Affinity Diagrams in UX Research

UX research can give rise to a wide variety of insights and ideas. This can get extremely overwhelming if not organized and analyzed under a set framework.

Affinity maps lend much-needed structure and cohesion to your research data by helping you quickly and effectively examine key findings and prioritize issues that need to be dealt with most urgently. It is also a great way to get your product team and stakeholders involved in the design process in a fun and collaborative way.

Affinity diagrams are useful when you need to generate solutions or establish patterns and themes in your research data. It's one of the best ways to analyze qualitative data derived in the pre-design phase. For example, it’s a great way to build user personas after carrying out diary studies or user interviews. You can also use it to sort through large amounts of user feedback to arrive at actionable insights that can be prioritized.^[1]

However, the technique does come with its caveats. For instance, it can be difficult to get a remote team to collaborate on an affinity diagram, although there are tools like Lucidchart that might help simplify the process. It is also not particularly useful in cases where there are very few data items.

The first step of affinity mapping is listing out every data point from your research on individual cards or sticky notes that can be affixed to a board or wall. Typically, an affinity mapping session involves multiple team members and stakeholders taking part. When several perspectives are involved, it reduces the chances of any vital data being left out.

Make sure you write down points legibly and concisely for everyone to be able to read and understand. User quotes are great to have on affinity maps, don’t shy away from them! Allocate about 30-60 minutes for this step.

Up to this point in the affinity mapping process, participants of the research group operate alone — they write down individual data points on cards and stick them to a surface. Now, together, they will have to discuss each data point and decide what groups their notes belong to.

Group names can be created on the spot depending on the themes and patterns that emerge and your research goals. It is a good idea to first start with top-level categories and then create granular sub-groups as you go.^[2] This step should take you around 60 minutes.

It is quite normal to be left with notes that don’t seem to fit into any group. Sort them under the miscellaneous category and try to make sense of them towards the end of the grouping session.

Once you’ve sorted all data points into groups, go ahead and summarize each group in detail. You can use this time to draw connections between data items, categories, and sub-categories. You could also sort out these groups in the order of importance, depending on your goals, vision, and company values.

During the discussion, any knowledge gaps in your research will become apparent. This will allow you to ask the right questions and look for more specific data in the future.

The thing about affinity mapping is that it is a flexible process. Just because you’ve placed a card into a certain group doesn’t mean that it has to stay fixed there. You might realize during further discussion and analysis that it fits better into another group or that it even belongs to multiple groups. So be open to shuffling cards around even in the discussion and summary stage.

Affinity mapping will either help you answer your original research questions or make glaring problems obvious to you. It will then prompt you to discuss potential solutions and devise a plan of action. This can be in the form of concrete steps you can take to arrive at solutions or call for further meetings, discussions, or research.

When multiple problems or ideas emerge after your session, get your team to vote on prioritizing them based on how urgent or important they are. A successful affinity mapping session is one that is concluded with actionable insights.