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.
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
Once you have outlined your goals, objectives, steps, and tasks, it’s time to drill down on selecting research methods . You’ll want to leverage specific research strategies and processes. When you know what methods will help you reach your goals, you and your teams will have direction to perform and execute your assigned tasks.
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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6.3 Steps in a Successful Marketing Research Plan
Learning outcomes.
By the end of this section, you will be able to:
- 1 Identify and describe the steps in a marketing research plan.
- 2 Discuss the different types of data research.
- 3 Explain how data is analyzed.
- 4 Discuss the importance of effective research reports.
Define the Problem
There are seven steps to a successful marketing research project (see Figure 6.3 ). Each step will be explained as we investigate how a marketing research project is conducted.
The first step, defining the problem, is often a realization that more information is needed in order to make a data-driven decision. Problem definition is the realization that there is an issue that needs to be addressed. An entrepreneur may be interested in opening a small business but must first define the problem that is to be investigated. A marketing research problem in this example is to discover the needs of the community and also to identify a potentially successful business venture.
Many times, researchers define a research question or objectives in this first step. Objectives of this research study could include: identify a new business that would be successful in the community in question, determine the size and composition of a target market for the business venture, and collect any relevant primary and secondary data that would support such a venture. At this point, the definition of the problem may be “Why are cat owners not buying our new cat toy subscription service?”
Additionally, during this first step we would want to investigate our target population for research. This is similar to a target market, as it is the group that comprises the population of interest for the study. In order to have a successful research outcome, the researcher should start with an understanding of the problem in the current situational environment.
Develop the Research Plan
Step two is to develop the research plan. What type of research is necessary to meet the established objectives of the first step? How will this data be collected? Additionally, what is the time frame of the research and budget to consider? If you must have information in the next week, a different plan would be implemented than in a situation where several months were allowed. These are issues that a researcher should address in order to meet the needs identified.
Research is often classified as coming from one of two types of data: primary and secondary. Primary data is unique information that is collected by the specific researcher with the current project in mind. This type of research doesn’t currently exist until it is pulled together for the project. Examples of primary data collection include survey, observation, experiment, or focus group data that is gathered for the current project.
Secondary data is any research that was completed for another purpose but can be used to help inform the research process. Secondary data comes in many forms and includes census data, journal articles, previously collected survey or focus group data of related topics, and compiled company data. Secondary data may be internal, such as the company’s sales records for a previous quarter, or external, such as an industry report of all related product sales. Syndicated data , a type of external secondary data, is available through subscription services and is utilized by many marketers. As you can see in Table 6.1 , primary and secondary data features are often opposite—the positive aspects of primary data are the negative side of secondary data.
There are four research types that can be used: exploratory, descriptive, experimental, and ethnographic research designs (see Figure 6.4 ). Each type has specific formats of data that can be collected. Qualitative research can be shared through words, descriptions, and open-ended comments. Qualitative data gives context but cannot be reduced to a statistic. Qualitative data examples are categorical and include case studies, diary accounts, interviews, focus groups, and open-ended surveys. By comparison, quantitative data is data that can be reduced to number of responses. The number of responses to each answer on a multiple-choice question is quantitative data. Quantitative data is numerical and includes things like age, income, group size, and height.
Exploratory research is usually used when additional general information in desired about a topic. When in the initial steps of a new project, understanding the landscape is essential, so exploratory research helps the researcher to learn more about the general nature of the industry. Exploratory research can be collected through focus groups, interviews, and review of secondary data. When examining an exploratory research design, the best use is when your company hopes to collect data that is generally qualitative in nature. 7
For instance, if a company is considering a new service for registered users but is not quite sure how well the new service will be received or wants to gain clarity of exactly how customers may use a future service, the company can host a focus group. Focus groups and interviews will be examined later in the chapter. The insights collected during the focus group can assist the company when designing the service, help to inform promotional campaign options, and verify that the service is going to be a viable option for the company.
