50 Example Market Research Questions to Ask Your Customers

Choose from 50 market research questions to use in your surveys, focus groups and your marketing plan to help you develop new products and increase customer satisfaction. These examples are based on fashion and shopping but you can swap out any of the fashion mentions to that of your product and see if they make sense for your industry.

Market Research Question Examples

  1. What do you think about our product?
  2. How would you describe yourself?
  3. What do you like most about this brand?
  4. Why did you choose this brand?
  5. Do you prefer to shop online or offline?
  6. Where do you usually buy your clothes?
  7. Which websites can you recommend?
  8. What kind of shopping experience do you want?
  9. What are your favorite stores?
  10. Who are your favorite brands?
  11. What are your favorite colors?
  12. What size do you wear?
  13. How much money do you spend on clothing each month?
  14. How many times per week do you go shopping?
  15. How long does it take you to decide what to purchase?
  16. How important is fashion to you?
  17. How do you feel when you see other people wearing similar items as yours?
  18. Do you follow trends?
  19. Are you interested in buying more expensive items?
  20. Have you ever bought something just because it was trendy?
  21. Do you consider yourself fashionable?
  22. Would you be willing to pay extra for quality?
  23. Do you think that fashion should be affordable?
  24. Do you think that high prices are justified?
  25. How do you define luxury?
  26. What is the biggest problem with current fashion industry?
  27. How do you feel about fast fashion?
  28. What do you think of the latest trend in fashion?
  29. How often do you change your style?
  30. When you look at someone’s outfit, how do you judge her/him?
  31. What are some of the things that influence your choice of clothing?
  32. If you had to pick one item to wear every day, which would it be?
  33. What is your ideal wardrobe?
  34. What is your idea of beauty?
  35. What is your opinion of celebrities?
  36. Do you think that women should dress up?
  37. What is your opinion about dressing up for work?
  38. What are your thoughts on casual vs formal attire?
  39. What is your definition of elegance?
  40. What is your definition for stylish?
  41. What is your definition about being fashionable?
  42. What is your opinion on men who dress well?
  43. What is your definition on dressing down?
  44. What is your opinion regarding the importance of accessories?
  45. What is your opinion towards minimalism?
  46. What is your opinion toward color matching?
  47. What is your opinion concerning the importance of fit?
  48. What is your opinion when it comes to the concept of “trendy”?
  49. What is your opinion in regards to the term ‘streetwear’?
  50. What is your definition of elegance?


What is market research?

Market research surveys are a type of marketing research that involves the collection and analysis of data from existing or potential customers. The purpose of this type of research is to gain information about what people think, feel, believe, want, etc., in order to make better business decisions. Market research can be conducted through various methods such as telephone interviews, focus groups, questionnaires, and online surveys.

Why do companies conduct market research?

Companies use market research to help them understand their target audience so they can create products and services that meet their needs. For example, if you’re planning on selling a new product, it’s important to know who your target audience is and how best to reach them. You might also conduct market research to find out whether there is enough demand for your product. If not, you may decide to change your plans.

What software can I use to conduct market research?

Our recommendations for software to run your market research are Typeform & SurveySparrow (conversational survey builders) or Jotform & Formstack.

How does market research work?

Market researchers typically start by identifying the problem they want to solve. They then identify their target audience and determine which demographic group(s) will most likely buy their product or service. Next, they develop a questionnaire (or series of questions) designed to gather information from potential customers. Once the questionnaire is complete, they send it to their potential customer base via email, snail mail, or other means. This method of gathering data is called “qualitative” because the researcher asks open-ended questions instead of providing respondents with a list of choices. Qualitative research is often used when the goal is to learn more about an issue or topic rather than to sell something.

In contrast, quantitative research uses structured questions to collect data. For instance, if you were interested in learning more about the number of people who eat at restaurants located near train stations, you could ask restaurant owners or managers the following question: How many people come into your restaurant each day?

What types of market research exist?

There are two main types of market research: qualitative research and quantitative research. Qualitative research is usually done using one of three different approaches: 1) descriptive research, 2) analytical research, or 3) experimental research. Descriptive research focuses on describing a situation or phenomenon. Analytical research examines cause-and-effect relationships between variables. Experimental research attempts to control all factors except those being studied. Quantitative research includes both primary and secondary research. Primary research is research based on direct observation. Secondary research is research based on previous studies.

Qualitative Market Research Methods

Descriptive research is commonly used to describe a situation or phenomenon. It’s also known as observational research because it relies on collecting data without influencing the behavior of the subjects. In addition, descriptive research is sometimes referred to as nonparticipant research because it doesn’t involve any interaction with participants.

