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Matrix Questions
Matrix Questions

Matrix Questions
Guide with Examples

Matrix questions are a powerful tool in survey design, allowing you to group related questions together and gather more efficient data. In this guide, we’ll explore what matrix questions are, their benefits, and provide examples to help you design effective surveys.

A matrix question is a 2-dimensional survey question that allows respondents to answer multiple sub-questions in a single grid. They are also sometimes called table questions or grid questions. Matrix questions are useful for asking complex questions and avoiding response bias, but they can be difficult to write and visualize

In this article, we will give you a definition of matrix questions, provide examples and explain how you can use them in your surveys.

What are Matrix Questions?

Matrix questions are a series of questions with the same set of predefined answer choices presented in a grid or matrix table format; also known as grid questions.

Matrix questions can be multiple or single selection – meaning the respondents can select multiple answers to one question, or only a single answer to one question, respectively. However, all questions must be closed-ended questions. In other words, matrix questions must be answered by selecting one or multiple predefined answer choices provided with the questions. The formatting of these questions is their key characteristic; the questions are presented in rows, and a set of predefined answer choices are presented in the columns.

This question type is very common in surveys for a wide range of purposes, including market research and customer feedback collection. For example, a matrix question may ask respondents to rate their satisfaction with customer service, with the columns representing the different levels of satisfaction (e.g., from “very satisfied” to “not satisfied at all”). Or a matrix question may ask how a specific image makes respondents feel, with the answer choices being statements like “It makes me happy”, “It makes me sad”, or “it makes me uncomfortable”.

Matrix questions are a powerful tool for both respondents and researchers. They make it easier and faster for respondents to answer the questions and allow researchers to collect qualitative and quantitative data efficiently.

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Single-selection and Multiple-selection Matrix Questions

Matrix questions are very common in surveys and focus groups, but they can benefit just about any kind of survey or questionnaire. While there are many variations, all matrix questions are either single-selection or multiple-selection.

  • Multiple-Selection Matrix Questions

    Multiple-selection questions allow respondents to select more than one answer choices from the predefined answer choices. The multiple-selection questions are great for collecting specific data points and gaining a deeper understanding of your respondents’ behaviors or preferences, as this format allows researchers to collect answers that only apply to the corresponding questions.

  • Multiple-Selection matrix questions
  • Single-selection Matrix Questions

    Single-selection questions, on the other hand, only allow respondents to select one answer choice per row.

  • An example of single-selection matrix questions

Benefits of Matrix Questions

  • Increased response rate
    The structure of these questions offers many unique benefits, the most obvious of all is its ability to save space, since each set of questions shares the same set of predefined answer choices, which in turn makes the questions easier to process by respondents, therefore reducing response time. This is significant because response time is a key factor in reducing drop-off. Understandably, most respondents prefer spending less time answering questions. In fact, a study in 2017 indicates that web surveys should not take more than 10 minutes for respondents to complete
  • Reduced respondent fatigue
    Item-by-item can be very tedious for respondents especially when numerous questions are similar or related to each other. Just reading through each question creates more mental labor for respondents, which is likely to lead to respondent fatigue. In a way, matrix questions synthesize the information and present it to respondents in a summary, and through this, they significantly reduce respondents’ reading time and thinking process, efficiently reducing, or even preventing, respondent fatigue.

In general, the grids of matrix questions are more intuitive and easier to digest, compared to item-by-item surveys, which is why these questions are an excellent tool to present close-ended, predefined answer choices for respondents to select. Additionally, the data collected from matrix questions are also easy to analyze and sort through for researchers.