Descriptive research design takes a bigger step into collection of data through primary research complemented by secondary data. Descriptive research helps explain the market situation and define an “opinion, attitude, or behavior” of a group of consumers, employees, or other interested groups. 8 The most common method of deploying a descriptive research design is through the use of a survey. Several types of surveys will be defined later in this chapter. Descriptive data is quantitative in nature, meaning the data can be distilled into a statistic, such as in a table or chart.
Again, descriptive data is helpful in explaining the current situation. In the opening example of LEGO , the company wanted to describe the situation regarding children’s use of its product. In order to gather a large group of opinions, a survey was created. The data that was collected through this survey allowed the company to measure the existing perceptions of parents so that alterations could be made to future plans for the company.
Experimental research , also known as causal research , helps to define a cause-and-effect relationship between two or more factors. This type of research goes beyond a correlation to determine which feature caused the reaction. Researchers generally use some type of experimental design to determine a causal relationship. An example is A/B testing, a situation where one group of research participants, group A, is exposed to one treatment and then compared to the group B participants, who experience a different situation. An example might be showing two different television commercials to a panel of consumers and then measuring the difference in perception of the product. Another example would be to have two separate packaging options available in different markets. This research would answer the question “Does one design sell better than the other?” Comparing that to the sales in each market would be part of a causal research study. 9
The final method of collecting data is through an ethnographic design. Ethnographic research is conducted in the field by watching people interact in their natural environment. For marketing research, ethnographic designs help to identify how a product is used, what actions are included in a selection, or how the consumer interacts with the product. 10
Examples of ethnographic research would be to observe how a consumer uses a particular product, such as baking soda. Although many people buy baking soda, its uses are vast. So are they using it as a refrigerator deodorizer, a toothpaste, to polish a belt buckle, or to use in baking a cake?
Select the Data Collection Method
Data collection is the systematic gathering of information that addresses the identified problem. What is the best method to do that? Picking the right method of collecting data requires that the researcher understand the target population and the design picked in the previous step. There is no perfect method; each method has both advantages and disadvantages, so it’s essential that the researcher understand the target population of the research and the research objectives in order to pick the best option.
Sometimes the data desired is best collected by watching the actions of consumers. For instance, how many cars pass a specific billboard in a day? What website led a potential customer to the company’s website? When are consumers most likely to use the snack vending machines at work? What time of day has the highest traffic on a social media post? What is the most streamed television program this week? Observational research is the collecting of data based on actions taken by those observed. Many data observations do not require the researched individuals to participate in the data collection effort to be highly valuable. Some observation requires an individual to watch and record the activities of the target population through personal observations .
Unobtrusive observation happens when those being observed aren’t aware that they are being watched. An example of an unobtrusive observation would be to watch how shoppers interact with a new stuffed animal display by using a one-way mirror. Marketers can identify which products were handled more often while also determining which were ignored.
Other methods can use technology to collect the data instead. Instances of mechanical observation include the use of vehicle recorders, which count the number of vehicles that pass a specific location. Computers can also assess the number of shoppers who enter a store, the most popular entry point for train station commuters, or the peak time for cars to park in a parking garage.
When you want to get a more in-depth response from research participants, one method is to complete a one-on-one interview . One-on-one interviews allow the researcher to ask specific questions that match the respondent’s unique perspective as well as follow-up questions that piggyback on responses already completed. An interview allows the researcher to have a deeper understanding of the needs of the respondent, which is another strength of this type of data collection. The downside of personal interviews it that a discussion can be very time-consuming and results in only one respondent’s answers. Therefore, in order to get a large sample of respondents, the interview method may not be the most efficient method.
Taking the benefits of an interview and applying them to a small group of people is the design of a focus group . A focus group is a small number of people, usually 8 to 12, who meet the sample requirements. These individuals together are asked a series of questions where they are encouraged to build upon each other’s responses, either by agreeing or disagreeing with the other group members. Focus groups are similar to interviews in that they allow the researcher, through a moderator, to get more detailed information from a small group of potential customers (see Figure 6.5 ).
Link to Learning
Focus groups.
Focus groups are a common method for gathering insights into consumer thinking and habits. Companies will use this information to develop or shift their initiatives. The best way to understand a focus group is to watch a few examples or explanations. TED-Ed has this video that explains how focus groups work.