Descriptive research methods include:

  1. Interviewing – A common way to gather information through interviews is to talk with someone about his or her experiences. The interviewer may ask questions such as: What do you like/dislike about this job? Why did you choose this company over another? How would you rate this organization overall? An interview is similar to a conversation but it is conducted face-to-face.
  2. Surveys – A survey is a tool that helps you understand what people think about a certain subject. You can use surveys for marketing purposes. Survey questions can be very simple or complex depending on how much information you need. Simple surveys might ask only a few yes or no questions while more complicated ones might have multiple choice answers.
  3. Questionnaires – A questionnaire is a tool that allows you to ask people specific questions. Unlike surveys, questionnaires don’t require the respondent to answer them immediately. Instead, he or she can return the completed form later.
  4. Focus groups – A focus group is a meeting where several people discuss a particular topic together. Participants may share personal opinions or ideas about the topic under discussion. Focus groups are helpful when you want to find out what other people think about a product, service, idea, etc.
  5. Observations – Observing something is a good method for gathering information. This type of research is often used by researchers who study human behavior. For example, if you wanted to know how customers behave in your store, you could observe these behaviors during normal business hours.
  6. Document analysis – Document analysis involves analyzing documents (e.g., annual reports, financial statements, contracts, emails, memos, letters, etc.) to determine trends and patterns.

Quantitative Market Research Methods

In contrast to qualitative methods, which rely solely on self-reporting, quantitative methods rely on empirical evidence. These methods involve measuring some aspect of reality (i.e., an objective variable). They’re typically divided into two categories: 1) correlation research and 2) regression research. Correlation research measures the relationship between two variables. Regression research uses statistical techniques to predict a dependent variable from one or more independent variables.

Correlation research includes:

  1. Experimental design – One way to measure the relationship between two variables is to conduct an experiment. For example, you could randomly assign different products to two different stores. Then, you could compare sales revenue at each location. If there’s a significant difference between locations, then you can conclude that location had an effect on sales.
  2. Descriptive statistics – Descriptive statistics include mean, median, mode, standard deviation, skewness, kurtosis, range, interquartile range, frequency distribution, and percentage. Mean, median, and mode are just three of many descriptive statistics you should know.
  3. Inferential statistics – Inferential statistics help us make conclusions based on data collected from our experiments. For example, we can say with 95% confidence that a sample population has a true mean of 50. In this case, we would conclude that the population as a whole most likely has a true mean of approximately 50.

Regression research includes:

  1. Linear regression – The goal of linear regression is to explain variation in a dependent variable using one or more independent variables (also called explanatory variables). We use multiple regression to analyze relationships among multiple variables.
  2. Logistic regression – The goal of logistic regression is to predict whether an outcome will occur given one or more predictor variables. You can use logistic regression to identify factors that influence customer satisfaction.
  3. Multiple regression – Multiple regression is similar to multiple linear regression. However, it allows for more than one dependent variable.
  4. Ordinary least squares regression – OLS regression is also known as ordinary least squares regression because it minimizes the sum of squared errors. It’s used to estimate parameters such as means, proportions, slopes, and intercepts.
  5. Probit regression – Probit regression is used when the probability of an event occurring is not 0 or 100%. This type of model estimates the conditional probability of an event occurring given certain values for other variables.
  6. Poisson regression – A Poisson regression predicts the number of events that will occur over time.
  7. Quantile regression – Quantile regression is used to find the value of a continuous random variable at any specified quantile.
  8. Regression analysis – Regression analysis helps us understand how changes in one variable affect another.
  9. Structural equation modeling – SEM is a technique that combines multiple regression and path analysis into a single statistical framework. The framework allows researchers to test hypotheses about direct effects, indirect effects, and moderating effects.
  10. Survival analysis – Survival analysis is used to study the length of time until an event occurs.
  11. Time series analysis – Time series analysis is used to forecast future trends.
  12. Two-way ANOVA – Two-way ANOVA is used to determine if there is a significant interaction between two categorical variables.
  13. Zero-inflated models – ZI models are used to account for situations where there are zeros in your dataset. They’re often used in cases where there are few observations but those observations have extreme values.
  14. Correlation – Correlation is used to measure the strength of a relationship between two variables.
  15. Factor analysis – Factor analysis is used to reduce large datasets by identifying patterns within the data.
  16. Cluster analysis – Cluster analysis groups data points together based on their similarities.
  17. Principal component analysis – PCA is used to reduce the dimensionality of a dataset.
  18. Canonical correlation analysis – CCA is used to find the maximum amount of variance shared between two sets of variables.
  19. Latent class analysis – LCA is used to group individuals into homogeneous classes.
  20. Bayesian statistics – Bayes’ theorem is used to calculate probabilities.
  21. Decision tree analysis – DT analysis is used to classify data based on a set of rules.
  22. Naive bayes classifier – NB classifier is an algorithm used to make predictions using probabilistic methods.
  23. Support vector machine – SVM is a supervised learning algorithm that uses training examples to learn a classification function.
  24. Linear discriminant analysis – LDA is used to identify the features that best discriminate between different categories.
  25. Logistic regression – LR is used to predict whether an outcome will occur or not.

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