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- Descriptive Research | Definition, Types, Methods & Examples
Descriptive Research | Definition, Types, Methods & Examples
Published on May 15, 2019 by Shona McCombes . Revised on June 22, 2023.
Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when and how questions , but not why questions.
A descriptive research design can use a wide variety of research methods to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.
Table of contents
When to use a descriptive research design, descriptive research methods, other interesting articles.
Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.
It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when and where it happens.
Descriptive research question examples
- How has the Amsterdam housing market changed over the past 20 years?
- Do customers of company X prefer product X or product Y?
- What are the main genetic, behavioural and morphological differences between European wildcats and domestic cats?
- What are the most popular online news sources among under-18s?
- How prevalent is disease A in population B?
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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .
Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. Common uses of surveys include:
- Describing the demographics of a country or region
- Gauging public opinion on political and social topics
- Evaluating satisfaction with a company’s products or an organization’s services
Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social and market researchers to understand how people act in real-life situations.
Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models or theories, it’s necessary to observe and systematically describe the subject under investigation.
A case study can be used to describe the characteristics of a specific subject (such as a person, group, event or organization). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.
Rather than aiming to describe generalizable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Normal distribution
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Ecological validity
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
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Descriptive Research: Definition, Characteristics, Methods + Examples
Suppose an apparel brand wants to understand the fashion purchasing trends among New York’s buyers, then it must conduct a demographic survey of the specific region, gather population data, and then conduct descriptive research on this demographic segment. The study will then uncover details on “what is the purchasing pattern of New York buyers,” but will not cover any investigative information about “ why ” the patterns exist. Because for the apparel brand trying to break into this market, understanding the nature of their market is the study’s main goal. Let’s talk about it.
LEARN ABOUT: Behavioral Research
What is descriptive research?
Characteristics of descriptive research, applications of descriptive research with examples, advantages of descriptive research, descriptive research methods, examples of descriptive research.
Descriptive research is a research method describing the characteristics of the population or phenomenon studied. This descriptive methodology focuses more on the “what” of the research subject than the “why” of the research subject.
The method primarily focuses on describing the nature of a demographic segment without focusing on “why” a particular phenomenon occurs. In other words, it “describes” the research subject without covering “why” it happens.
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The term descriptive research then refers to research questions, design of the study, and data analysis conducted on that topic. We call it an observational research method because none of the research study variables are influenced in any capacity.
LEARN ABOUT: Descriptive Analysis
Some distinctive characteristics of descriptive research are:
- Quantitative research: It is a quantitative research method that attempts to collect quantifiable information for statistical analysis of the population sample. It is a popular market research tool that allows us to collect and describe the demographic segment’s nature.
- Uncontrolled variables: In it, none of the variables are influenced in any way. This uses observational methods to conduct the research. Hence, the nature of the variables or their behavior is not in the hands of the researcher.
- Cross-sectional studies: It is generally a cross-sectional study where different sections belonging to the same group are studied.
- The basis for further research: Researchers further research the data collected and analyzed from descriptive research using different research techniques. The data can also help point towards the types of research methods used for the subsequent research.
LEARN ABOUT: Action Research
A descriptive research method can be used in multiple ways and for various reasons. Before getting into any survey , though, the survey goals and survey design are crucial. Despite following these steps, there is no way to know if one will meet the research outcome. How to use descriptive research? To understand the end objective of research goals, below are some ways organizations currently use descriptive research today:
- Define respondent characteristics: The aim of using close-ended questions is to draw concrete conclusions about the respondents. This could be the need to derive patterns, traits, and behaviors of the respondents. It could also be to understand from a respondent, their attitude, or opinion about the phenomenon. For example, understanding from millenials the hours per week they spend on browsing the internet. All this information helps the organization researching to make informed business decisions.
- Measure data trends: Researchers measure data trends over time with a descriptive research design’s statistical capabilities. Consider if an apparel company researches different demographics like age groups from 24-35 and 36-45 on a new range launch of autumn wear. If one of those groups doesn’t take too well to the new launch, it provides insight into what clothes are like and what is not. The brand drops the clothes and apparel that customers don’t like.
- Conduct comparisons: Organizations also use a descriptive research design to understand how different groups respond to a specific product or service. For example, an apparel brand creates a survey asking general questions that measure the brand’s image. The same study also asks demographic questions like age, income, gender, geographical location, geographic segmentation , etc. This consumer research helps the organization understand what aspects of the brand appeal to the population and what aspects do not. It also helps make product or marketing fixes or even create a new product line to cater to high growth potential groups.
LEARN ABOUT: Research Process Steps
- Validate existing conditions: Researchers widely use descriptive research to help ascertain the research object’s prevailing conditions and underlying patterns. Due to the non-invasive research method and the use of quantitative observation and some aspects of qualitative observation , researchers observe each variable and conduct an in-depth analysis . Researchers also use it to validate any existing conditions that may be prevalent in a population.
- Conduct research at different times: The analysis can be conducted at different periods to ascertain any similarities or differences. This also allows any number of variables to be evaluated. For verification, studies on prevailing conditions can also be repeated to draw trends.
LEARN ABOUT: market research trends
Some of the significant advantages of descriptive research are:
- Data collection: A researcher can conduct descriptive research using specific methods like observational method, case study method, and survey method. Between these three, all primary data collection methods are covered, which provides a lot of information. This can be used for future research or even developing a hypothesis of your research object.
- Varied: Since the data collected is qualitative and quantitative, it gives a holistic understanding of a research topic. The information is varied, diverse, and thorough.
- Natural environment: Descriptive research allows for the research to be conducted in the respondent’s natural environment, which ensures that high-quality and honest data is collected.
- Quick to perform and cheap: As the sample size is generally large in descriptive research, the data collection is quick to conduct and is inexpensive.
LEARN ABOUT: Best Data Collection Tools
There are three distinctive methods to conduct descriptive research. They are:
- Observational method
The observational method is the most effective method to conduct this research, and researchers make use of both quantitative and qualitative observations.
A quantitative observation is the objective collection of data primarily focused on numbers and values. It suggests “associated with, of or depicted in terms of a quantity.” Results of quantitative observation are derived using statistical and numerical analysis methods. It implies observation of any entity associated with a numeric value such as age, shape, weight, volume, scale, etc. For example, the researcher can track if current customers will refer the brand using a simple Net Promoter Score question .
Qualitative observation doesn’t involve measurements or numbers but instead just monitoring characteristics. In this case, the researcher observes the respondents from a distance. Since the respondents are in a comfortable environment, the characteristics observed are natural and effective. In a descriptive research design, the researcher can choose to be either a complete observer, an observer as a participant, a participant as an observer, or a full participant. For example, in a supermarket, a researcher can from afar monitor and track the customers’ selection and purchasing trends. This offers a more in-depth insight into the purchasing experience of the customer.
LEARN ABOUT: Qualitative Interview
- Case study method
Case studies involve in-depth research and study of individuals or groups. Case studies lead to a hypothesis and widen a further scope of studying a phenomenon. However, case studies should not be used to determine cause and effect as they can’t make accurate predictions because there could be a bias on the researcher’s part. The other reason why case studies are not a reliable way of conducting descriptive research is that there could be an atypical respondent in the survey. Describing them leads to weak generalizations and moving away from external validity.
LEARN ABOUT: Causal Research
- Survey research
In survey research, respondents answer through surveys or questionnaires or polls . They are a popular market research tool to collect feedback from respondents. A study to gather useful data should have the right survey questions. It should be a balanced mix of open-ended questions and close ended-questions . The survey method can be conducted online or offline, making it the go-to option for descriptive research where the sample size is enormous.
LEARN ABOUT: 12 Best Tools for Researchers
Some examples of descriptive research are:
- A specialty food group launching a new range of barbecue rubs would like to understand what flavors of rubs are favored by different people. To understand the preferred flavor palette, they conduct this type of research study using various methods like observational methods in supermarkets. By also surveying while collecting in-depth demographic information, offers insights about the preference of different markets. This can also help tailor make the rubs and spreads to various preferred meats in that demographic. Conducting this type of research helps the organization tweak their business model and amplify marketing in core markets.
- Another example of where this research can be used is if a school district wishes to evaluate teachers’ attitudes about using technology in the classroom. By conducting surveys and observing their comfortableness using technology through observational methods, the researcher can gauge what they can help understand if a full-fledged implementation can face an issue. This also helps in understanding if the students are impacted in any way with this change.
Some other research problems and research questions that can lead to descriptive research are:
- Market researchers want to observe the habits of consumers.