You might be asking when it is best to use a focus group or a survey. Learn the differences, the pros and cons of each, and the specific types of questions you ask in both situations in this article .
Preparing for a focus group is critical to success. It requires knowing the material and questions while also managing the group of people. Watch this video to learn more about how to prepare for a focus group and the types of things to be aware of.
One of the benefits of a focus group over individual interviews is that synergy can be generated when a participant builds on another’s ideas. Additionally, for the same amount of time, a researcher can hear from multiple respondents instead of just one. 11 Of course, as with every method of data collection, there are downsides to a focus group as well. Focus groups have the potential to be overwhelmed by one or two aggressive personalities, and the format can discourage more reserved individuals from speaking up. Finally, like interviews, the responses in a focus group are qualitative in nature and are difficult to distill into an easy statistic or two.
Combining a variety of questions on one instrument is called a survey or questionnaire . Collecting primary data is commonly done through surveys due to their versatility. A survey allows the researcher to ask the same set of questions of a large group of respondents. Response rates of surveys are calculated by dividing the number of surveys completed by the total number attempted. Surveys are flexible and can collect a variety of quantitative and qualitative data. Questions can include simplified yes or no questions, select all that apply, questions that are on a scale, or a variety of open-ended types of questions. There are four types of surveys (see Table 6.2 ) we will cover, each with strengths and weaknesses defined.
Let’s start off with mailed surveys —surveys that are sent to potential respondents through a mail service. Mailed surveys used to be more commonly used due to the ability to reach every household. In some instances, a mailed survey is still the best way to collect data. For example, every 10 years the United States conducts a census of its population (see Figure 6.6 ). The first step in that data collection is to send every household a survey through the US Postal Service (USPS). The benefit is that respondents can complete and return the survey at their convenience. The downside of mailed surveys are expense and timeliness of responses. A mailed survey requires postage, both when it is sent to the recipient and when it is returned. That, along with the cost of printing, paper, and both sending and return envelopes, adds up quickly. Additionally, physically mailing surveys takes time. One method of reducing cost is to send with bulk-rate postage, but that slows down the delivery of the survey. Also, because of the convenience to the respondent, completed surveys may be returned several weeks after being sent. Finally, some mailed survey data must be manually entered into the analysis software, which can cause delays or issues due to entry errors.
Phone surveys are completed during a phone conversation with the respondent. Although the traditional phone survey requires a data collector to talk with the participant, current technology allows for computer-assisted voice surveys or surveys to be completed by asking the respondent to push a specific button for each potential answer. Phone surveys are time intensive but allow the respondent to ask questions and the surveyor to request additional information or clarification on a question if warranted. Phone surveys require the respondent to complete the survey simultaneously with the collector, which is a limitation as there are restrictions for when phone calls are allowed. According to Telephone Consumer Protection Act , approved by Congress in 1991, no calls can be made prior to 8:00 a.m. or after 9:00 p.m. in the recipient’s time zone. 12 Many restrictions are outlined in this original legislation and have been added to since due to ever-changing technology.
In-person surveys are when the respondent and data collector are physically in the same location. In-person surveys allow the respondent to share specific information, ask questions of the surveyor, and follow up on previous answers. Surveys collected through this method can take place in a variety of ways: through door-to-door collection, in a public location, or at a person’s workplace. Although in-person surveys are time intensive and require more labor to collect data than some other methods, in some cases it’s the best way to collect the required data. In-person surveys conducted through a door-to-door method is the follow-up used for the census if respondents do not complete the mailed survey. One of the downsides of in-person surveys is the reluctance of potential respondents to stop their current activity and answer questions. Furthermore, people may not feel comfortable sharing private or personal information during a face-to-face conversation.
Electronic surveys are sent or collected through digital means and is an opportunity that can be added to any of the above methods as well as some new delivery options. Surveys can be sent through email, and respondents can either reply to the email or open a hyperlink to an online survey (see Figure 6.7 ). Additionally, a letter can be mailed that asks members of the survey sample to log in to a website rather than to return a mailed response. Many marketers now use links, QR codes, or electronic devices to easily connect to a survey. Digitally collected data has the benefit of being less time intensive and is often a more economical way to gather and input responses than more manual methods. A survey that could take months to collect through the mail can be completed within a week through digital means.
