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

What Is a Research Design | Types, Guide & Examples

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

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

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

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

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

Types of quantitative research designs

Quantitative designs can be split into four main types.

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

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

• Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

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

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalization

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

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

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

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

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

 Statistics

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

Research bias

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

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

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

Quantitative research designs can be divided into two main categories:

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

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

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

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

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

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

Operationalization means turning abstract conceptual ideas into measurable observations.

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

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

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

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Writing a Research Strategy

This page is focused on providing practical tips and suggestions for preparing The Research Strategy, the primary component of an application's Research Plan along with the Specific Aims. The guidance on this page is primarily geared towards an R01-style application, however, much of it is useful for other grant types as well.

Developing the Research Strategy

The primary audience for your application is your peer review group. When writing your Research Strategy, your goal is to present a well-organized, visually appealing, and readable description of your proposed project and the rationale for pursuing it. Your writing should be streamlined and organized so your reviewers can readily grasp the information. If it's a key point, repeat it, then repeat it again. Add more emphasis by putting the text in bold , or bold italics . If writing is not your forte, get help.  For more information, please visit  W riting For Reviewers .

How to Organize the Research Strategy Section

How to organize a Research Strategy is largely up to the applicant. Start by following the NIH application instructions and guidelines for formatting attachments such as the research plan section.

It is generally structured as follows:

Significance

For  Preliminary Studies (for new applications) or a Progress Report (for renewal and revision applications).

• You can either include preliminary studies or progress report information as a subsection of Approach or integrate it into any or all of the three main sections.
• If you do the latter, be sure to mark the information clearly, for example, with a bold subhead.

 Helpful tips to consider when formatting:

• Organize using bold headers or an outline or numbering system—or both—that are used consistently throughout.
• Start each section with the appropriate header: Significance, Innovation, or Approach.
• Organize the Approach section around the Specific Aims.

For most applications, you need to address Rigor ous Study Design  by describing the experimental design and methods you propose and how they will achieve robust and unbiased results. See the NIH guidance for elaboration on the 4 major areas of rigor and transparency emphasized in grant review.  These requirements apply to research grant, career development, fellowship, and training applications.

Tips for Drafting Sections of the Research Strategy

Although you will emphasize your project's significance throughout the application, the Significance section should give the most details. The farther removed your reviewers are from your field, the more information you'll need to provide on basic biology, importance of the area, research opportunities, and new findings. Reviewing the potentially relevant study section rosters may give you some ideas as to general reviewer expertise. You will also need to describe the prior and preliminary studies that provide a strong scientific rationale for pursuing the proposed studies, emphasizing the strengths and weaknesses in the rigor and transparency of these key studies.

This section gives you the chance to explain how your application is conceptually and/or technically innovative. Some examples as to how you might do this could include but not limited to:

• Demonstrate the proposed research is new and unique, e.g., explores new scientific avenues, has a novel hypothesis, will create new knowledge.
• Explain how the proposed work can refine, improve, or propose a new application of an existing concept or method.

If your proposal is paradigm-shifting or challenges commonly held beliefs, be sure that you include sufficient evidence in your preliminary data to convince reviewers, including strong rationale, data supporting the approach, and clear feasibility. Your job is to make the reviewers feel confident that the risk is worth taking.

For projects predominantly focused on innovation and outside-the-box research, investigators may wish to consider mechanisms other than R01s for example (e.g., exploratory/developmental research (R21) grants, NIH Director's Pioneer Award Program (DP1), and NIH Director's New Innovator Award Program (DP2).

The Approach section is where the experimental design is described. Expect your assigned reviewers to scrutinize your approach: they will want to know what you plan to do, how you plan to do it, and whether you can do it. NIH data show that of the peer review criteria, approach has the highest correlation with the overall impact score. Importantly, elements of rigorous study design should be addressed in this section, such as plans for minimization of bias (e.g. methods for blinding and treatment randomization) and consideration of relevant biological variables. Likewise, be sure to lay out a plan for alternative experiments and approaches in case you get uninterpretable or surprising results, and also consider limitations of the study and alternative interpretations. Point out any procedures, situations, or materials that may be hazardous to personnel and precautions to be exercised. A full discussion on the use of select agents should appear in the Select Agent Research attachment.  Consider including a timeline demonstrating anticipated completion of the Aims. 

Here are some pointers to consider when organizing your Approach section:

• Enter a bold header for each Specific Aim.
• Under each aim, describe the experiments.
• If you get result X, you will follow pathway X; if you get result Y, you will follow pathway Y.
• Consider illustrating this with a flowchart.

Preliminary Studies

If submitting a new application to a NOFO that allows preliminary data, it is strongly encouraged to include preliminary studies.  Preliminary studies demonstrate competency in the methods and interpretation. Well-designed and robust preliminary studies also serve to provide a strong scientific rationale for the proposed follow-up experiments. Reviewers also use preliminary studies together with the biosketches to assess the investigator review criterion, which reflects the competence of the research team. Provide alternative interpretations to your data to show reviewers you've thought through problems in-depth and are prepared to meet future challenges. As noted above, preliminary data can be put anywhere in the Research Strategy, but just make sure reviewers will be able to distinguish it from the proposed studies. Alternatively, it can be a separate section with its own header.

Progress Reports

If applying for a renewal or a revision (a competing supplement to an existing grant), include a progress report for reviewers.