- A company wants to evaluate the morale of its staff.
- A school district wants to understand if students will access online lessons rather than textbooks.
- To understand if its wellness questionnaire programs enhance the overall health of the employees.
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The Four Types of Research Design — Everything You Need to Know
Updated: May 11, 2023
Published: January 18, 2023
When you conduct research, you need to have a clear idea of what you want to achieve and how to accomplish it. A good research design enables you to collect accurate and reliable data to draw valid conclusions.
In this blog post, we'll outline the key features of the four common types of research design with real-life examples from UnderArmor, Carmex, and more. Then, you can easily choose the right approach for your project.
Table of Contents
What is research design?
The four types of research design, research design examples.
Research design is the process of planning and executing a study to answer specific questions. This process allows you to test hypotheses in the business or scientific fields.
Research design involves choosing the right methodology, selecting the most appropriate data collection methods, and devising a plan (or framework) for analyzing the data. In short, a good research design helps us to structure our research.
Marketers use different types of research design when conducting research .
There are four common types of research design — descriptive, correlational, experimental, and diagnostic designs. Let’s take a look at each in more detail.
Researchers use different designs to accomplish different research objectives. Here, we'll discuss how to choose the right type, the benefits of each, and use cases.
Research can also be classified as quantitative or qualitative at a higher level. Some experiments exhibit both qualitative and quantitative characteristics.
An experimental design is used when the researcher wants to examine how variables interact with each other. The researcher manipulates one variable (the independent variable) and observes the effect on another variable (the dependent variable).
In other words, the researcher wants to test a causal relationship between two or more variables.
In marketing, an example of experimental research would be comparing the effects of a television commercial versus an online advertisement conducted in a controlled environment (e.g. a lab). The objective of the research is to test which advertisement gets more attention among people of different age groups, gender, etc.
Another example is a study of the effect of music on productivity. A researcher assigns participants to one of two groups — those who listen to music while working and those who don't — and measure their productivity.
The main benefit of an experimental design is that it allows the researcher to draw causal relationships between variables.
One limitation: This research requires a great deal of control over the environment and participants, making it difficult to replicate in the real world. In addition, it’s quite costly.
Best for: Testing a cause-and-effect relationship (i.e., the effect of an independent variable on a dependent variable).
A correlational design examines the relationship between two or more variables without intervening in the process.
Correlational design allows the analyst to observe natural relationships between variables. This results in data being more reflective of real-world situations.
For example, marketers can use correlational design to examine the relationship between brand loyalty and customer satisfaction. In particular, the researcher would look for patterns or trends in the data to see if there is a relationship between these two entities.
Similarly, you can study the relationship between physical activity and mental health. The analyst here would ask participants to complete surveys about their physical activity levels and mental health status. Data would show how the two variables are related.
Best for: Understanding the extent to which two or more variables are associated with each other in the real world.
Descriptive research refers to a systematic process of observing and describing what a subject does without influencing them.
Methods include surveys, interviews, case studies, and observations. Descriptive research aims to gather an in-depth understanding of a phenomenon and answers when/what/where.
SaaS companies use descriptive design to understand how customers interact with specific features. Findings can be used to spot patterns and roadblocks.
For instance, product managers can use screen recordings by Hotjar to observe in-app user behavior. This way, the team can precisely understand what is happening at a certain stage of the user journey and act accordingly.
Brand24, a social listening tool, tripled its sign-up conversion rate from 2.56% to 7.42%, thanks to locating friction points in the sign-up form through screen recordings.
Carma Laboratories worked with research company MMR to measure customers’ reactions to the lip-care company’s packaging and product . The goal was to find the cause of low sales for a recently launched line extension in Europe.
The team moderated a live, online focus group. Participants were shown w product samples, while AI and NLP natural language processing identified key themes in customer feedback.
This helped uncover key reasons for poor performance and guided changes in packaging.
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What Is Descriptive Marketing Research?
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Conclusive research is a structured data collection technique that provides detailed, factual information that's useful in decision-making. Descriptive marketing research is a form of conclusive research used to describe both the composition of a group in such terms as income, gender, age and education and the characteristics of group members in regards to both current and future behavior. Examples of a group include a collection of customers, sales people, organizations or market segments. Surveys, case studies, job analyses, document analyses, and correlational studies are each a form of descriptive marketing research.
A survey gathers information from a sample to construct quantitative statistics that describe the size and attributes of a larger population. For example, descriptive statistics can be used to calculate the percentage of a population that supports the policies of a particular president. To conduct a survey, the researcher questions a sample of respondents from within a population. The survey or questionnaire may be a document to be completed by the person who is surveyed, an online questionnaire, a telephone interview or a face-to-face interview.
A case study draws conclusions from data collected regarding real-life events for decision-support purposes. For example, a case study may focus on a particular group behavior, a business process or a school's performance. To conduct a case study, detailed information regarding a participant or group is collected and summarized. This information is not intended to generate conclusions about a larger population, but rather to describe the event, individual or group that's the subject of the study.
A job analysis describes and classifies jobs. For example, a job analysis may provide detailed information regarding the major tasks of a tax accountant, the environment in which he works and the physical, emotional and cognitive capacities required for an individual to be successful in the role. Whereas job analyses are used by corporations in hiring, training and evaluating employees, governments rely on the job descriptions to monitor workforce activity. In turn, psychologists focus on job characteristics to analyze issues of workplace behavior.
Document analysis requires the collection and review of documents that are specific to a particular group in terms of the characteristics of the individual group members or their behavior. For example, government statistics provide information regarding the income, gender, age and education of the U. S. population. Document analysis requires that documents be selected according to predefined criteria that reflect the issues regarding which a researcher seeks evidence. Written agreements, website data, meeting agendas, reports and other publications can be used for this purpose.
Correlational studies allow a researcher to identify an association between two variables as well as the degree to which the association holds true across multiple populations. For example, a study may focus on a man's age and his expenditures on sports equipment. A positive correlation suggests that a man will spend more on sports equipment as he grows older whereas a negative correlation suggests that he spends less with age.
- "A Concise Guide to Market Research: The Process, Data, and Methods Using IBM SPSS Statistics"; Sarstedt et al. ; 2011
- "Marketing Research: Methodological Foundations": Churchill et al.
- "Essentials of Marketing Research"; Zikmund et al.; 2007
- "Survey methodology"; Groves, et al.; 2009
- "International Marketing Research"; Craig, et al.; 2005
Billie Nordmeyer works as a consultant advising small businesses and Fortune 500 companies on performance improvement initiatives, as well as SAP software selection and implementation. During her career, she has published business and technology-based articles and texts. Nordmeyer holds a Bachelor of Science in accounting, a Master of Arts in international management and a Master of Business Administration in finance.
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What Is Descriptive Analytics? 5 Examples
- 09 Nov 2021
Data analytics is a valuable tool for businesses aiming to increase revenue, improve products, and retain customers. According to research by global management consulting firm McKinsey & Company, companies that use data analytics are 23 times more likely to outperform competitors in terms of new customer acquisition than non-data-driven companies. They were also nine times more likely to surpass them in measures of customer loyalty and 19 times more likely to achieve above-average profitability.
Data analytics can be broken into four key types :
- Descriptive, which answers the question, “What happened?”
- Diagnostic , which answers the question, “Why did this happen?”
- Predictive , which answers the question, “What might happen in the future?”
- Prescriptive , which answers the question, “What should we do next?”
Each type of data analysis can help you reach specific goals and be used in tandem to create a full picture of data that informs your organization’s strategy formulation and decision-making.
Descriptive analytics can be leveraged on its own or act as a foundation for the other three analytics types. If you’re new to the field of business analytics, descriptive analytics is an accessible and rewarding place to start.
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What Is Descriptive Analytics?
Descriptive analytics is the process of using current and historical data to identify trends and relationships. It’s sometimes called the simplest form of data analysis because it describes trends and relationships but doesn’t dig deeper.
Descriptive analytics is relatively accessible and likely something your organization uses daily. Basic statistical software, such as Microsoft Excel or data visualization tools , such as Google Charts and Tableau, can help parse data, identify trends and relationships between variables, and visually display information.
Descriptive analytics is especially useful for communicating change over time and uses trends as a springboard for further analysis to drive decision-making .
Here are five examples of descriptive analytics in action to apply at your organization.
Related: 5 Business Analytics Skills for Professionals
5 Examples of Descriptive Analytics
1. traffic and engagement reports.