Design the Sample
Although you might want to include every possible person who matches your target market in your research, it’s often not a feasible option, nor is it of value. If you did decide to include everyone, you would be completing a census of the population. Getting everyone to participate would be time-consuming and highly expensive, so instead marketers use a sample , whereby a portion of the whole is included in the research. It’s similar to the samples you might receive at the grocery store or ice cream shop; it isn’t a full serving, but it does give you a good taste of what the whole would be like.
So how do you know who should be included in the sample? Researchers identify parameters for their studies, called sample frames . A sample frame for one study may be college students who live on campus; for another study, it may be retired people in Dallas, Texas, or small-business owners who have fewer than 10 employees. The individual entities within the sampling frame would be considered a sampling unit . A sampling unit is each individual respondent that would be considered as matching the sample frame established by the research. If a researcher wants businesses to participate in a study, then businesses would be the sampling unit in that case.
The number of sampling units included in the research is the sample size . Many calculations can be conducted to indicate what the correct size of the sample should be. Issues to consider are the size of the population, the confidence level that the data represents the entire population, the ease of accessing the units in the frame, and the budget allocated for the research.
There are two main categories of samples: probability and nonprobability (see Figure 6.8 ). Probability samples are those in which every member of the sample has an identified likelihood of being selected. Several probability sample methods can be utilized. One probability sampling technique is called a simple random sample , where not only does every person have an identified likelihood of being selected to be in the sample, but every person also has an equal chance of exclusion. An example of a simple random sample would be to put the names of all members of a group into a hat and simply draw out a specific number to be included. You could say a raffle would be a good example of a simple random sample.
Another probability sample type is a stratified random sample , where the population is divided into groups by category and then a random sample of each category is selected to participate. For instance, if you were conducting a study of college students from your school and wanted to make sure you had all grade levels included, you might take the names of all students and split them into different groups by grade level—freshman, sophomore, junior, and senior. Then, from those categories, you would draw names out of each of the pools, or strata.
A nonprobability sample is a situation in which each potential member of the sample has an unknown likelihood of being selected in the sample. Research findings that are from a nonprobability sample cannot be applied beyond the sample. Several examples of nonprobability sampling are available to researchers and include two that we will look at more closely: convenience sampling and judgment sampling.
The first nonprobability sampling technique is a convenience sample . Just like it sounds, a convenience sample is when the researcher finds a group through a nonscientific method by picking potential research participants in a convenient manner. An example might be to ask other students in a class you are taking to complete a survey that you are doing for a class assignment or passing out surveys at a basketball game or theater performance.
A judgment sample is a type of nonprobability sample that allows the researcher to determine if they believe the individual meets the criteria set for the sample frame to complete the research. For instance, you may be interested in researching mothers, so you sit outside a toy store and ask an individual who is carrying a baby to participate.
Collect the Data
Now that all the plans have been established, the instrument has been created, and the group of participants has been identified, it is time to start collecting data. As explained earlier in this chapter, data collection is the process of gathering information from a variety of sources that will satisfy the research objectives defined in step one. Data collection can be as simple as sending out an email with a survey link enclosed or as complex as an experiment with hundreds of consumers. The method of collection directly influences the length of this process. Conducting personal interviews or completing an experiment, as previously mentioned, can add weeks or months to the research process, whereas sending out an electronic survey may allow a researcher to collect the necessary data in a few days. 13
Analyze and Interpret the Data
Once the data has been collected, the process of analyzing it may begin. Data analysis is the distillation of the information into a more understandable and actionable format. The analysis itself can take many forms, from the use of basic statistics to a more comprehensive data visualization process. First, let’s discuss some basic statistics that can be used to represent data.
The first is the mean of quantitative data. A mean is often defined as the arithmetic average of values. The formula is:
A common use of the mean calculation is with exam scores. Say, for example, you have earned the following scores on your marketing exams: 72, 85, 68, and 77. To find the mean, you would add up the four scores for a total of 302. Then, in order to generate a mean, that number needs to be divided by the number of exam scores included, which is 4. The mean would be 302 divided by 4, for a mean test score of 75.5. Understanding the mean can help to determine, with one number, the weight of a particular value.
