Use case
It's common to want to analyze interview responses by certain subgroups within your data. To do this type of analysis within Outset, you'll want to set up a filter, segment, or crosstab.
For example:
How did customer sentiment towards this product vary by gender (male vs. female) or age (18-35, 65+)?
For people who responded "1 or 2" out of 5 in likelihood to buy the product, what themes existed in their demographics or other responses?
Watch the short video below for more details!
How to set up filters, segments, and crosstabs
🚀 Product update: as of May 2025, filters and segments are also available in the Insights tab (not just custom reports) 🚀
To recap -
If you want to apply a few specific filters to all of the answers in your report, and you don't expect to need to switch between subgroups, you can select the "filter" option and set up filter criteria for the report
If you have several different subgroups you want to be able to flip between as you're viewing responses (e.g., men vs. women), you'll want to set up segments
If you want to look at how responses to a particular question vary by a subgroup, you can use the "crosstab" feature
Are there any analysis differences between filters and segments?
Yes, we're glad you asked!
When you filter the Insights page or a report, you just take the existing report and filter the data to that one sub-group (e.g., women). None of the underlying categorization of data is updated - it shows the same graphs you see that were analyzed at the population-level, but just for that sub-group.
When you create a segment, you actually re-run the Insights page/ report for that sub-group. What that means is that the graphs will actually re-generate with relevant findings just for that one sub-group.
For example, this graph was generated across all participants, with N=29, for a study focused on nutritional goals.
When we filter the data - e.g., filtering to people who are within Category A, with N=15, that takes the same graph and just cuts down the numbers to only people who are from Category A.
You can see that the overall categories are the same, it's just the numbers that are different here vs. the graph above.
In comparison, when we generate segments - e.g., Category A here, with N=15, the graph actually re-generates and creates new categories that were only relevant to that category.
You can see that these categories are somewhat different compared to the first full-population graph.