One example of descriptive analytics is reporting. If your organization tracks engagement in the form of social media analytics or web traffic, you’re already using descriptive analytics.
These reports are created by taking raw data—generated when users interact with your website, advertisements, or social media content—and using it to compare current metrics to historical metrics and visualize trends.
For example, you may be responsible for reporting on which media channels drive the most traffic to the product page of your company’s website. Using descriptive analytics, you can analyze the page’s traffic data to determine the number of users from each source. You may decide to take it one step further and compare traffic source data to historical data from the same sources. This can enable you to update your team on movement; for instance, highlighting that traffic from paid advertisements increased 20 percent year over year.
The three other analytics types can then be used to determine why traffic from each source increased or decreased over time, if trends are predicted to continue, and what your team’s best course of action is moving forward.
2. Financial Statement Analysis
Another example of descriptive analytics that may be familiar to you is financial statement analysis. Financial statements are periodic reports that detail financial information about a business and, together, give a holistic view of a company’s financial health.
There are several types of financial statements, including the balance sheet , income statement , cash flow statement , and statement of shareholders’ equity. Each caters to a specific audience and conveys different information about a company’s finances.
Financial statement analysis can be done in three primary ways: vertical, horizontal, and ratio.
Vertical analysis involves reading a statement from top to bottom and comparing each item to those above and below it. This helps determine relationships between variables. For instance, if each line item is a percentage of the total, comparing them can provide insight into which are taking up larger and smaller percentages of the whole.
Horizontal analysis involves reading a statement from left to right and comparing each item to itself from a previous period. This type of analysis determines change over time.
Finally, ratio analysis involves comparing one section of a report to another based on their relationships to the whole. This directly compares items across periods, as well as your company’s ratios to the industry’s to gauge whether yours is over- or underperforming.
Each of these financial statement analysis methods are examples of descriptive analytics, as they provide information about trends and relationships between variables based on current and historical data.
3. Demand Trends
Descriptive analytics can also be used to identify trends in customer preference and behavior and make assumptions about the demand for specific products or services.
Streaming provider Netflix’s trend identification provides an excellent use case for descriptive analytics. Netflix’s team—which has a track record of being heavily data-driven—gathers data on users’ in-platform behavior. They analyze this data to determine which TV series and movies are trending at any given time and list trending titles in a section of the platform’s home screen.
Not only does this data allow Netflix users to see what’s popular—and thus, what they might enjoy watching—but it allows the Netflix team to know which types of media, themes, and actors are especially favored at a certain time. This can drive decision-making about future original content creation, contracts with existing production companies, marketing, and retargeting campaigns.
4. Aggregated Survey Results
Descriptive analytics is also useful in market research. When it comes time to glean insights from survey and focus group data, descriptive analytics can help identify relationships between variables and trends.
For instance, you may conduct a survey and identify that as respondents’ age increases, so does their likelihood to purchase your product. If you’ve conducted this survey multiple times over several years, descriptive analytics can tell you if this age-purchase correlation has always existed or if it was something that only occurred this year.
Insights like this can pave the way for diagnostic analytics to explain why certain factors are correlated. You can then leverage predictive and prescriptive analytics to plan future product improvements or marketing campaigns based on those trends.
Related: What Is Marketing Analytics?
5. Progress to Goals
Finally, descriptive analytics can be applied to track progress to goals. Reporting on progress toward key performance indicators (KPIs) can help your team understand if efforts are on track or if adjustments need to be made.
For example, if your organization aims to reach 500,000 monthly unique page views, you can use traffic data to communicate how you’re tracking toward it. Perhaps halfway through the month, you’re at 200,000 unique page views. This would be underperforming because you’d like to be halfway to your goal at that point—at 250,000 unique page views. This descriptive analysis of your team’s progress can allow further analysis to examine what can be done differently to improve traffic numbers and get back on track to hit your KPI.
Using Data to Identify Relationships and Trends
“Never before has so much data about so many different things been collected and stored every second of every day,” says Harvard Business School Professor Jan Hammond in the online course Business Analytics . “In this world of big data, data literacy —the ability to analyze, interpret, and even question data—is an increasingly valuable skill.”
Leveraging descriptive analytics to communicate change based on current and historical data and as a foundation for diagnostic, predictive, and prescriptive analytics has the potential to take you and your organization far.
Do you want to become a data-driven professional? Explore our eight-week Business Analytics course and our three-course Credential of Readiness (CORe) program to deepen your analytical skills and apply them to real-world business problems.
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Descriptive research questions: Definition, examples and designing methodology
- October 4, 2021
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Conducting thorough market research is all about framing the right questions that provide accurate answers to research questions. The two main categories of questions namely: Quantitative and Qualitative questions focus on differential aspects.
While quantitative research questions are based on numerical data that provides a substantial backing to the decision making process, qualitative research questions aim to derive insights based on textual responses. Both these questions are used based on their relevance and suitability to meet end objectives of the user.
One such useful quantitative question type are the descriptive research questions.
What is descriptive research?
Descriptive research questions aim to provide a description of the variable under consideration. It is one of the easiest and commonly used ways to quantify research variables.
Questions that begin with:
- How much: How much time does an average teenager spend on watching documentaries on OTT platforms?
Variable: time spent on watching documentaries
- How often: How often do you take an international family trip in a year?
Variable: International trips
- How likely: How likely is it for a person to purchase life insurance within the age group of 20-26?
Variable: Likelihood of purchasing a life insurance
Group: People within the age group of 20-26
- What percentage: What percentage of high school students exercise on a daily basis?
Variable: Daily Exercise
Group: High School Students
- How many: How many smartphone users make use of curated apps to manage daily tasks?
Variable: Usage of curated apps
Group: Smartphone users
- What proportion: What proportion of students prefer online education to offline education?
Variable: Educational format
- How regularly: How regularly does a woman engage or purchase from a cosmetic brand outlet as against e-commerce websites?
Variable: Purchasing Behaviour of cosmetics
- What is: What is the ratio of passengers indulging in train travel to travelling by flight?
Variable: Travelling medium
- What are: What are the influencing factors that impact the choice of purchasing a house in the UK?
Variable: Influencing factors
Group: UK property investors/ New buyers
Among other such phrases are all classified as descriptive questions. By gathering sufficient responses to such questions, end users are able to make intelligent decisions based on hard figures that help in gathering stakeholder confidence.
For example: What percentage of college students make use of e-libraries for their academic needs. In this example the variable under observation is usage of e-libraries and the group that is evaluated are the college going students.
By providing percentages, averages, sum, proportions and other such figures, descriptive research questions provide a complete view of the target groups responses with respect to that variable. The above example has restricted the usage of variables to one, but many researchers alternatively choose to incorporate multiple variables under a single head.
Why are descriptive research questions important?
Descriptive research questions are a systematic methodology that helps in understanding the what, where, when and how. Important variables can be rigidly defined using descriptive research, unlike qualitative research where the subjectivity in responses makes it relatively difficult to get a grasp on the overall picture. The multiple methods available allow for in-person as well as online research to be carried out based on whatever the need of the end user is.
The data provided by descriptive research assists comprehensive understanding by providing an in-depth view of the variable that is being studied.
Steps to conduct Cluster Sampling
These are the following steps used to perform single-stage cluster sampling:
- Decide on a target population and desired sample size.
- Divide the target population into clusters based on a specific criteria.
- Select clusters using methods of random selection while keeping in mind the desired sample size.
- Collect data from the final sample group.
Further steps may be taken using two-stage or multistage sampling to achieve desired sample size if it cannot be achieved through one-stage sampling.
Types of descriptive research questions?
Descriptive research questions has divisions based on multiple business applications:
Descriptive research questions can be centred around organizational market performance in terms of sales figures, competitive appeal, updated practices, market share analytics, concept studies and other data collection processes that intend to gather market know-how. Target market analysis can also be done using descriptive question types wherein organizations can precisely define their niche audience.
Consumer perceptions and ideas about what suits them best can be understood using descriptive question types. These studies are used to design curated products that meet target market requirements. Anything from products, services, offers, incentives, promotions and marketing, pricing, packaging, feedback mechanism can be put into perspective and gauged to extract material results.
While market performance looks at external variables, internal trends focus on departmental contributions, revenue generation, product specific demands, sales figures etc. This internal summary helps appraise performance within the organization and contrast it with external performance for benchmarking purposes.
How to frame descriptive research questions?
There is no rocket science behind framing the right question for your variable. It’s just a matter of figuring out what you want to assess and the numerical measure you’re looking for. The usage of descriptive questions in your study also comes with the condition of keeping the entire process concise and to the point.