Another commonly used statistic is median. The median is often referred to as the middle number. To generate a median, all the numeric answers are placed in order, and the middle number is the median. Median is a common statistic when identifying the income level of a specific geographic region. 14 For instance, the median household income for Albuquerque, New Mexico, between 2015 and 2019 was $52,911. 15 In this case, there are just as many people with an income above the amount as there are below.
Mode is another statistic that is used to represent data of all types, as it can be used with quantitative or qualitative data and represents the most frequent answer. Eye color, hair color, and vehicle color can all be presented with a mode statistic. Additionally, some researchers expand on the concept of mode and present the frequency of all responses, not just identifying the most common response. Data such as this can easily be presented in a frequency graph, 16 such as the one in Figure 6.9 .
Additionally, researchers use other analyses to represent the data rather than to present the entirety of each response. For example, maybe the relationship between two values is important to understand. In this case, the researcher may share the data as a cross tabulation (see Figure 6.10 ). Below is the same data as above regarding social media use cross tabulated with gender—as you can see, the data is more descriptive when you can distinguish between the gender identifiers and how much time is spent per day on social media.
Not all data can be presented in a graphical format due to the nature of the information. Sometimes with qualitative methods of data collection, the responses cannot be distilled into a simple statistic or graph. In that case, the use of quotations, otherwise known as verbatims , can be used. These are direct statements presented by the respondents. Often you will see a verbatim statement when reading a movie or book review. The critic’s statements are used in part or in whole to represent their feelings about the newly released item.
Infographics
As they say, a picture is worth a thousand words. For this reason, research results are often shown in a graphical format in which data can be taken in quickly, called an infographic .
Check out this infographic on what components make for a good infographic. As you can see, a good infographic needs four components: data, design, a story, and the ability to share it with others. Without all four pieces, it is not as valuable a resource as it could be. The ultimate infographic is represented as the intersection of all four.
Infographics are particularly advantageous online. Refer to this infographic on why they are beneficial to use online .
Prepare the Research Report
The marketing research process concludes by sharing the generated data and makes recommendations for future actions. What starts as simple data must be interpreted into an analysis. All information gathered should be conveyed in order to make decisions for future marketing actions. One item that is often part of the final step is to discuss areas that may have been missed with the current project or any area of further study identified while completing it. Without the final step of the marketing research project, the first six steps are without value. It is only after the information is shared, through a formal presentation or report, that those recommendations can be implemented and improvements made. The first six steps are used to generate information, while the last is to initiate action. During this last step is also when an evaluation of the process is conducted. If this research were to be completed again, how would we do it differently? Did the right questions get answered with the survey questions posed to the respondents? Follow-up on some of these key questions can lead to additional research, a different study, or further analysis of data collected.
Methods of Quantifying Marketing Research
One of the ways of sharing information gained through marketing research is to quantify the research . Quantifying the research means to take a variety of data and compile into a quantity that is more easily understood. This is a simple process if you want to know how many people attended a basketball game, but if you want to quantify the number of students who made a positive comment on a questionnaire, it can be a little more complicated. Researchers have a variety of methods to collect and then share these different scores. Below are some of the most common types used in business.