Drawbacks of Matrix Questions

As popular as matrix questions are, they are not without drawbacks. It is important to understand the pros and cons before designing these questions to fully leverage their strength while minimizing their weakness. Here are some of the most relevant disadvantages of these type of question:

  • Straight-lining
    While the formatting of these questions makes it easier for respondents to answer questions, it can also lead to straight-lining, where respondents mindlessly select the same answer or select answers in a pattern for every question; although when compared to item-by-item surveys, the difference is usually not significant. To avoid straight-lining, it is crucial to carefully design not only the wording of the questions, but also the overall formatting.
  • Poor data quality
    The biggest advantage of this question type can also be its biggest downfall; aside from straight-lining, matrix questions also make it easy for respondents to rush through questions, clicking away randomly without reading. Mandatory or incentivized surveys are particularly vulnerable to this risk.
  • Missing data
    Compared to item-by-item surveys, matrix questions produce more missing data in five-category and seven-category questions (Questions that offer five predefined answer choices and seven predefined answer choices, respectively). Additionally, if there is a financial incentive for taking the survey, these questions can also be filled in by bots.
  • Risk of poor mobile responses
    Smartphones are now the primary device for people to access the internet. Unfortunately, research shows that matrix questions produce more missing data than item-by-item questions in web-based surveys, especially in mobile-based surveys Additionally, these questions can often appear distorted on smartphone screens, which is known to cause respondents to disengage.

Different Types and Variations of Matrix Questions

Matrix questions are very effective in communicating ideas and presenting them in a way that is easy to understand for respondents. They work best when asking respondents to rate a series of similar or related questions. They are also useful when asking about a subtopic under a larger topic, such as asking respondents to rate different services or attributes of an experience or product; you may have seen this in customer experience surveys, in which they ask about different aspects of the customer experience using the same set of predefined answer choices.

  1. Likert scale questions

    It is very common to see these questions with a Likert scale, which uses a five- or seven-point scale, presenting answer choices from one extreme to another. Created by, and named after American social scientist Rensis Likert, the Likert Scale is a very popular tool to reliably measure attitudes, opinions, and behaviors as it allows respondents to quickly give feedback for different items using the same scale.

    For example, the answer choices may go from “strongly agree” to “strongly disagree”, with an option of “neutral” in the middle, while the different questions can be a variety of related items. When used properly, the Likert Scale can greatly benefit the data analysis of the survey as each answer choice can be weighted in the analysis.

  2. An example for likert scale matrix question
  3. Side-by-side questions

    Side-by-side matrix questions combine two sets of columns for the same set of questions, making it a useful and effective tool to combine two sets of questions with the same questions but different answer choices

    This is a powerful tool to reduce survey length and further reduce response time as well as respondent fatigue. From a research and analysis standpoint, side by side matrix questions are very powerful because they can collect data from multiple variables at once and are ideal for conducting map analysis.

  4. An example for side by side matrix question
  5. Ranking questions

    As the name suggests, ranking matrix questions ask respondents to rank different items using the same scale. The items to be ranked are the questions (rows) and the ranking scale simply goes from 1 to 5 or other predetermined points. This type of matrix question is essentially a variation of the Likert scale questions where statements are replaced with numbers representing different levels of sentiments.

  6. An example for matrix question ranking

Tips for Matrix Questions

Before deploying a survey with matrix questions, it is crucial to thoroughly understand their strength and weakness in order to fully leverage their strength while minimizing the weakness. A good survey experience also encourages future survey responses. While the design and layout of any survey largely depend on the content, there are still some basic tips and best practice for matrix questions. Here are a number of key points to bear in mind.

  • Respondent experience
    First and foremost, the respondent experience should always be the first priority as it is the core of reducing drop-off and maintaining data quality. This includes visual presentation as well as wording, which brings us to our next key point.
  • Concise language
    Use concise and simple language to reduce survey length and respondent fatigue, as well as to ensure questions and the overall content are easily understood and digested. If your survey’s target respondents are the general public, then it is best to avoid using any technical terms or wording that only professionals in specific industries are familiar with. Concise language should also be used in answer choices, not just the questions; this will help create a better respondent experience as well as a better understanding of the answer choices.
  • Undecided response
    In the very beginning of designing matrix questions surveys, it is important to decide if the survey allows undecided answers, and if so, in what form? Some surveys allow undecided answers in the form of “skip this question”, while others provide an additional answer choice for an undecided answer. Note that both would increase risk of low-quality data.
  • Number of answer choices
    Finding a balance between data collection and minimum answer choices is an important task when designing a matrix questions survey. The most common number of answer choices are five and seven, which means respondents are also more likely to be accustomed to them. More answer choices beyond seven risk drop-offs could negatively impact data quality.
  • Layout and formatting
    When it comes to the presentation of the questions, it is important that respondents are not overwhelmed by the number of questions in each matrix table. It is generally advisable that there should be less than five questions in each matrix table. Beyond five rows, the matrix table may appear clumsy and make it tedious for respondents to read through and respond. Another crucial point is that the questions in each grid are related to each other, in order to avoid any confusion.

