Filters and profiles

What is filtering for?

It's the case for many research projects that to answer all your business questions you need to look at how respondents with different attributes or attitudes responded to your survey. This is called filtering your data.

When you first open a report, the platform will show you the KPIs and other automated reporting that are most important to your business question. The report will default to showing you the aggregate of everyone who answered the survey. While it's a best practice to look first at the results in aggregate, it's very common to have more targeted questions about subgroups. For example, you may ask how your study results differ by the respondent's:

  • Region
  • Age
  • Gender
  • Purchase behavior (i.e., those who purchase from your category most often) 
  • Attitudes about your stimulus (i.e., those who especially liked your stimulus, often referred to as those in the "top two box")
  • Answers to custom questions you included 

By filtering to see how different subgroups responded to your survey, you may find opportunities or risks hidden in the aggregate that help give you and your teams much clearer guidance on how to move forward, with whom, and what's at stake.

How do I find and apply filters in Zappi?

1. Locate the report you'd like to filter. Typically this will be via the Projects menu tab and selecting Analysis. Locate the tool you used to run the survey and then the project. When a project is selected, a menu will appear on the left. Select Charts to open your report.

2. Select any group of charts within the report you are interested in and then an individual chart. For this example, we're going to look at the Behavior Change metric for a Concept Test.

3. Once the chart is open, make sure the "Show sidebar" option is toggled to "Yes."

4. Then, explore your filters! What exactly is available will depend on which tool you've used and what custom questions you included. Generally speaking, the first filters listed are from the survey's screening portion, followed by measures or attitudes asked for in the main survey, followed by your custom questions. Expand the filter you'd like to apply and select options to include in your analysis. This GIF illustrates filtering on how often the respondents purchase from the category. In the aggregate, the stimulus performed at or below the norm. However, among those who shop the category the most, it performed well above the norm.

Caution: Watch your base size

As you adjust your filters, the base size reflected in your analysis will drop. Take caution with conclusions drawn based on small numbers of people.

How do I add custom filters?

Creating custom filters (and custom, user-defined norms) is easy! Check out this video to learn how and then head over to the platform, select your project and try it yourself within the “Filters” tab on the right-hand sidebar. Remember that when you add a new condition, “ALL” means all x AND y criteria must be met; and “ANY” means x OR y criteria must be met.

Other ways to look at subgroups


On a selection of our tools, we have an additional functionality called Profiles. Profiles help to do a lot of the heavy lifting of filtering by pre-grouping them into a single click. For example, "All adults under 35" or "Male mid-lifers." You can also build your own Profile to use over and over. 

Perhaps most importantly, profiles are also tied to normative data for the grouping selected. So the key difference between filters and profiles is that applying a filter only affects the selected stimuli data you are analyzing, while applying a profile affects both the stimuli data and the norm you are analyzing. 

This means that if you select "All adults under 35," you will not only filter the data you're looking at down to all adults under 35, you will also see the norm change to reference the benchmark for that measure among adults under 35. This can be especially useful when you want to determine if a group that tends to skew in a certain direction (i.e., males 18-35 tend to have higher purchase intent in the beer category) is responding even more than you'd expect to the current stimulus.

Note: Profiles and the norms they reference are tied to the category, so a profile created for "Beer" could not be applied to "Wine." If you intend to analyze multiple categories, it will require consistent testing in each category to create a profile for each category.

The tools where Profiles are available are:

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