Is a customer aware of a product, brand, or company? What is meant by awareness? Awareness in the context of marketing research is when a consumer is familiar with the product, brand, or company. It does not assume that the consumer has tried the product or has purchased it. Consumers are just aware. That is a measure that many businesses find valuable. There are several ways to measure awareness. For instance, the first type of awareness is unaided awareness . This type of awareness is when no prompts for a product, brand, or company are given. If you were collecting information on fast-food restaurants, you might ask a respondent to list all the fast-food restaurants that serve a chicken sandwich. Aided awareness would be providing a list of products, brands, or companies and the respondent selects from the list. For instance, if you give a respondent a list of fast-food restaurants and ask them to mark all the locations with a chicken sandwich, you are collecting data through an aided method. Collecting these answers helps a company determine how the business location compares to those of its competitors. 17
Customer Satisfaction (CSAT)
Have you ever been asked to complete a survey at the end of a purchase? Many businesses complete research on buying, returning, or other customer service processes. A customer satisfaction score , also known as CSAT, is a measure of how satisfied customers are with the product, brand, or service. A CSAT score is usually on a scale of 0 to 100 percent. 18 But what constitutes a “good” CSAT score? Although what is identified as good can vary by industry, normally anything in the range from 75 to 85 would be considered good. Of course, a number higher than 85 would be considered exceptional. 19
Customer Acquisition Cost (CAC) and Customer Effort Score (CES)
Other metrics often used are a customer acquisition cost (CAC) and customer effort score (CES). How much does it cost a company to gain customers? That’s the purpose of calculating the customer acquisition cost. To calculate the customer acquisition cost , a company would need to total all expenses that were accrued to gain new customers. This would include any advertising, public relations, social media postings, etc. When a total cost is determined, it is divided by the number of new customers gained through this campaign.
The final score to discuss is the customer effort score , also known as a CES. The CES is a “survey used to measure the ease of service experience with an organization.” 20 Companies that are easy to work with have a better CES than a company that is notorious for being difficult. An example would be to ask a consumer about the ease of making a purchase online by incorporating a one-question survey after a purchase is confirmed. If a number of responses come back negative or slightly negative, the company will realize that it needs to investigate and develop a more user-friendly process.
Knowledge Check
It’s time to check your knowledge on the concepts presented in this section. Refer to the Answer Key at the end of the book for feedback.
- Defining the problem
- Developing the research plan
- Selecting a data collection method
- Designing the sample
- you are able to send it to all households in an area
- it is inexpensive
- responses are automatically loaded into the software
- the data comes in quickly
- Primary data
- Secondary data
- Secondary and primary data
- Professional data
- It shows how respondents answered two variables in relation to each other and can help determine patterns by different groups of respondents.
- By presenting the data in the form of a picture, the information is easier for the reader to understand.
- It is an easy way to see how often one answer is selected by the respondents.
- This analysis can used to present interview or focus group data.
This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.
Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.
Access for free at https://openstax.org/books/principles-marketing/pages/1-unit-introduction
- Authors: Dr. Maria Gomez Albrecht, Dr. Mark Green, Linda Hoffman
- Publisher/website: OpenStax
- Book title: Principles of Marketing
- Publication date: Jan 25, 2023
- Location: Houston, Texas
- Book URL: https://openstax.org/books/principles-marketing/pages/1-unit-introduction
- Section URL: https://openstax.org/books/principles-marketing/pages/6-3-steps-in-a-successful-marketing-research-plan
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- How we work
- PhD Research
- Research Paper Marketing
How to Write a Marketing Research Paper: A Comprehensive Overview
Research paper on marketing: definition.
A marketing research paper is a fairly large work that requires students to collect data on different aspects of the field. Typically, students undertaking their undergrad or postgrad studies, particularly those studying in management, are the ones who commonly write this type of paper.
A research paper on marketing combines qualitative and quantitative analysis to understand various targets and markets better. The research quality and findings are always evaluated by peer review. It makes potential objections and counterarguments an integral part of the paper.
This type of paper is a widely used method of sharing progress with the academic community. So, even if you do not plan to pursue a job in the field but aim for a career in academic research, learning to write such a type of paper is crucial. And that is exactly what we can assist you with!
Steps to Writing Marketing Research Papers
Not sure how to start or what to put in your research paper marketing? Do not worry! To give you a better sense of the process, we have listed the key steps below.
Step 1: Pick a good topic
The first step in writing almost any academic paper is to choose a topic that aligns with your interests. If you are unsure about your interests, a good idea is to explore the available options on the web. Next, write down at least 10 marketing research paper topics that you think fit. Lastly, narrow them down to an ideal option.
Step 2: Prepare a plan
Every research work requires a robust plan. That’s why, after you select a topic, the next step is to develop a solid research plan. Your strategy should detail each phase of the investigation, whether it is experimental or not. Once done, take the time to understand the design and type of study at this stage. If you need professional help, consider using a PhD research proposal writing service.
