1. How did this exercise help you build empathy with prospective users?

This exercise challenged us to translate simple comments into user needs, frustrations, problems or desires. Instead of starting from pre-established, general statements (e.g., Some people like to feel like a local when they travel) we began the other way around, going from specific points or comments to more general insights. With the affinity diagram, you can get a better understanding of central themes. By starting from specific issues (e.g, I avoid tourist traps, I like to talk with locals, I love traditional food, I like to feel at home when I travel, I don´t use travel guides,etc.), you can

imagine how and why a user feels. What things are important for them in that particular context, what do they value, what things they like or dislike. You can put yourself in their shoes, and maybe you even feel identified with some of the issues they raise. With such a level of detail, you understand better their behaviours and build empathy.

2. How did the clustering of information help you understand user needs?

By clustering, you start seeing the “bigger picture” and discovering key insights. It helps the designer realise that by clustering a set of comments or issues (affinity notes) he/she can “find” unmet needs, something the user values in that context or a problem that could be solved or something to be improved. Starting with issues that might seem trivial or unimportant, you start finding key trends and insights on users needs and behaviour.

3. What was challenging with the technique?

The first challenge was that some of the yellow labels were a little ambiguous or confusing for other members of the group. Getting to a shared understanding on how to classify the affinity notes was also challenging. Especially because you have to find a general insight that captures the most important points, without being too abstract. I think that time was also an issue, so for the next time, it would be good that we read the interviews before (even twice), to be able to write as many affinity labels as possible and to get a better understanding of the user needs and behaviours.

 

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