To start off, figure out the variable that you wish to gauge and the target group that needs to be evaluated. This will determine the centre point of your research questions. Avoid providing vague descriptions and instead, try narrowing the details. Such a practice will direct the questioning to the exact audience you wish to examine without adding in unnecessary responses.
Choose the starting phrase that encompasses what you’re looking to measure. For example: If you’re looking to examine or separate a certain type of person from the entire target audience, phrases such as “what proportion” or “what percentage” can prove highly useful.
- Proceed from general to specific questions while making sure that you don’t lose focus of your target variable and audience.
- Avoid using ambiguous terminologies that are likely to confuse your respondents into misunderstanding questions as this can adversely affect the quality of your responses.
- Keep the questions simple and easy to understand in such a way that all targeted respondents are able to grasp the overall meaning equally.
- Avoid leading questions that skew the respondent into answering a certain way. Research is all about getting the information that you want in an authentic manner and such questions can sway the respondent into giving artificial responses.
Make sure that your answer choices are balanced. This is another bias that forces the respondent into altering their actual responses. Try to provide equal representation to all possible answers such that the probability of receiving each response is equally likely.
Lastly, look for variables of questions that you can club together without affecting the overall questioning process. However, it is often useful to bifurcate combined questions wherever you can, combining relevant questions together can provide useful information about existing relationships. This goes without saying that such clubbing must not act as a hindrance to the understanding of these variables as separate characteristics.
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6 Types of Research Design
By the end of this chapter, students must be able to:
- Explain the three types of research design used by marketers
- Understand the application of these designs
This chapter looks at the types of research designs that are utilized by marketers. A research design is an overall plan or structure for a research project. A research design will use different combinations of primary, secondary, qualitative, and quantitative data. Depending on the overall research questions, research designs in marketing may fall into one of the following three categories:
- Exploratory research design
- Descriptive research design
- Causal research design (experiments)
An exploratory research design is more informal and unstructured than the other two types of designs. Exploratory design is used to explore a situation, especially when the researcher is in unfamiliar territory. Most academic projects begin with exploratory research when researchers undertake desk research. Similarly, when marketers plan to venture into new markets, such as India, it is advisable to employ an exploratory research design. This could mean going through case studies, accessing published reports (i.e., secondary data) on the market, undertaking experience interviews with experts, and conducting focus groups – if needed. Exploratory design is useful in gaining background information and deciding about future research approaches. It may generate more questions, which need to be tackled with other research designs.
As the name suggests, descriptive research design is employed to describe the market or respondents’ characteristics. This type of research design generates quantitative information. Therefore, such a design would often involve surveys. Surveys are useful to measure the descriptive numbers relating to respondents’ age groups, income levels, expenditure patterns, and even attitudes. This can be done by employing relevant scales, such as, “On a scale of 1–5, how satisfied were you with this organisation’s service?”.
Physiological measurements, such as people’s involuntary responses (such as heart rate, skin changes, and eye movement) to marketing stimuli, such as an advertisement may also be categorised in descriptive research. While recording such information requires special instruments, it is nevertheless a type of descriptive information that can be useful for marketers.
Source: Meanthat and authentic data science 
Causal research design (also known as experimental research design) examines cause-and-effect relationships. A well-designed experiment is the best way of understanding how one variable (e.g., advertisement) may influence another variable (e.g., sale of a product). An experiment involves one or more independent variables (for example, price level, and product features) which are manipulated to determine how they may impact one or more dependent variables (such as customer preference or customer satisfaction). Independent variables can be ‘manipulated’ by the researcher while the dependent variables are variables that get influenced due to changes in the independent variables.
Experiments can be categorised as field experiments or lab experiments . When an experiment is conducted in a natural setting – such as in a retail store – it is referred to as a field experiment . On the other hand, experiments conducted in a researcher’s office or a university classroom are lab experiments. A lab experiment may be undertaken to measure the impact of an ad on the subject’s attitude.
A field experiment is often seen as providing researchers with reliable results as it is undertaken in the actual environment. However, it is not easy to implement a field experiment. It is difficult to control other factors – in the real environment – which may also impact the final results. Moreover, running an experiment requires expertise in the design of the experiment. It may also require financial and time resources. As an example, Mcdonald’s may wish to see if a drop in the price of its cheeseburger results in greater sales. The fast-food restaurant may drop the price in one locality, such as Fairfield. It may also tediously measure the sales around the time of a price reduction. While interpreting the results, it would need to be assured that any changes in sales figures can be attributed to the price change – and not to other environmental factors such as an increase in prices at Hungry Jacks or an overall increase in customers due to a local football match. Thus, controlling such extraneous variables – that is, all those variables besides the identified independent variables which may also affect the dependent variable.
One of the popular experimental research designs is the ‘Before-After’ Testing design . As the name suggests, it measures the dependent variable, before and after a change in the independent variable. An example will help clarify the concept:
Experimental Group (R) O 1 X O 2
Control Group O 3 O 4
Experimental Effect (E) = (O 2 – O 1 ) – (O 4 – O 3 )
R = random allocation of subjects to experimental or control group
O = observation
X = treatment or manipulation of the independent variable, such as a change in price
Explanation of the above example:
- Subjects or research participants are randomly allocated to one of the groups
- The experimental group is the one in which the independent variable (e.g., price) is manipulated (e.g., reduced)
- The control group is not exposed to any changes in the independent variable
- Measurements (i.e., O) for the dependent variable (e.g., sales) – for both groups – are taken before the change in price (X) – PRE-TEST
- Measurements (i..e., O) for the dependent variable are taken after the change in price – POST-TEST
- The difference between O 2 and O 1 demonstrates the change in the dependent variable due to the change in X (independent variable)
- The difference between O 4 and O 3 demonstrate any change in the dependent variable due to factors other than X
- Therefore, the difference between the two groups (O 2 – O 1 ) – (O 4 – O 3 ) demonstrates the true effect of the independent variable as it removes any influence of extraneous variables.
- Meanthat and authentic data science 2016, 1.3 Exploratory, descriptive and explanatory nature of research , 17 March, online video, viewed 3 March 2022, <https://www.youtube.com/watch?v=FlBFdEgrTBM>. ↵
Customer Insights Copyright © 2022 by Aila Khan is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
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Home » Descriptive Research Design – Types, Methods and Examples
Descriptive Research Design – Types, Methods and Examples
Table of Contents
Descriptive Research Design
Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied.
Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions about future outcomes. Instead, it focuses on providing a detailed and accurate representation of the data collected, which can be useful for generating hypotheses, exploring trends, and identifying patterns in the data.
Types of Descriptive Research Design
Types of Descriptive Research Design are as follows:
This involves collecting data at a single point in time from a sample or population to describe their characteristics or behaviors. For example, a researcher may conduct a cross-sectional study to investigate the prevalence of certain health conditions among a population, or to describe the attitudes and beliefs of a particular group.
This involves collecting data over an extended period of time, often through repeated observations or surveys of the same group or population. Longitudinal studies can be used to track changes in attitudes, behaviors, or outcomes over time, or to investigate the effects of interventions or treatments.
This involves an in-depth examination of a single individual, group, or situation to gain a detailed understanding of its characteristics or dynamics. Case studies are often used in psychology, sociology, and business to explore complex phenomena or to generate hypotheses for further research.
This involves collecting data from a sample or population through standardized questionnaires or interviews. Surveys can be used to describe attitudes, opinions, behaviors, or demographic characteristics of a group, and can be conducted in person, by phone, or online.
This involves observing and documenting the behavior or interactions of individuals or groups in a natural or controlled setting. Observational studies can be used to describe social, cultural, or environmental phenomena, or to investigate the effects of interventions or treatments.
This involves examining the relationships between two or more variables to describe their patterns or associations. Correlational studies can be used to identify potential causal relationships or to explore the strength and direction of relationships between variables.
Data Analysis Methods
Descriptive research design data analysis methods depend on the type of data collected and the research question being addressed. Here are some common methods of data analysis for descriptive research:
This method involves analyzing data to summarize and describe the key features of a sample or population. Descriptive statistics can include measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., range, standard deviation).
This method involves analyzing data by creating a table that shows the frequency of two or more variables together. Cross-tabulation can help identify patterns or relationships between variables.
This method involves analyzing qualitative data (e.g., text, images, audio) to identify themes, patterns, or trends. Content analysis can be used to describe the characteristics of a sample or population, or to identify factors that influence attitudes or behaviors.
