Skip to main content
All CollectionsAnalysing results
Getting to insights faster with Crosstabs
Getting to insights faster with Crosstabs

Crosstabs simplify the process of extracting meaningful insights. Learn more about crosstabs and how to create them in Attest platform.

Updated over 4 months ago

What are Crosstabs?

Crosstabs, also known as cross tabulations or contingency tables, are two-dimensional (or more) tables that allow you to split data based on variables and determine if there is a relationship between them.

Crosstabs are commonly used to analyse survey response data, as they provide a more detailed comparison of how different groups of respondents answered specific questions. The results are presented in aggregate data tables that display the results of the entire group of respondents (total), as well as the results from defined subgroups.

How to create Crosstabs with Attest

With the new Analysis page, it’s easier then ever to split your data and look for statistically significant differences across demographics, countries, waves, and questions.

Instructions

  1. Navigate to “Analysis”
    On your results dashboard you will see Analysis as a new tab next to Overview and Trends.
    ​

  2. Select the data you want to analyse
    If you’ve sent out your survey multiple times or to multiple countries, select the waves and/or countries for which you would like to build your Crosstab from the dropdown at the top of the page.
    ​


    ​

  3. Choose your visualisation
    ​    You can choose to build out Crosstabs, or you can choose for chart visualisations. Both will only display the total column until you have selected your variables.
    ​

  4. Add your variables
    Select the variables you want to include from the panel on the right-hand side. You can choose to add demographics, waves and answers to certain questions (single and multiple choice only). You can include all fields in a variable or select specific fields by clicking on the arrows and choosing the variables you need (e.g., certain age ranges). To remove a variable from your Crosstab, simply deselect it.
    ​


    ​

  5. (optional) Add another stacked variable
    Standard crosstabs are most commonly used and allow you to add multiple variables as columns to your crosstabs. Stacked crosstabs takes it one step further by allowing you to add a top-level variable (e.g., country) as well as multiple sub-variables (e.g., age). This additional layer splits your crosstab based on the top variable, providing a more detailed and comprehensive view of your data. We recommend this for larger multi-country or multi-wave surveys.
    ​
    If you want to create a combination of various demographics, answers or other criteria you can create segments and add these to your crosstab. Learn more about segments here.
    ​

  6. Look for statistically significant differences
    With our built-in significance test you can see on where the results are significantly higher or lower. You can toggle this on and off, choose the confidence level you want to run the test at (95%, 90% or 80%) and the column you want to compare against (total, previous column or a specific column).
    ​


    ​

  7. Choose how to display your results
    To customize your crosstab, click on the options menu located at the top-right of your page. From there, you can choose what to display (values, percentages, or both) and the order of your answers (based on draft order or based on results order).

  8. Export the data
    You can download all your questions at once in an Excel file or copy the data of a single question to your clipboard by clicking "copy data". This will copy the data to your clipboard, allowing you to paste it into a spreadsheet for further analysis.

The benefits of Crosstabs

Analysing data can be overwhelming, but Crosstabs can help you manage large data sets by breaking them down into more manageable subgroups.

You can split your data based on various variables, such as:

  • Demographics – to see if there are any differences in peoples responses based on age, gender, income etc.

  • Questions – to find out if there are relationships between people’s responses to different questions

  • Geographic region - to discover differences across countries and regions

  • Dates – to check for granular changes over time, if you’ve sent out your survey multiple times (multiple waves)

Delving through this information and visualizing this through Crosstabs makes it easier to uncover granular insights, patterns, trends and opportunities. Without Crosstabs, these insights would likely go unnoticed or require a lot more work to reveal.

Let’s look at an example

We asked 2,000 respondents across the US and the UK which social media app they use the most. The results show that Facebook is by far the most popular app, with 47% of saying it’s their most-used app.

However, when we create a Crosstab and examine certain subgroups (in this case, age groups), we can see that TikTok is the most used social app for respondents aged 18-24, with 40.5%, followed by Instagram (24%) and Snapchat (19.5%).
​

This can be very helpful information when deciding on what the best way is to reach your target audience.

When should I use Crosstabs?

Crosstabs can be used for any type of data analysis, but they are particularly helpful when you’re looking for:

  • Informed decision-making: Use the insights gained from Crosstabs to guide decision-making in areas such as marketing strategies or new product development.

  • Hypothesis testing: Test hypotheses or assumptions by comparing the responses of different groups and validate or reject certain hypotheses.

  • Segment analysis: Break down your data into subgroups and see how different demographic or characteristic groups responded differently to survey questions. You can learn more about analysing different segments.

  • Exploratory analysis: Discover unexpected relationships and new areas to explore further.

Did this answer your question?