Testing the Effectiveness of Matrix Questions

Testing the effectiveness of these questions is an essential step in ensuring that your survey is collecting the data you need accurately and efficiently. Here are some steps you can take to test the effectiveness of your matrix questions:

  1. Conduct a pilot study

    Before launching your survey, conduct a pilot study with a small sample of respondents to test the clarity and effectiveness of your questions. A pilot study can help you identify any issues with your survey design before you launch the full survey.

  2. Use a diverse sample

    When conducting your pilot study, make sure to use a diverse sample of respondents that is representative of your target population. This can help you identify any biases or issues with your survey design that you may have overlooked.

  3. Monitor response rates

    Keep track of response rates for each question in the matrix to identify any questions that may be confusing or difficult for respondents to answer. Low response rates for a particular question may indicate that the question is unclear or that the response options are not appropriate.

  4. Use open-ended questions

    Consider including open-ended questions in your matrix to allow respondents to provide more detailed feedback on their experiences. Open-ended questions can help you identify issues with your survey design that you may have overlooked.

  5. Analyze data quality

    Once your survey is complete, analyze the data to identify any issues with response consistency or validity. Look for patterns in the responses to each question in the matrix and compare the results to other data sources, such as customer feedback or sales data.

  6. Iterate and refine

    Based on the results of your pilot study and analysis of the data, make any necessary adjustments to your matrix questions to improve their effectiveness. Refine your questions and response options to ensure that they are clear, concise, and relevant to your target population.

Testing the effectiveness of these questions is an ongoing process that requires careful attention to detail and a commitment to continuous improvement. By following these best practices for testing and refining your questions, you can ensure that your survey is collecting the data you need accurately and efficiently.


Even with all its disadvantages and challenges, matrix questions are still an effective and popular tool for a variety of surveys and questionnaires. Fortunately, most of the challenges and risks that come with these questions can also be minimized and/or migrated by a thoughtful design and layout.

Among the biggest challenges of this question type is the display of the matrix tables in mobile devices, a simple and effective solution for this would be using a dedicated software or online survey creation tools to build your surveys.

It would also be a good idea to manually review the data collected from your questions from time to time, just to confirm data quality. And don’t forget, for any matrix questions, the priority should be creating a visually tidy and easily understood survey to maximize your response rate and data quality.

Learn about further Online Survey Question Types


What are the advantages of using matrix questions?

Matrix questions allow you to ask multiple related questions in a condensed format, which can save time and reduce respondent fatigue. They also allow for consistent response scales, which can help to reduce response bias.

How many questions should I include in a matrix question?

It's generally best to limit the number of questions in a matrix to no more than six or seven, to avoid overwhelming respondents.

What types of response scales can I use for matrix questions?

Common response scales for matrix questions include Likert scales, semantic differential scales, and numeric scales. Choose the response scale that best fits the type of data you're collecting.

How should I group related questions in a matrix question?

Group related questions thematically, so that respondents can easily understand the connection between the questions. For example, if you're collecting data on customer satisfaction with a product, you might group questions together on aspects such as ease of use, reliability, and customer support.

How should I format a matrix question?

Matrix questions can be presented in several different formats, such as a table or a series of separate questions. Consider which format would be most appropriate for your survey design and the data you're collecting.

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