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Analyze your observations with the affinity map
Analyze your observations with the affinity map

An overview of analyzing observations using affinity map in Reframer

Updated over a week ago


Affinity mapping is a flexible and visual way to quickly group, organize and make sense of qualitative data.

Reframer makes this method more powerful than ever with the ability to search and filter your data, and having your observations, tags, and themes all connected and stored in one place.

The affinity map interface at a glance

This is where all your hard work reviewing, tidying and tagging your data pays off. When you first land on the affinity map, the canvas will be blank, with your observations and all their metadata in the list on the left hand side.

Group observations into themes

To make sense of your data, move observations that relate to a similar concept into the same group. This will create a visual representation of themes within your data.

You don't have to get everything perfect in one go. Affinity mapping is a very flexible method, and we encourage you to go through the grouping and refinement in iterations.

You can start by creating a few groups first, and then splitting them or combining a few of them later. However, tidying up the groups by adding titles and aligning them neatly as you go makes it easier for you to revisit your groups further down the track.

Use search and filter to narrow down relevant observations

Use the keyword search and filters to quickly narrow down observations. If the observations are structured with tags, tasks, sessions and segments, you could use them as lenses to look at a smaller data set and have a quick go of grouping your observations.

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