working with them to find ways to make gaming more accessible. The insights gained from this research led to a controller that has opened up gaming to a wider audience.

The following are 5 common steps in how to conduct exploratory research:

Step 1: Identify the problem

The very first step in conducting exploratory research is identifying the problem in a clear and concise manner that needs to be addressed and decide if this is the most suitable approach to take, which is most likely if there is little or no information readily available. For example, in designing a new logo and coming up with draft concept ideas that will appeal to customers. So, what kind of things to include in the logo that will have a positive impact, while still retaining the values of the brand.

Step 2: Hypothesis for a possible answer

After you identified the problem and decided this is the correct path to take, you will need to formulate a hypothesis on what the possible answer could be in order to help you manage the research you are doing such as customers will prefer more of a modern type of logo design of the brand.

Step 3: Design the methodology that will be used

Design a research approach that will incapsulate how you envisage the analysis will be and how that will tie in with the chosen data collection method that will be used like in-depth interviews, focus groups or desk research . For example, conducting in-depth interviews with internal stakeholders (suppliers, distributors, staff) and focus groups with customers to discuss whether the brand logo needs modernising.

Step 4: Gather feedback for analysis

Now moving onto collecting the feedback allows you the opportunity to then analyse this information and see if there are common patterns or themes that are emerging. Plus, exploratory research gives you the flexibility to change your initial hypothesis if the results are different to what you were expecting. Using the logo design example, this would be seeing if the common consensus should be moving the brand logo design to a more modern style or does it differ between different groups (customers, non-customers, stakeholders).

Step 5: Possibility of further research

After the results have been analysed, you may decide follow-up research is needed to get a fuller picture and answer the research questions you may have, which could lead to a survey with a large sample of respondents to give something that is more measurable and also statistical comparisons can be made. For example, a concept test survey can then be used to compare the current and new potential logo designs and see which is most preferred.

You can use a simple and inexpensive (from $15) service like PickFu to run a poll across 9 countries like the US, Canada, Australia and the UK to compare, rank and comment on different designs, logos, book covers, webpages, apps and advertising messaging to help you make informed decisions.

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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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Exploratory data analysis: frequencies, descriptive statistics, histograms, and boxplots.

Jacob Shreffler ; Martin R. Huecker .

Affiliations

Last Update: November 3, 2023 .

• Definition/Introduction

Researchers must utilize exploratory data techniques to present findings to a target audience and create appropriate graphs and figures. Researchers can determine if outliers exist, data are missing, and statistical assumptions will be upheld by understanding data. Additionally, it is essential to comprehend these data when describing them in conclusions of a paper, in a meeting with colleagues invested in the findings, or while reading others’ work.

• Issues of Concern

This comprehension begins with exploring these data through the outputs discussed in this article. Individuals who do not conduct research must still comprehend new studies, and knowledge of fundamentals in analyzing data and interpretation of histograms and boxplots facilitates the ability to appraise recent publications accurately. Without this familiarity, decisions could be implemented based on inaccurate delivery or interpretation of medical studies.

Frequencies and Descriptive Statistics

Effective presentation of study results, in presentation or manuscript form, typically starts with frequencies and descriptive statistics (ie, mean, medians, standard deviations). One can get a better sense of the variables by examining these data to determine whether a balanced and sufficient research design exists. Frequencies also inform on missing data and give a sense of outliers (will be discussed below).

Luckily, software programs are available to conduct exploratory data analysis. For this chapter, we will be examining the following research question.

RQ: Are there differences in drug life (length of effect) for Drug 23 based on the administration site?

A more precise hypothesis could be: Is drug 23 longer-lasting when administered via site A compared to site B?

To address this research question, exploratory data analysis is conducted. First, it is essential to start with the frequencies of the variables. To keep things simple, only variables of minutes (drug life effect) and administration site (A vs B) are included. See Image. Figure 1 for outputs for frequencies.

Figure 1 shows that the administration site appears to be a balanced design with 50 individuals in each group. The excerpt for minutes frequencies is the bottom portion of Figure 1 and shows how many cases fell into each time frame with the cumulative percent on the right-hand side. In examining Figure 1, one suspiciously low measurement (135) was observed, considering time variables. If a data point seems inaccurate, a researcher should find this case and confirm if this was an entry error. For the sake of this review, the authors state that this was an entry error and should have been entered 535 and not 135. Had the analysis occurred without checking this, the data analysis, results, and conclusions would have been invalid. When finding any entry errors and determining how groups are balanced, potential missing data is explored. If not responsibly evaluated, missing values can nullify results.  