This method involves analyzing qualitative data by assigning codes to segments of data based on their meaning or content. Qualitative coding can be used to identify common themes, patterns, or categories within the data.
This method involves creating graphs or charts to represent data visually. Visualization can help identify patterns or relationships between variables and make it easier to communicate findings to others.
This method involves comparing data across different groups or time periods to identify similarities and differences. Comparative analysis can help describe changes in attitudes or behaviors over time or differences between subgroups within a population.
Applications of Descriptive Research Design
Descriptive research design has numerous applications in various fields. Some of the common applications of descriptive research design are:
- Market research: Descriptive research design is widely used in market research to understand consumer preferences, behavior, and attitudes. This helps companies to develop new products and services, improve marketing strategies, and increase customer satisfaction.
- Health research: Descriptive research design is used in health research to describe the prevalence and distribution of a disease or health condition in a population. This helps healthcare providers to develop prevention and treatment strategies.
- Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs. This helps educators to improve teaching methods and develop effective educational programs.
- Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs. This helps researchers to understand social behavior and develop effective policies.
- Public opinion research: Descriptive research design is used in public opinion research to understand the opinions and attitudes of the general public on various issues. This helps policymakers to develop effective policies that are aligned with public opinion.
- Environmental research: Descriptive research design is used in environmental research to describe the environmental conditions of a particular region or ecosystem. This helps policymakers and environmentalists to develop effective conservation and preservation strategies.
Descriptive Research Design Examples
Here are some real-time examples of descriptive research designs:
- A restaurant chain wants to understand the demographics and attitudes of its customers. They conduct a survey asking customers about their age, gender, income, frequency of visits, favorite menu items, and overall satisfaction. The survey data is analyzed using descriptive statistics and cross-tabulation to describe the characteristics of their customer base.
- A medical researcher wants to describe the prevalence and risk factors of a particular disease in a population. They conduct a cross-sectional study in which they collect data from a sample of individuals using a standardized questionnaire. The data is analyzed using descriptive statistics and cross-tabulation to identify patterns in the prevalence and risk factors of the disease.
- An education researcher wants to describe the learning outcomes of students in a particular school district. They collect test scores from a representative sample of students in the district and use descriptive statistics to calculate the mean, median, and standard deviation of the scores. They also create visualizations such as histograms and box plots to show the distribution of scores.
- A marketing team wants to understand the attitudes and behaviors of consumers towards a new product. They conduct a series of focus groups and use qualitative coding to identify common themes and patterns in the data. They also create visualizations such as word clouds to show the most frequently mentioned topics.
- An environmental scientist wants to describe the biodiversity of a particular ecosystem. They conduct an observational study in which they collect data on the species and abundance of plants and animals in the ecosystem. The data is analyzed using descriptive statistics to describe the diversity and richness of the ecosystem.
How to Conduct Descriptive Research Design
To conduct a descriptive research design, you can follow these general steps:
- Define your research question: Clearly define the research question or problem that you want to address. Your research question should be specific and focused to guide your data collection and analysis.
- Choose your research method: Select the most appropriate research method for your research question. As discussed earlier, common research methods for descriptive research include surveys, case studies, observational studies, cross-sectional studies, and longitudinal studies.
- Design your study: Plan the details of your study, including the sampling strategy, data collection methods, and data analysis plan. Determine the sample size and sampling method, decide on the data collection tools (such as questionnaires, interviews, or observations), and outline your data analysis plan.
- Collect data: Collect data from your sample or population using the data collection tools you have chosen. Ensure that you follow ethical guidelines for research and obtain informed consent from participants.
- Analyze data: Use appropriate statistical or qualitative analysis methods to analyze your data. As discussed earlier, common data analysis methods for descriptive research include descriptive statistics, cross-tabulation, content analysis, qualitative coding, visualization, and comparative analysis.
- I nterpret results: Interpret your findings in light of your research question and objectives. Identify patterns, trends, and relationships in the data, and describe the characteristics of your sample or population.
- Draw conclusions and report results: Draw conclusions based on your analysis and interpretation of the data. Report your results in a clear and concise manner, using appropriate tables, graphs, or figures to present your findings. Ensure that your report follows accepted research standards and guidelines.
When to Use Descriptive Research Design
Descriptive research design is used in situations where the researcher wants to describe a population or phenomenon in detail. It is used to gather information about the current status or condition of a group or phenomenon without making any causal inferences. Descriptive research design is useful in the following situations:
- Exploratory research: Descriptive research design is often used in exploratory research to gain an initial understanding of a phenomenon or population.
- Identifying trends: Descriptive research design can be used to identify trends or patterns in a population, such as changes in consumer behavior or attitudes over time.
- Market research: Descriptive research design is commonly used in market research to understand consumer preferences, behavior, and attitudes.
- Health research: Descriptive research design is useful in health research to describe the prevalence and distribution of a disease or health condition in a population.
- Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs.
- Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs.
Purpose of Descriptive Research Design
The main purpose of descriptive research design is to describe and measure the characteristics of a population or phenomenon in a systematic and objective manner. It involves collecting data that describe the current status or condition of the population or phenomenon of interest, without manipulating or altering any variables.
The purpose of descriptive research design can be summarized as follows:
- To provide an accurate description of a population or phenomenon: Descriptive research design aims to provide a comprehensive and accurate description of a population or phenomenon of interest. This can help researchers to develop a better understanding of the characteristics of the population or phenomenon.
- To identify trends and patterns: Descriptive research design can help researchers to identify trends and patterns in the data, such as changes in behavior or attitudes over time. This can be useful for making predictions and developing strategies.
- To generate hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
- To establish a baseline: Descriptive research design can establish a baseline or starting point for future research. This can be useful for comparing data from different time periods or populations.
Characteristics of Descriptive Research Design
Descriptive research design has several key characteristics that distinguish it from other research designs. Some of the main characteristics of descriptive research design are:
- Objective : Descriptive research design is objective in nature, which means that it focuses on collecting factual and accurate data without any personal bias. The researcher aims to report the data objectively without any personal interpretation.
- Non-experimental: Descriptive research design is non-experimental, which means that the researcher does not manipulate any variables. The researcher simply observes and records the behavior or characteristics of the population or phenomenon of interest.
- Quantitative : Descriptive research design is quantitative in nature, which means that it involves collecting numerical data that can be analyzed using statistical techniques. This helps to provide a more precise and accurate description of the population or phenomenon.
- Cross-sectional: Descriptive research design is often cross-sectional, which means that the data is collected at a single point in time. This can be useful for understanding the current state of the population or phenomenon, but it may not provide information about changes over time.
- Large sample size: Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
- Systematic and structured: Descriptive research design involves a systematic and structured approach to data collection, which helps to ensure that the data is accurate and reliable. This involves using standardized procedures for data collection, such as surveys, questionnaires, or observation checklists.
Advantages of Descriptive Research Design
Descriptive research design has several advantages that make it a popular choice for researchers. Some of the main advantages of descriptive research design are:
- Provides an accurate description: Descriptive research design is focused on accurately describing the characteristics of a population or phenomenon. This can help researchers to develop a better understanding of the subject of interest.
- Easy to conduct: Descriptive research design is relatively easy to conduct and requires minimal resources compared to other research designs. It can be conducted quickly and efficiently, and data can be collected through surveys, questionnaires, or observations.
- Useful for generating hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
- Large sample size : Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
- Can be used to monitor changes : Descriptive research design can be used to monitor changes over time in a population or phenomenon. This can be useful for identifying trends and patterns, and for making predictions about future behavior or attitudes.
- Can be used in a variety of fields : Descriptive research design can be used in a variety of fields, including social sciences, healthcare, business, and education.
Limitation of Descriptive Research Design
Descriptive research design also has some limitations that researchers should consider before using this design. Some of the main limitations of descriptive research design are:
- Cannot establish cause and effect: Descriptive research design cannot establish cause and effect relationships between variables. It only provides a description of the characteristics of the population or phenomenon of interest.
- Limited generalizability: The results of a descriptive study may not be generalizable to other populations or situations. This is because descriptive research design often involves a specific sample or situation, which may not be representative of the broader population.
- Potential for bias: Descriptive research design can be subject to bias, particularly if the researcher is not objective in their data collection or interpretation. This can lead to inaccurate or incomplete descriptions of the population or phenomenon of interest.
- Limited depth: Descriptive research design may provide a superficial description of the population or phenomenon of interest. It does not delve into the underlying causes or mechanisms behind the observed behavior or characteristics.
