Using Attest's powerful in-browser analytics, you can quickly look for correlations between responses. If you click on an answer that you care about, the results for all questions will update. That means that within the question (if it's not single choice) you'll see what these respondents have selected as well and you will see how they have responded to all other questions of your survey.
The average score from the whole panel for each answer will be marked by the vertical dashed line, while the greyed out area represents the average for that question of the specific demographic you've highlighted.
Keep in mind that for a single choice question, the other answers will become 0, as these users could only select one answer within that question.
You can select as many answers across as many questions as you want and the results will keep updating to reflect the responses of those respondents.
You can also layer these filters on top of demographic filters, or see how the demographic profiles change when you click these answer filters on.
What is the logic that is applied?
When you select multiple answers within one question, this will follow an
OR logic . In the below example this means that you would be looking at how people that are interested in design & decoration
OR Art & photography.
When you select multiple answers across different questions, this will follow an
AND logic. In the below example you will be looking at the results for people that enjoy watching video content the most
AND post image content the most themselves.
Filtering ranked questions
We've recently also added the functionality to filter by ranked questions. This allows you to see how people that have ranked an answer high (first or second) have responded to the rest of your survey. You'll also see what these people ranked second, third etc. within the same question. In the below example you can see that people that are most interested in "politics", mostly selected "business" as second option.
There are many benefits of this feature. Looking at big raw data can be confusing and filtering by answers allows you to map out relationships between different variables. Making it easier to make sense of your results.
If you have any more questions about interpreting your data, don’t hesitate to get in touch with our Client Experience team.