After replacing the incorrect 135 with 535, descriptive statistics, including the mean, median, mode, minimum/maximum scores, and standard deviation were examined. Output for the research example for the variable of minutes can be seen in Figure 2. Observe each variable to ensure that the mean seems reasonable and that the minimum and maximum are within an appropriate range based on medical competence or an available codebook. One assumption common in statistical analyses is a normal distribution. Image . Figure 2 shows that the mode differs from the mean and the median. We have visualization tools such as histograms to examine these scores for normality and outliers before making decisions.

Histograms are useful in assessing normality, as many statistical tests (eg, ANOVA and regression) assume the data have a normal distribution. When data deviate from a normal distribution, it is quantified using skewness and kurtosis. [1]  Skewness occurs when one tail of the curve is longer. If the tail is lengthier on the left side of the curve (more cases on the higher values), this would be negatively skewed, whereas if the tail is longer on the right side, it would be positively skewed. Kurtosis is another facet of normality. Positive kurtosis occurs when the center has many values falling in the middle, whereas negative kurtosis occurs when there are very heavy tails. [2]

Additionally, histograms reveal outliers: data points either entered incorrectly or truly very different from the rest of the sample. When there are outliers, one must determine accuracy based on random chance or the error in the experiment and provide strong justification if the decision is to exclude them. [3]  Outliers require attention to ensure the data analysis accurately reflects the majority of the data and is not influenced by extreme values; cleaning these outliers can result in better quality decision-making in clinical practice. [4]  A common approach to determining if a variable is approximately normally distributed is converting values to z scores and determining if any scores are less than -3 or greater than 3. For a normal distribution, about 99% of scores should lie within three standard deviations of the mean. [5]  Importantly, one should not automatically throw out any values outside of this range but consider it in corroboration with the other factors aforementioned. Outliers are relatively common, so when these are prevalent, one must assess the risks and benefits of exclusion. [6]

Image . Figure 3 provides examples of histograms. In Figure 3A, 2 possible outliers causing kurtosis are observed. If values within 3 standard deviations are used, the result in Figure 3B are observed. This histogram appears much closer to an approximately normal distribution with the kurtosis being treated. Remember, all evidence should be considered before eliminating outliers. When reporting outliers in scientific paper outputs, account for the number of outliers excluded and justify why they were excluded.

Boxplots can examine for outliers, assess the range of data, and show differences among groups. Boxplots provide a visual representation of ranges and medians, illustrating differences amongst groups, and are useful in various outlets, including evidence-based medicine. [7]  Boxplots provide a picture of data distribution when there are numerous values, and all values cannot be displayed (ie, a scatterplot). [8]  Figure 4 illustrates the differences between drug site administration and the length of drug life from the above example.

Image . Figure 4 shows differences with potential clinical impact. Had any outliers existed (data from the histogram were cleaned), they would appear outside the line endpoint. The red boxes represent the middle 50% of scores. The lines within each red box represent the median number of minutes within each administration site. The horizontal lines at the top and bottom of each line connected to the red box represent the 25th and 75th percentiles. In examining the difference boxplots, an overlap in minutes between 2 administration sites were observed: the approximate top 25 percent from site B had the same time noted as the bottom 25 percent at site A. Site B had a median minute amount under 525, whereas administration site A had a length greater than 550. If there were no differences in adverse reactions at site A, analysis of this figure provides evidence that healthcare providers should administer the drug via site A. Researchers could follow by testing a third administration site, site C. Image . Figure 5 shows what would happen if site C led to a longer drug life compared to site A.

Figure 5 displays the same site A data as Figure 4, but something looks different. The significant variance at site C makes site A’s variance appear smaller. In order words, patients who were administered the drug via site C had a larger range of scores. Thus, some patients experience a longer half-life when the drug is administered via site C than the median of site A; however, the broad range (lack of accuracy) and lower median should be the focus. The precision of minutes is much more compacted in site A. Therefore, the median is higher, and the range is more precise. One may conclude that this makes site A a more desirable site.

• Clinical Significance

Ultimately, by understanding basic exploratory data methods, medical researchers and consumers of research can make quality and data-informed decisions. These data-informed decisions will result in the ability to appraise the clinical significance of research outputs. By overlooking these fundamentals in statistics, critical errors in judgment can occur.

• Nursing, Allied Health, and Interprofessional Team Interventions

All interprofessional healthcare team members need to be at least familiar with, if not well-versed in, these statistical analyses so they can read and interpret study data and apply the data implications in their everyday practice. This approach allows all practitioners to remain abreast of the latest developments and provides valuable data for evidence-based medicine, ultimately leading to improved patient outcomes.