- Limited utility for theory development: Descriptive research design may not be useful for developing theories about the relationship between variables. It only provides a description of the variables themselves.
- Relies on self-report data: Descriptive research design often relies on self-report data, such as surveys or questionnaires. This type of data may be subject to biases, such as social desirability bias or recall bias.
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3 Types of Market Research: Which Does Your Business Need?
Companies use exploratory research methods to uncover facts and opinions regarding a particular subject. Exploratory research seeks to highlight the main points of a situation, thus, enabling researchers to more clearly understand an issue or concern (i.e., gain insight). It seldom provides enough data to make any conclusive market decisions, but rather forms a foundation on which companies can start to build better research objectives for subsequent studies. Oftentimes, exploratory research makes use of qualitative measures like consumer and expert interviews and focus groups, as well as secondary research materials including books, syndicated reports and trade journals or magazines.
Descriptive research seeks to concretely describe a situation in ways that will allow companies to direct decisions and monitor progress. It is quantitative by nature, using a standardized format with close-ended questions to collect information that can be statistically measured and analyzed. Surveys, questionnaires and certain types of experiments are all types of descriptive research methodologies that can provide the necessary data to formulate conclusions and take action and/or measure changing attitudes and behaviors over time. Specifically, researchers might use descriptive research techniques to gather demographic information on consumers, evaluate a product’s market potential or monitor a target group’s opinions and actions. Using the information collected, they are able to draw conclusions and/or make correlations concerning the market at large.
When companies want to establish a cause and effect relationship among two or more variables, they use causal research methods. Similar to descriptive research, causal research is quantifiable. But instead of merely reporting on a situation, causal research methods use experiments to predict and test theories about a company’s products and marketing efforts. Researchers manipulate chosen variables with the hope that a certain effect will result. For instance, a business might devise an experiment to see what would happen to sales if their product’s packaging was changed or if their advertisements were altered in some way. Although causal research can be informative, basing any action on its results should be tempered by conclusions drawn from other types of research, as it is very hard to isolate and verify any one variable’s ability to cause any given effect.
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Descriptive Research – Characteristics, Methods, Examples, Advantages
June 12, 2023 By Hitesh Bhasin Filed Under: Marketing
Descriptive research is a type of research that provides an in-depth description of the phenomenon or population under study. Descriptive research is neither in the category of qualitative research nor in the class of quantitative research, but it uses the features of both types of research.
Descriptive research emphasizes what kind of question to be asked in the research study. The descriptive research provides the answer to the “what” part of a research and does not answer the questions why/when/how.
Descriptive research is a suitable choice if you want to learn about the trends of a particular field or the frequency of an event. This research is also an appropriate option when you do not have any information about the research problem, and primary information gathering is required to establish a hypothesis. In this article, you will learn about the characteristics, methods, examples, advantages, and disadvantages of descriptive research.
Table of Contents
Characteristics of Descriptive Research
1. Statistical Outcome
Descriptive research answers the “what” questions in statistical form. As the output is in emphasizes form, it is easy for the researcher to deduce results and implement them. Because of this characteristic of descriptive research, it is popularly used in market researches.
2. The basis for secondary research
The results obtained from descriptive research is in statistical form. Therefore, it can also be used as secondary data for similar research problems. In addition to this, different research techniques can be applied to the data for the analysis of various factors of the research problem.
3. Unrestrained variable
Random variables are used in descriptive research. Therefore, it is not in the hands of researchers to control the variables of descriptive research. In descriptive research, the natural behavior of participants is observed to learn about them.
4. Natural setting
Descriptive researches are usually conducted in natural settings. For example, you can distribute questionnaires of surveys among random people, or in an observational method, you can observe the behavior of people in a particular environment. For example, if you want to learn about the buying behavior of people, then you can go to a supermarket and observe people.
5. Cross-sectional study
In descriptive research, different aspects of a single group are studied and compared to gain a different insight into the group.
Methods of Descriptive Research
There are three methods of descriptive research
1. Case study method
The case study method refers to the in-depth and detailed study of the subject, person or case, which is to be studied. A case study involves a formal research method to carry out the research. Using the outcomes obtained from the case study research hypothesis can be established, which can be used to expand the horizons of research.
However, case study research is not suitable to determine the relationship between cause and effect as it does not provide accurate results. Moreover, the outcome of the case study method is relevant to that particular case and similar cases and can’t be generalised. Case studies are focused on interesting and unusual cases that are complex and challenging and provide additional information about a particular case.
For example, in a medical case study, researchers study a rare medical case to get more knowledge about the medical case. Similarly, case study methods are used by scientists to learn about unusual phenomenon.
2. Observational Method
Observational research is a type of non- experimental research . Observational research can be defined as a type of research where the researcher observes the ongoing behaviors of the subject being studied. Observational research is majorly used in the marketing and social science fields. In observational research, the researcher finds the actions of subjects under study in their natural setting.
Observational methods are different from experimental research methods because, in experimental research methods, an artificial environment is created for the subjects under study. An observational study can be of two types, naturalistic observation or participant observation. A naturalistic observation study means the study of subjects when they are at their natural behavior.
In participant observation, people being observed in the research study are aware of the observation. They are asked to take part in the observation study. Observational research methods are suitable for studying the behavior of subjects under the study. However, this research is incapable of providing information about the actual cause of the behaviours of subjects under study.
3. Survey Research
Survey research is one of the most popular and easy forms of research to obtain information or to collect data. A questionnaire is prepared to contain questions related to the research problem either on paper or in any digital format. These questionnaires are distributed among random people in the hope of getting their accurate opinion.
The survey research method is popularly used in University researches and business researches. Survey research is also called primary research and can be used with other research methods to obtain accurate outcomes.
Moreover, data collected from survey research can be used as secondary research data by other researchers.
Examples of descriptive research
Let us take the case of a sports clothing brand . The sports brand wants to set up a business in selling gym gears. They want to know about in detail about the kind of clothes people want to wear while exercising in the gym. To get in-depth information about the preference of people, they adopted two descriptive methods one is naturalistic observation, and the other is a survey.
In naturalistic observation, they started observing people at different gyms and silently learn about the kind of clothes they prefer to wear. To know more about their choices, they conducted a survey and distributed questionnaire containing questions like How much would they like to spend on a sports track pant?
What color of gym gear do they prefer to wear while working out? Answer to these questions will provide them the knowledge that was difficult to obtain through observing.
A restaurant planned to start to serve continental food to its customers. Therefore, to learn about the choice of people in flavor and taste, they an observation method to learn about what kind of spreads, herbs, and meat preferred by people.
Here is a video by Marketing91 on Descriptive Research.
Advantages of descriptive research
- Data collected from descriptive research is helpful in important decision-making because the data is obtained from a large population. Because using the descriptive survey method, statistical information can be obtained, and analysis of that data can be made to deduce desired results.
- A variety of data can be obtained using different descriptive research methods like surveys, observation, and vase study. These three research methods provide different type of data which can be used to analysis for a research problem. For example, using the case study research method can be used to develop a hypothesis about a research problem.
- One advantage of descriptive research over other research methods is that it is cheap and quick to conduct descriptive research. You don’t require having a great place dedicated only to research. Descriptive research like observation research can be held in natural settings, and you can distribute surveys to people online or get them answered by random people at your business place or other public places.
- Descriptive research provides both quantitative and qualitative data. The variety of data provides a holistic understanding of the research problem.
- Descriptive research can be conducted in natural settings. There is no need to have a designated space to conduct research using any of the descriptive research methods.
Disadvantages of descriptive research
- Descriptive methods only provide the answers for “what” and do not answer the why and how. Therefore, descriptive research methods are not suitable for determining cause and effect relationships.
- Descriptive methods mainly depend on the responses of people. There are chances that people might not act their true selves if they know they are being observed. In the case of the survey method, there are chances that some people don’t answer the questions honestly, which makes the output of the descriptive research study invalid. Because the results derived from this type of data will not be accurate.
- Another problem associated with descriptive research is the halo effect. A researcher might get partial if he knows the participant personally. The observations made in this way would be considered invalid.
- In descriptive research methods, participants are picked randomly. The randomness of the sample can’t represent the whole population accurately.
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About Hitesh Bhasin
Hi, I am an MBA and the CEO of Marketing91. I am a Digital Marketer and an Entrepreneur with 12 Years of experience in Business and Marketing. Business is my passion and i have established myself in multiple industries with a focus on sustainable growth. You will generally find me online at the Marketing91 Academy .
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What is Descriptive Research in Marketing?