Create a header so reviewers can easily find it and include the following information:

• Project period beginning and end dates.
• Summary of the importance and robustness of the completed findings in relation to the Specific Aims.
• Account of published and unpublished results, highlighting progress toward achieving your Specific Aims.  

Other Helpful Tips

Referencing publications.

References show breadth of knowledge of the field and provide a scientific foundation for your application. If a critical work is omitted, reviewers may assume the applicant is not aware of it or deliberately ignoring it.

Throughout the application, reference all relevant publications for the concepts underlying your research and your methods. Remember the strengths and weaknesses in the rigor of the key studies you cite for justifying your proposal will need to be discussed in the Significance and/or Approach sections.

Read more about Bibliography and References Cited at Additional Application Elements .

Graphics can illustrate complex information in a small space and add visual interest to your application. Including schematics, tables, illustrations, graphs, and other types of graphics can enhance applications. Consider adding a timetable or flowchart to illustrate your experimental plan, including decision trees with alternative experimental pathways to help your reviewers understand your plans.

Video may enhance your application beyond what graphics alone can achieve. If you plan to send one or more videos, you'll need to meet certain requirements and include key information in your Research Strategy. State in your cover letter that a video will be included in your application (don't attach your files to the application). After you apply and get assignment information from the Commons, ask your assigned Scientific Review Officer (SRO) how your business official should send the files. Your video files are due at least one month before the peer review meeting.

However, you can't count on all reviewers being able to see or hear video, so you'll want to be strategic in how you incorporate it into your application by taking the following steps:

• Caption any narration in the video.
• Include key images from the video
• Write a description of the video, so the text would make sense even without the video.

Tracking for Your Budget

As you design your experiments, keep a running tab of the following essential data:

• Who. A list of people who will help (for the Key Personnel section later).
• What. A list of equipment and supplies for the experiments
• Time. Notes on how long each step takes. Timing directly affects the budget as well as how many Specific Aims can realistically be achieved.

Jotting this information down will help when Creating a Budget  and complete other sections later.

Review and Finalize Your Research Plan

Critically review the research plan through the lens of a reviewer to identify potential questions or weak spots.

Enlist others to review your application with a fresh eye. Include people who aren't familiar with the research to make sure the proposed work is clear to someone outside the field.

When finalizing the details of the Research Strategy, revisit and revise the Specific Aims as needed. Please see Writing Specific Aims . 

comments Want to contact NINDS staff? Please visit our Find Your NINDS Program Officer page to learn more about contacting Program Officer, Grants Management Specialists, Scientific Review Officers, and Health Program Specialists.

An Introduction to Design Science pp 39–73 Cite as

Research Strategies and Methods

• Paul Johannesson 3 &
• Erik Perjons 3  
• First Online: 01 January 2014

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Researchers have since centuries used research methods for supporting the creation of reliable knowledge based on empirical evidence and logical arguments. This chapter offers an overview of established research strategies and methods with a focus on empirical research in the social sciences. The chapter discusses research strategies, such as experiment, survey, case study, ethnography, grounded theory, action research, and phenomenology. Research methods for data collection are also described, including questionnaires, interviews, focus groups, observations, and documents. Qualitative and quantitative methods for data analysis are discussed. Finally, the use of research strategies and methods in design science is investigated.

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• Research Strategy
• Discourse Analysis
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• Inferential Statistic

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

Last updated

30 January 2024

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

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

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

• What is a research plan?

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

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

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

• Why do you need a research plan?

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

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

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

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

Project organization and structure

Well-informed participants

All stakeholders and teams align in support of the project

Clearly defined project definitions and purposes

Distractions are eliminated, prioritizing task focus

Timely management of individual task schedules and roles

Costly reworks are avoided

• What should a research plan include?

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

Specific project goals and individual objectives

Ideal strategies or methods for reaching those goals

Required resources

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

Key performance indicators (KPIs)

Project background

Research and testing support

Preliminary studies and progress reporting mechanisms

Cost estimates and change order processes

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

• How to write a research plan for your project

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

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

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

Define your project’s purpose

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

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

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

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

What you’re doing

Why you’re doing it

What you expect from it

Identify individual objectives

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

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

Select research methods

Research methods might include any of the following:

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

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

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

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

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

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

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

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

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

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

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

What do you plan to do with the research findings?

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

Recruit participants and allocate tasks

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

Prepare a thorough project summary

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

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

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

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

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

Create a realistic timeline

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

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

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

Determine how to present your results

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

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

Presentations and slides

A project report booklet

A project findings pamphlet

Documents with key takeaways and statistics

Graphic visuals to support your findings

• Format your research plan

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

Find format inspiration among the following layouts:

Written outlines

Narrative storytelling

Visual mapping

Graphic timelines

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

• Research plan example

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

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

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

Project title

Project members involved in the research plan

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

Objective 1 (provide a short description for each objective)

Objective 2

Objective 3

Proposed timeline

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

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

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

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

Customizing a research plan template

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

Introductions to participants and stakeholders

Background problems and needs statement

Significance, ethics, and purpose

Research methods, questions, and designs

Preliminary beliefs and expectations

Implications and intended outcomes

Realistic timelines for each phase

Conclusion and presentations

How many pages should a research plan be?

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

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

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

What are the seven steps to developing a research plan?

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

Defining the problem

Identifying goals

Choosing research methods

Recruiting participants

Preparing the brief or summary

Establishing task timelines

Defining how you will present the findings

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