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Exploratory Data Analysis Figure 1 Contributed by Martin Huecker, MD and Jacob Shreffler, PhD

Exploratory Data Analysis Figure 2 Contributed by Martin Huecker, MD and Jacob Shreffler, PhD

Exploratory Data Analysis Figure 3 Contributed by Martin Huecker, MD and Jacob Shreffler, PhD

Exploratory Data Analysis Figure 4 Contributed by Martin Huecker, MD and Jacob Shreffler, PhD

Exploratory Data Analysis Figure 5 Contributed by Martin Huecker, MD and Jacob Shreffler, PhD

Disclosure: Jacob Shreffler declares no relevant financial relationships with ineligible companies.

Disclosure: Martin Huecker declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Shreffler J, Huecker MR. Exploratory Data Analysis: Frequencies, Descriptive Statistics, Histograms, and Boxplots. [Updated 2023 Nov 3]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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What is explanatory research?

Last updated

12 June 2023

Reviewed by

Miroslav Damyanov

The search for knowledge and understanding never stops in the field of research. Researchers are always finding new techniques to help analyze and make sense of the world. Explanatory research is one such technique. It provides a new perspective on various areas of study.

So, what exactly is explanatory research? This article will provide an in-depth overview of everything you need to know about explanatory research and its purpose. You’ll also get to know the different types of explanatory research and how they’re conducted.

Analyze explanatory research

Get a deeper understanding of your explanatory research when you analyze it in Dovetail

• Explanatory research: definition

Explanatory research is a technique used to gain a deeper understanding of the underlying reasons for, causes of, and relationships behind a particular phenomenon that has yet to be extensively studied.

Researchers use this method to understand why and how a particular phenomenon occurs the way it does. Since there is limited information regarding the phenomenon being studied, it’s up to the researcher to develop fresh ideas and collect more data.

The results and conclusions drawn from explanatory research give researchers a deeper understanding and help predict future occurrences.

• Descriptive research vs. explanatory research

Descriptive research aims to define or summarize an event or population without explaining why it exists. It focuses on acquiring and conveying facts.

On the other hand, explanatory research aims to explain why a phenomenon occurs by working to understand the causes and correlations between variables.

Unlike descriptive research, which focuses on providing descriptions and characteristics of a given phenomenon, explanatory research goes a step further to explain different mechanisms and the reasons behind them. Explanatory research is never concerned with producing new knowledge or solving problems. Instead, it aims to explain why and how something happens.

• Exploratory research vs. explanatory research

Explanatory research explains why specific phenomena function as they do. Meanwhile, exploratory research examines and investigates an issue that is not clearly defined. Both methods are crucial for problem analysis.

Researchers use exploratory research at the outset to discover new ideas, concepts, and opportunities. Once exploratory research has identified a potential area of interest or problem, researchers employ explanatory research to delve further into the specific subject matter.

Researchers employ the explanatory research technique when they want to explain why and how something occurs in a certain way. Researchers who employ this approach usually have an outcome in mind, and carrying it out is their top priority.

• When to use explanatory research

Explanatory research may be helpful in the following situations:

When testing a theoretical model: explanatory research can help researchers develop a theory. It can provide sufficient evidence to validate or refine existing theories based on the available data.

When establishing causality: this research method can determine the cause-and-effect relationships between study variables and determine which variable influences the predicted outcome most. Explanatory research explores all the factors that lead to a certain outcome or phenomenon.

When making informed decisions: the results and conclusions drawn from explanatory research can provide a basis for informed decision-making. It can be helpful in different industries and sectors. For example, entrepreneurs in the business sector can use explanatory research to implement informed marketing strategies to increase sales and generate more revenue.

When addressing research gaps: a research gap is an unresolved problem or unanswered question due to inadequate research in that space. Researchers can use explanatory research to gather information about a certain phenomenon and fill research gaps. It also enables researchers to answer previously unanswered questions and explain different mechanisms that haven’t yet been studied.

When conducting program evaluation: researchers can also use the technique to determine the effectiveness of a particular program and identify all the factors that are likely to contribute to its success or failure.

• Types of explanatory research

Here are the different types of explanatory research:

Case study research: this method involves the in-depth analysis of a given individual, company, organization, or event. It allows researchers to study individuals or organizations that have faced the same situation. This way, they can determine what worked for them and what didn’t.

Experimental research: this involves manipulating independent variables and observing how they affect dependent variables. This method allows researchers to establish a cause-and-effect relationship between different variables.