Descriptive research is a type of research that focuses on describing the characteristics and behaviors of a particular group or population. In marketing, descriptive research is used to gather information about consumers, their preferences, and their behaviors. This type of research is often used to identify trends, patterns, and relationships between different variables. In this article, we will explore the basics of descriptive research in marketing and its importance for businesses.
What is the Purpose of Descriptive Research in Marketing?
The purpose of descriptive research in marketing is to provide businesses with a clear understanding of their target audience. This type of research helps businesses to identify the needs and preferences of their customers, which can be used to develop better products and services. Descriptive research can also help businesses to identify the strengths and weaknesses of their competitors, which can be used to gain a competitive advantage.
One of the key benefits of descriptive research is that it provides businesses with a large amount of data that can be used to make informed decisions. This data can be used to identify patterns and trends, which can help businesses to develop marketing strategies that are more effective. For example, if a business identifies that its target audience is primarily made up of young adults, it can develop marketing campaigns that are tailored to this demographic.
Types of Descriptive Research
There are several types of descriptive research that can be used in marketing. Some of the most common types include:
Surveys are one of the most common types of descriptive research in marketing. They involve asking a large number of people questions about their preferences, behaviors, and attitudes. Surveys can be conducted in a variety of ways, including online, by mail, or in person.
Observational studies involve observing people in their natural environment. This type of research can be used to gather information about consumer behaviors, such as how people shop for products or how they use certain products.
Case studies involve examining a particular group or individual in depth. This type of research can be used to gather information about consumer behaviors, preferences, and attitudes.
Benefits of Descriptive Research in Marketing
There are several benefits of descriptive research in marketing, including:
Identifying Market Trends
Descriptive research can help businesses to identify market trends, such as changes in consumer preferences or the emergence of new products and services. This information can be used to develop marketing strategies that are more effective.
Identifying Customer Needs
Descriptive research can help businesses to identify the needs and preferences of their customers. This information can be used to develop products and services that better meet the needs of consumers.
Identifying Competitor Strengths and Weaknesses
Descriptive research can help businesses to identify the strengths and weaknesses of their competitors. This information can be used to develop marketing strategies that are more effective.
Descriptive Research vs. Analytical Research
Descriptive research is often contrasted with analytical research. While descriptive research focuses on describing a particular group or population, analytical research focuses on analyzing the relationships between different variables. Analytical research is often used to test hypotheses and to identify cause-and-effect relationships.
When to Use Descriptive Research
Descriptive research is most useful when a business needs to gather information about a particular group or population. This type of research is often used to identify trends, patterns, and relationships between different variables.
When to Use Analytical Research
Analytical research is most useful when a business needs to test hypotheses or to identify cause-and-effect relationships. This type of research is often used to determine the effectiveness of marketing campaigns or to identify the factors that influence consumer behavior.
In conclusion, descriptive research is an important tool for businesses that want to better understand their target audience. This type of research can help businesses to identify market trends, customer needs, and competitor strengths and weaknesses. By using descriptive research, businesses can develop marketing strategies that are more effective and that are better tailored to the needs of their customers.
Frequently Asked Questions
Here are some frequently asked questions about descriptive research in marketing:
1. What is the purpose of descriptive research in marketing?
Descriptive research in marketing is used to describe the characteristics of a target market or population. It is used to gather information about consumers, such as their age, gender, income, buying habits, and preferences. The purpose of descriptive research is to provide a detailed picture of the target audience, which can help marketers develop more effective marketing strategies.
Descriptive research can also be used to track changes in consumer behavior over time. For example, a company might conduct a survey to determine how many people are using their product, how often they are using it, and what other products they are using in conjunction with it. This information can be used to identify trends and make adjustments to marketing strategies as needed.
2. What are some common methods used in descriptive research?
There are several methods used in descriptive research, including surveys, focus groups, and observational studies. Surveys are one of the most common methods, and they can be conducted in person, over the phone, or online. Focus groups involve bringing together a small group of people to discuss a particular topic or product. Observational studies involve observing people in their natural environment to gather information about their behavior.
Each method has its own strengths and weaknesses, and the choice of method will depend on the research question and the target audience. For example, surveys are often used to gather quantitative data, while focus groups are better suited for exploring attitudes and opinions in more depth.
3. How is descriptive research different from other types of research?
Descriptive research is often contrasted with exploratory and causal research. Exploratory research is used to generate ideas and hypotheses about a particular topic, while causal research is used to establish cause-and-effect relationships between variables. Descriptive research, on the other hand, is used to describe a target audience or population in detail.
Descriptive research is often used as a first step in the research process, as it can provide a foundation for further research. For example, if a descriptive study reveals that a certain demographic group is more likely to purchase a particular product, a causal study could be conducted to determine why this is the case.
4. What are some advantages of descriptive research?
Descriptive research has several advantages over other types of research. One advantage is that it allows researchers to gather a large amount of data in a relatively short amount of time. Surveys, for example, can be administered to a large number of people quickly and easily.
Another advantage of descriptive research is that it can provide a detailed picture of the target audience, which can help marketers develop more effective marketing strategies. Descriptive research can also be used to track changes in consumer behavior over time, which can help companies stay ahead of trends and make adjustments to their marketing strategies as needed.
5. What are some limitations of descriptive research?
Despite its advantages, descriptive research also has some limitations. One limitation is that it can be difficult to establish cause-and-effect relationships between variables. For example, a descriptive study might reveal that people who use a certain product are more likely to be satisfied with it, but it cannot determine whether using the product actually causes satisfaction.
Another limitation is that descriptive research relies on self-reported data, which can be biased or inaccurate. People may not always be truthful in their responses, or they may not remember certain details accurately. Finally, descriptive research is limited by the research question and the methods used, and it cannot provide answers to all research questions.
Descriptive Research Design I Marketing Research #1
While descriptive research is not always suitable for all marketing situations, it is a powerful tool that can provide valuable insights for marketers. It can help them to identify opportunities, predict trends, and make informed decisions about their marketing campaigns.
In today’s competitive business environment, the ability to collect and analyze data is more critical than ever. Descriptive research can help marketers to gain a deeper understanding of their customers and markets, which can lead to more effective marketing strategies. By using descriptive research, marketers can stay ahead of the curve and ensure their marketing efforts are delivering results.
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9 Key stages in your marketing research process
You can conduct your own marketing research. Follow these steps, add your own flair, knowledge and creativity, and you’ll have bespoke research to be proud of.
Marketing research is the term used to cover the concept, development, placement and evolution of your product or service, its growing customer base and its branding – starting with brand awareness , and progressing to (everyone hopes) brand equity . Like any research, it needs a robust process to be credible and useful.
Marketing research uses four essential key factors known as the ‘marketing mix’ , or the Four Ps of Marketing :
- Product (goods or service)
- Price ( how much the customer pays )
- Place (where the product is marketed)
- Promotion (such as advertising and PR)
These four factors need to work in harmony for a product or service to be successful in its marketplace.
The marketing research process – an overview
A typical marketing research process is as follows:
- Identify an issue, discuss alternatives and set out research objectives
- Develop a research program
- Choose a sample
- Gather information
- Gather data
- Organize and analyze information and data
- Present findings
- Make research-based decisions
- Take action based on insights
Step 1: Defining the marketing research problem
Defining a problem is the first step in the research process. In many ways, research starts with a problem facing management. This problem needs to be understood, the cause diagnosed, and solutions developed.
However, most management problems are not always easy to research, so they must first be translated into research problems. Once you approach the problem from a research angle, you can find a solution. For example, “sales are not growing” is a management problem, but translated into a research problem, it becomes “ why are sales not growing?” We can look at the expectations and experiences of several groups : potential customers, first-time buyers, and repeat purchasers. We can question whether the lack of sales is due to:
- Poor expectations that lead to a general lack of desire to buy, or
- Poor performance experience and a lack of desire to repurchase.
This, then, is the difference between a management problem and a research problem. Solving management problems focuses on actions: Do we advertise more? Do we change our advertising message? Do we change an under-performing product configuration? And if so, how?
Defining research problems, on the other hand, focus on the whys and hows, providing the insights you need to solve your management problem.
Step 2: Developing a research program: method of inquiry
The scientific method is the standard for investigation. It provides an opportunity for you to use existing knowledge as a starting point, and proceed impartially.
