About Double-Crossing
Double-crossing, also known as “breakdown” or “multi-variable analysis,” allows you to analyze your survey data at a deeper level by applying a second layer of cross-referencing.
While the Crosstab report lets you cross one variable with another, double-crossing takes it a step further by enabling you to break down your data by an additional variable, at the chart level.
How It Works
For example, if you first cross your survey results by gender, double-crossing lets you add a second variable—such as age—allowing you to view results for each age category within each gender group. This added layer of analysis helps you dig deeper into your data and uncover more nuanced insights.
- Navigate to the Detailed Results tab in the Results section of the Platform
- Select a chart, click on 'edit'
- Select 'Cross' and scroll to add a breakdown variable
When to Use Multi-Variable Analysis
- Comparing Results Across Multiple Segments: For instance, when analyzing data across different countries, waves, or target groups, you can use a demographic variable (like age or income) as a second level of cross-referencing to see differences within each segment.
- Advanced Demographic Analysis: By applying a second demographic variable, you gain a clearer understanding of how specific groups within your sample respond to your questions.
Double-crossing is compatible with all question types, except matrix questions, and is available exclusively in the table view.
Significance tests are also active when using this feature, helping you quickly identify key insights. Additionally, charts generated from this analysis can be exported for further use.