Step 3: Gather materials
Research papers differ significantly from essays and dissertations. You can’t simply express your opinions on the paper. Instead, you have to gather accurate and valid data from reliable sources. During the data collection stage, it is also crucial to cross-check it to ensure the data is factual and accurate. Also, use both quantitative (o-data) and qualitative (x-data) information.
Step 4: Analyze data
Just because you gathered data from various sources does not guarantee it is reliable. Some data may be irrelevant or inaccurate. So, the crucial next step is a thorough analysis. Some of the techniques you can use at this stage of your PhD marketing research process include:
- Factor analysis.
- Text analysis.
- Benchmarking.
Step 5: Writing and editing
Suppose you have completed all the preceding steps. The final step is to commence writing. In your digital marketing research paper, ensure meticulous citation of all data and proper structure:
- Title page.
- Thesis statement.
- Introduction.
- Conclusion.
- References.
Finish it before the deadline to allow time for a quality review. If you spot any errors in your paper, address them promptly.
If you aim for high grades, make sure not to skip any of the above steps. Each step is important and contributes to an effective paper.
Top 20 Marketing Research Paper Topics to Consider
To make topic selection easier for you, we have hand-picked 20 compelling marketing topics for research paper. Feel free to review our list and choose the one that best aligns with your interests. Also, make sure you can write a solid thesis on it.
- Impact of augmented reality on user experiences.
- Consumer purchase decision and the influence of e-marketing.
- Impact of implicit and explicit consumer knowledge on buying behavior.
- Integration of IoT and smart devices for automated customer service.
- Relationship between brand awareness and repeat purchases.
- Technologies to improve online decision-making processes.
- Role of ICT in supply chain management.
- Conventional business marketing techniques.
- Importance of Instagram Reels in new product promotion.
- Assessing the ROI of commonly used digital strategies.
- Benefits of smartphones in understanding customer thinking.
- Loyalty programs as effective tools.
- Impact of impulsive buying behavior on businesses.
- Pros and cons of SEO in digital marketing.
- Effective methods for user retention.
- Importance of product labels in capturing user attention.
- Effectiveness of Black Friday as a sales driver.
- In-depth analysis of Facebook’s application in the field.
- Relationship between influencer marketing and lifestyle branding.
- Application of Progressive Web Apps (PWAs) in the field.
If you are still struggling, try to look for more topics for marketing research papers on the web. Another option is to consult your supervisor. Remember, trending topics change as fast as strategies do. So, dedicate enough time to the groundwork, and you will write a perfect paper!
- FREE topic suggestion
- 100% original research
- Dedicated experts only
Ultimate Tips for Doing PhD Marketing Research
Writing a PhD-level paper requires a thorough approach. Here are some tips to guide you through the process:
Choose a specific niche that aligns with your interests. Make sure the selected topic has the potential to contribute to the existing knowledge.
Conduct an in-depth review of relevant literature. These are the key steps:
- Understand the current state of things.
- Identify gaps.
- Recognize key theories.
Develop a strong research question. It should be focused and capable of contributing new insights to the field.
Create a detailed proposal. It should outline the following:
- Your objectives.
- Research questions.
- Methodology.
- Potential contributions.
Ensure it aligns with the standards of your institution. For those looking to enhance their project management skills, exploring a PhD project management online program can provide valuable insights and tools for managing research effectively.
Choose the most suitable methodology. Whether quantitative, qualitative, or a mix of both, ensure it fits your objectives.
Clearly outline how you’ll collect data. This may involve the following:
- Interviews.
- Case studies.
- Experiments.
- A combination of methods.
Employ appropriate data analysis techniques. Clearly interpret your findings and relate them to your research questions. Be prepared to discuss the implications of your results.
Seek feedback from your supervisor. Regular meetings will help you receive guidance and stay on track.
When in doubt, always consult a style guide or request a marketing research paper example from a librarian. Also, you can ask your supervisor for help. If still in doubt, consider receiving professional PhD research help from qualified experts of our writing service. Individual approach, reasonable prices, and flawless work tailored to your needs are guaranteed!
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