Explorer: CrossTab charts

What is a cross-tab?

It’s a table that highlights the relationship between two or more variables, also known as a “contingency table”.

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Cross-tabs are a very popular way to analyse the relationship between demographics in market research.

How to set up a cross-tab

Select your dataset, on an Explorer dashboard, set up Category View tab. Next, click on "Charts" under the overview chart to configure per-category charts.

A new page will open on which you can select your desired chart type among the 6+ possible options. Click on "Show all" if Crosstab is not listed under Chart Type.

1. Select Crosstab
2. Select the two categorical fields that you wish to cross analyse
3. Select the metrics you wish to include. Note that you can reorder them by drag-and-drop on the left side of each item
4. Select / Deselect the optional items
5. Name your chart on top
6. Hit save

Components

Crosstab header

Display a header above your cross-tab to provide context. Perfect for survey questions. For example "What insurance provider do you have a policy with?"

Metrics to display in cells

• Count (default): the frequency of the cell in your dataset.
• Expected count: the expected frequency of the cell, calculated against your dataset
• Column percentage: the proportion of the cell relative to the column’s total count, represented as a percentage. Useful for breaking down a category.
  Example: If you’re looking at the relationship between age and insurance provider, column percentage helps you breakdown how popular each insurance provider is within an age bracket.
• Row percentage: the proportion of the cell relative to the row’s total count, represented as a percentage. Useful for breaking down a category.
  Example: If you’re looking at the relationship between age and insurance provider, column percentage helps you breakdown the distribution of ages for a provider.

Note: You can re-arrange metrics by dragging the handle.

Highlight insights

See if cells are above or below their expected value, and whether the two variables you selected are related. Each cell is color-coded: blue means above (over-indexing), red means below (under-indexing). An insight displays at the bottom of the cross-tab showing whether a statistically significant relationship exists between the two variables or not.

Selecting over/under arrows displays a corresponding arrow aside each cell value indicating whether it’s above / below the expected.

Show Chi-squared test results

Crosstab insights are based on a Chi-squared test computed at a significance value of 0.05. Selecting this displays the computed statistic, degrees of freedom and p-value below the crosstab.

Tips

Cross-tabs tell stories, but not when they’re difficult to read. We suggest the following to make your cross-tab easier to interpret:

• Display a maximum of two metrics in each cell. Count and Row Percentages are good to start off with.
• Use a header to provide context to your cross-tab.
• Enable insights and over/under arrows to make trends easier to visualise.
• Only enable row / column totals when they support the data.