The scientific method includes the following steps:
- Define a problem
- Develop a hypothesis
- Make predictions based on the hypothesis
- Devise a test of the hypothesis
- Conduct the test
- Analyze the results
This terminology is similar to the stages in the research process. However, there are subtle differences in the way the steps are performed:
- the scientific research method is objective and fact-based, using quantitative research and impartial analysis
- the marketing research process can be subjective, using opinion and qualitative research, as well as personal judgment as you collect and analyze data
Step 3: Developing a research program: research method
As well as selecting a method of inquiry (objective or subjective), you must select a research method . There are two primary methodologies that can be used to answer any research question:
- Experimental research : gives you the advantage of controlling extraneous variables and manipulating one or more variables that influence the process being implemented.
- Non-experimental research : allows observation but not intervention – all you do is observe and report on your findings.
Step 4: Developing a research program: research design
Research design is a plan or framework for conducting marketing research and collecting data. It is defined as the specific methods and procedures you use to get the information you need.
There are three core types of marketing research designs: exploratory, descriptive, and causal . A thorough marketing research process incorporates elements of all of them.
Exploratory marketing research
This is a starting point for research. It’s used to reveal facts and opinions about a particular topic, and gain insight into the main points of an issue. Exploratory research is too much of a blunt instrument to base conclusive business decisions on, but it gives the foundation for more targeted study. You can use secondary research materials such as trade publications, books, journals and magazines and primary research using qualitative metrics, that can include open text surveys, interviews and focus groups.
Descriptive marketing research
This helps define the business problem or issue so that companies can make decisions, take action and monitor progress. Descriptive research is naturally quantitative – it needs to be measured and analyzed statistically , using more targeted surveys and questionnaires. You can use it to capture demographic information , evaluate a product or service for market, and monitor a target audience’s opinion and behaviors. Insights from descriptive research can inform conclusions about the market landscape and the product’s place in it.
Causal marketing research
This is useful to explore the cause and effect relationship between two or more variables. Like descriptive research , it uses quantitative methods, but it doesn’t merely report findings; it uses experiments to predict and test theories about a product or market. For example, researchers may change product packaging design or material, and measure what happens to sales as a result.
Step 5: Choose your sample
Your marketing research project will rarely examine an entire population. It’s more practical to use a sample - a smaller but accurate representation of the greater population. To design your sample, you’ll need to answer these questions:
- Which base population is the sample to be selected from? Once you’ve established who your relevant population is (your research design process will have revealed this), you have a base for your sample. This will allow you to make inferences about a larger population.
- What is the method (process) for sample selection? There are two methods of selecting a sample from a population:
1. Probability sampling : This relies on a random sampling of everyone within the larger population.
2. Non-probability sampling : This is based in part on the investigator’s judgment, and often uses convenience samples, or by other sampling methods that do not rely on probability.
- What is your sample size? This important step involves cost and accuracy decisions. Larger samples generally reduce sampling error and increase accuracy, but also increase costs. Find out your perfect sample size with our calculator .
Step 6: Gather data
Your research design will develop as you select techniques to use. There are many channels for collecting data, and it’s helpful to differentiate it into O-data (Operational) and X-data (Experience):
- O-data is your business’s hard numbers like costs, accounting, and sales. It tells you what has happened, but not why.
- X-data gives you insights into the thoughts and emotions of the people involved: employees, customers, brand advocates.
When you combine O-data with X-data, you’ll be able to build a more complete picture about success and failure - you’ll know why. Maybe you’ve seen a drop in sales (O-data) for a particular product. Maybe customer service was lacking, the product was out of stock, or advertisements weren’t impactful or different enough: X-data will reveal the reason why those sales dropped. So, while differentiating these two data sets is important, when they are combined, and work with each other, the insights become powerful.
With mobile technology, it has become easier than ever to collect data. Survey research has come a long way since market researchers conducted face-to-face, postal, or telephone surveys. You can run research through:
- Social media ( polls and listening )
Another way to collect data is by observation. Observing a customer’s or company’s past or present behavior can predict future purchasing decisions. Data collection techniques for predicting past behavior can include market segmentation , customer journey mapping and brand tracking .
Regardless of how you collect data, the process introduces another essential element to your research project: the importance of clear and constant communication .
And of course, to analyze information from survey or observation techniques, you must record your results . Gone are the days of spreadsheets. Feedback from surveys and listening channels can automatically feed into AI-powered analytics engines and produce results, in real-time, on dashboards.
Step 7: Analysis and interpretation
The words ‘ statistical analysis methods ’ aren’t usually guaranteed to set a room alight with excitement, but when you understand what they can do, the problems they can solve and the insights they can uncover, they seem a whole lot more compelling.
Statistical tests and data processing tools can reveal:
- Whether data trends you see are meaningful or are just chance results
- Your results in the context of other information you have
- Whether one thing affecting your business is more significant than others
- What your next research area should be
- Insights that lead to meaningful changes
There are several types of statistical analysis tools used for surveys. You should make sure that the ones you choose:
- Work on any platform - mobile, desktop, tablet etc.
- Integrate with your existing systems
- Are easy to use with user-friendly interfaces, straightforward menus, and automated data analysis
- Incorporate statistical analysis so you don’t just process and present your data, but refine it, and generate insights and predictions.
Here are some of the most common tools:
- Benchmarking : a way of taking outside factors into account so that you can adjust the parameters of your research. It ‘levels the playing field’ – so that your data and results are more meaningful in context. And gives you a more precise understanding of what’s happening.
- Regression analysis : this is used for working out the relationship between two (or more) variables. It is useful for identifying the precise impact of a change in an independent variable.
- T-test is used for comparing two data groups which have different mean values. For example, do women and men have different mean heights?
- Analysis of variance (ANOVA) Similar to the T-test, ANOVA is a way of testing the differences between three or more independent groups to see if they’re statistically significant.
- Cluster analysis : This organizes items into groups, or clusters, based on how closely associated they are.
- Factor analysis: This is a way of condensing many variables into just a few, so that your research data is less unwieldy to work with.
- Conjoint analysis : this will help you understand and predict why people make the choices they do. It asks people to make trade-offs when making decisions, just as they do in the real world, then analyzes the results to give the most popular outcome.
- Crosstab analysis : this is a quantitative market research tool used to analyze ‘categorical data’ - variables that are different and mutually exclusive, such as: ‘men’ and ‘women’, or ‘under 30’ and ‘over 30’.
- Text analysis and sentiment analysis : Analyzing human language and emotions is a rapidly-developing form of data processing, assigning positive, negative or neutral sentiment to customer messages and feedback.
Stats IQ can perform the most complicated statistical tests at the touch of a button using our online survey software , or data from other sources. Learn more about Stats iQ now .
Step 8: The marketing research results
Your marketing research process culminates in the research results. These should provide all the information the stakeholders and decision-makers need to understand the project.
The results will include:
- all your information
- a description of your research process
- the results
- recommended courses of action
They should also be presented in a form, language and graphics that are easy to understand, with a balance between completeness and conciseness, neither leaving important information out or allowing it to get so technical that it overwhelms the readers.
Traditionally, you would prepare two written reports:
- a technical report , discussing the methods, underlying assumptions and the detailed findings of the research project
- a summary report , that summarizes the research process and presents the findings and conclusions simply.
There are now more engaging ways to present your findings than the traditional PowerPoint presentations, graphs, and face-to-face reports:
- Live, interactive dashboards for sharing the most important information, as well as tracking a project in real time.
- Results-reports visualizations – tables or graphs with data visuals on a shareable slide deck
- Online presentation technology, such as Prezi
- Visual storytelling with infographics
- A single-page executive summary with key insights
- A single-page stat sheet with the top-line stats
You can also make these results shareable so that decision-makers have all the information at their fingertips.
Step 9 Turn your insights into action
Insights are one thing, but they’re worth very little unless they inform immediate, positive action. Here are a few examples of how you can do this:
- Stop customers leaving – negative sentiment among VIP customers gets picked up; the customer service team contacts the customers, resolves their issues, and avoids churn .
- Act on important employee concerns – you can set certain topics, such as safety, or diversity and inclusion to trigger an automated notification or Slack message to HR. They can rapidly act to rectify the issue.
- Address product issues – maybe deliveries are late, maybe too many products are faulty. When product feedback gets picked up through Smart Conversations, messages can be triggered to the delivery or product teams to jump on the problems immediately.
- Improve your marketing effectiveness - Understand how your marketing is being received by potential customers, so you can find ways to better meet their needs
- Grow your brand - Understand exactly what consumers are looking for, so you can make sure that you’re meeting their expectations
Download now: 8 Innovations to Modernize Market Research
Scott Smith, Ph.D. is a contributor to the Qualtrics blog.
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