Matrix Questions Explained + Survey Template

Definition: Matrix questions allow you to capture multiple points of feedback about one general subject. They are often used to capture ratings. For example, a hotel guest might be asked to rate various aspects of their accommodations. A matrix question will contain the topics as rows and the ratings as columns.

A matrix question is commonly used when you want to rate a group of similar attributes. In the example below, the characteristics of a company are displayed as rows, and the rating for each attribute is displayed as columns. This allows a customer to give feedback for various topics using the same scale quickly. This example could be used as part of a more extensive customer satisfaction questionnaire.

• Survey questions that ask respondents how often (rows) they perform certain actives (columns)
• A hotel asking quests how important (columns) different amenities (rows) are
• A restaurant chain asking head chefs what vendors (columns) they think are the best fit for different menu items (rows)

To create a matrix survey, simply create a survey as normal, and then add a matrix question where you see fit. An unlimited number of rows can be included along with up to twenty (20) columns. To limit survey fatigue, we recommend including no more than twenty (20) rows and ten (10) columns.

In the example above, we only include three (3) columns for the various levels of satisfaction. We recommend for any type of satisfaction rating, only a scale of three (3) or five (5) levels should be used. Anything more incuses survey length, increases survey fatigue leading to lower quality data.

• Require an answer (can not proceed until answered - each row much at have one checkmark)
• Add "N/A" column (does not factor into weighted average if marked)
• Display logic can be enabled for this question type - meaning this question will only show if previous questions have been answered a certain way

One downside to a matrix question can arise if you are using it to determine the importance of different attributes (rows). If a hotel chain used a matric question to how important (on a scale of 1-5, other attributes are (such as mattress comfort, parking, and proximity to the beach), nearly respondents will likely rate all of these as important. Ideally, hotel management would want to identify what is truly most important to guests so they can have a narrow focus and use resources appropriately.

A solution to this problem is MaxDiff. MaxDiff is used to identify what is most and least important (or most/least desired) from a list of attributes. The basic concept is that respondents are shown a small subset of the total attributes (like a random set of five out of ten attributes) and pick what is most and least important. Respondents are shown multiple sets, meaning attributes are compared against one another.

Results for a matrix question will include the response counts per column and row with a resulting bar chart. The bar chart can help you quickly identify trends.

The system will compute a weighted average for each for each row (each attribute). You can change the value of weights at any time on the survey creation page. The Excel export will contain a column for each matrix row, with the rating value each respondent selected. If a respondent skipped a question row, that cell would be left blank.

Creating a segment report for a matrix question can help identify hidden issues. A regional store manager might want to segment results the results of a customer satisfaction survey by state or city. The questionnaire may atomically include store location using query strings.

With the location data, a segment report (or a cross-tabulation report) could be created. The segment report would then include the table shown above, separated by state or city. The regional manager could then use this analysis to follow up with certain stores to find ways they can improve certain areas.