Quasi-experimental research: this type of research is quite similar to experimental research, but it lacks complete control over variables. It’s best suited to situations where manipulating certain variables is difficult or impossible.

Correlational research: this involves identifying underlying relationships between two or more variables without manipulating them. It determines the strength and direction of the relationship between different variables.

Historical research: this method involves studying past events to gain a better understanding of their causes and effects. It’s mostly used in fields like history and sociology.

Survey research: this type of explanatory research involves collecting data using a set of structured questionnaires or interviews given to a representative sample of participants. It helps researchers gather information about individuals’ attitudes, opinions, and behaviors toward certain phenomena.

Observational research: this involves directly observing and recording people in their natural setting, like the home, the office, or a shop. By studying their actions, needs, and challenges, researchers can gain valuable insights into their behavior, preferences, and pain points. This results in explanatory conclusions.

• How to conduct explanatory research

Take the following steps when conducting explanatory research:

Develop the research question

The first step is to familiarize yourself with the topic you’re interested in and clearly articulate your specific goals. This will help you define the research question you want to answer or the problem you want to solve. Doing this will guide your research and ensure you collect the right data.

Formulate a hypothesis

The next step is to formulate a hypothesis that will address your expectations. Some researchers find that literature material has already covered their topic in the past. If this is the case with you, you can use such material as the main foundation of your hypothesis. However, if it doesn’t exist, you must formulate a hypothesis based on your own instincts or literature material on closely related topics.

Select the research type

Choose an appropriate research type based on your research questions, available resources, and timeline. Consider the level of control you need over the variables.

Next, design and develop instruments such as surveys, interview guides, or observation guidelines to gather relevant data.

Collect the data

Collecting data involves implementing the research instruments and gathering information from a representative sample of your target audience. Ensure proper data collection protocol, ethical considerations , and appropriate documentation for the data you collect.

Analyze the data

Once you have collected the data you need for your research, you’ll need to organize, code, and interpret it.

Use appropriate analytical methods, such as statistical analysis or thematic coding , to uncover patterns, relationships, and explanations that address your research goals and questions. You may have to suggest or conduct further research based on the results to elaborate on certain areas.

Communicate the results

Finally, communicate your results to relevant stakeholders , such as team members, clients, or other involved partners. Present your insights clearly and concisely through reports, slides, or visualizations. Provide actionable recommendations and avenues for future research.

• Examples of explanatory research

Here are some real-life examples of explanatory research:

Understanding what causes high crime rates in big cities

Law enforcement organizations use explanatory research to pinpoint what causes high crime rates in particular cities. They gather information about various influencing factors, such as gang involvement, drug misuse, family structures, and firearm availability.

They then use regression analysis to examine the data further to understand the factors contributing to the high crime rates.

Factors that influence students’ academic performance

Educators and stakeholders in the Department of Education use questionnaires and interviews to gather data on factors that affect academic performance. These factors include parental engagement, learning styles, motivation, teaching quality, and peer pressure.

The data is used to ascertain how these variables affect students’ academic performance.

Examining what causes economic disparity in certain areas

Researchers use correlational and experimental research approaches to gather information on variables like education levels, household income, and employment rates. They use the information to examine the causes of economic disparity in certain regions.

• Advantages of explanatory research

Here are some of the benefits you can expect from explanatory research:

Deeper understanding : the technique helps fill research gaps in previous studies by explaining the reasons, causes, and relationships behind particular behaviors or phenomena.

Competitive edge: by understanding the underlying factors that drive customer satisfaction and behavior, companies can create more engaging products and desirable services.

Predictable capabilities: it helps researchers and teams make predictions regarding certain phenomena like user behavior or future iterations of product features.

Informed decision-making: explanatory research generates insights that can help individuals make informed decisions in various sectors.

• Disadvantages of explanatory research

Explanatory research is a great approach for better understanding various phenomena, but it has some limitations.

It’s time-consuming: explanatory research can be a time-consuming process, requiring careful planning, data collection, analysis, and interpretation. The technique might extend your timeline.

It’s resource intensive: explanatory research often requires a significant allocation of resources, including financial, human, and technological. This could pose challenges for organizations with limited budgets or constraints.

You have limited control over real-world factors: this type of research often takes place in controlled environments. Researchers may find this limits their ability to capture real-world complexities and variables that influence a particular behavior or phenomenon.

Depth and breadth are difficult to balance : explanatory research mainly focuses on a narrow hypothesis, which can limit the scope of the research and prevent researchers from understanding a problem more broadly.

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How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

• Age & Generations
• Demographic Research
• Generation X
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• Generations
• Greatest Generation
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• Millennials
• Silent Generation

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