How to Create and Configure a Cross-tab Table

A cross-tab table is a table that allows you to compare two or more variables together to check differences in responses between groups or the relationship between variables. Looking at the overall response results alone can make it seem as though all respondents share similar opinions, but using a cross-tab table makes it easy to see which responses appear more frequently in specific groups.

For example, if you want to compare how "brand satisfaction" differs by "gender" or "age," a cross-tab table lets you see at a glance which group has higher satisfaction — male or female — or how satisfaction varies by age group.

To use a cross-tab table, you need two or more variables that can be compared against each other. The table consists of two elements: "Analysis Criteria" and "Analysis Target."

This is the information that defines how you divide and compare the data. It serves to segment respondents into multiple groups. For example, the following variables can be used:

These criteria allow you to compare differences in responses between different groups.

This is the data you actually want to analyze and review in the cross-tab table. It typically consists of response results from survey questions. For example, the following items can be analysis targets:

In short, the basic structure of cross-tab analysis is to segment respondents using the analysis criteria and then compare the response results of each group using the analysis target.

In Dataspace's Cross-tab tab, you can easily configure a table using just mouse drag and drop.

step 1. From the variable list in the left sidebar, select the variable you want to use as the analysis criteria (e.g., gender, age, or other profile or survey variables), then drag and drop it into the [Analysis Criteria] area.

step 2. In the same way, select the variable whose results you want to check from the left sidebar and drag and drop it into the [Analysis Target] area.

step 3. Configure the confidence level, analysis level, weighting, and other settings as needed.

step 4. Once you complete the settings, the cross-tab table is automatically generated on screen. Use the generated table to compare response results across groups.

A. The variable list in the left sidebar is divided into "Embedded Data" and "Survey Data."

A few simple settings in the cross-tab table allow you to view data more clearly and in the way you prefer.

Click the sort icon to the right of "Total" or "Response count" in the cross-tab table to sort the data. Changing the sort order lets you view results in descending order of response rate or response count, so you can quickly see which items were selected most.

For ranking-type questions, you can select how many ranks to include in the analysis. Click the dropdown menu in the analysis criteria or analysis target area, then select one of the following: Top 1, Top 1–2, or Top 1–3. The responses within the selected rank range will be reflected in the cross-tab table.

Click the dropdown button in the upper left of the cross-tab table to choose how data is displayed. Depending on your analysis purpose, you can view data as percentages or also see the actual number of responses.

If you want to exclude specific choices from the cross-tab table, use the filter icon to the right of the response count. Click the filter, uncheck the choices you want to exclude, and select [Apply]. The data from respondents who selected those choices will be excluded from the cross-tab table.

This feature swaps the positions of the analysis criteria (columns) and the analysis target (rows). Click the arrow icon to switch the table layout and analyze the data from a different perspective.

Click the enlarge table icon to display the cross-tab table in an expanded view. This lets you see the table larger and more clearly, making it easier to review data at a glance.

Click the "Copy Table" icon at the top of the cross-tab table in the Cross-tab tab to copy the table to your clipboard. You can then paste it in Excel or a spreadsheet by right-clicking and selecting [Paste], or by pressing Ctrl + V.

If you need a more precise analysis, you can combine multiple variables in the analysis criteria area to create a multi-dimensional cross-tab table.

Stack variable cards on top of each other in the analysis criteria area to create more detailed subgroups within a single criterion. (Up to 3 variables)

For example, adding "Age" below "Gender" lets you see results broken down into more granular groups, such as Male-20s, Male-30s, and so on.

Place variable cards side by side in the analysis criteria area to compare the results of each criterion simultaneously on a single screen.

For example, placing a "Gender" criteria table and an "Age" criteria table side by side lets you quickly compare differences in responses across each criterion.

You can also use horizontal and vertical combinations together to configure analysis criteria in whatever way you need.

For example, combining [Gender × Age] vertically and adding "Place of residence" as a horizontal criterion enables a more multi-dimensional data analysis that takes multiple conditions into account at once.

Have you successfully created your cross-tab table to suit your purpose?

If you're unsure how to structure the table, please click the [Help Center icon] in the bottom right corner of the screen to contact us. Our team will quickly review and help resolve any difficulties you're experiencing.