Want to convey how bad a user experience is? Talk about the user’s emotion | by Kai Wong | Feb, 2024


User counts aren’t the most crucial thing to summarize: emotions are

A woman with her forehead resting on a laptop while seated. She looks defeated while sitting in the chair
Photo by Andrea Piacquadio: https://www.pexels.com/photo/woman-sitting-on-chair-while-leaning-on-laptop-3791136/

“There’s no point in fixing anything. I’d rather you rebuild this whole stupid application.” A user spoke bitterly, sounding like he’d given up on making things better.

We often see a wide range of emotions when we test with users. Whether banging the table in frustration or self-deprecating because they don’t understand, users often react to tasks differently.

However, we don’t often know what to do with this, so we often ignore this data. That’s a mistake I learned you shouldn’t make when designing personas of people who recently got a cancer diagnosis. People are emotional creatures: we can’t just design for them on their good days.

Showcasing your user’s emotions is often one of the most important things to do because it can be a critical step in getting your team to take action.

This is because we’re doing qualitative research, and talking about emotions is one of our strengths.

The ineffectiveness of user counts in research presentations

One of the first lessons I learned when learning Data Storytelling was to pay less attention to counting the number of participants who did something.

It sounds counter-productive: after all, isn’t it great to know that 4 out of 5 users did X or said Y? From your perspective, yes. However, several issues come up when you consider how your audience might interpret those things.

If you say 5/5 or 4/5 users ran into this issue, we can emphasize that this problem may be common.

However, how about if 3/5 users ran into a problem? Some of your team might want to interpret that as 60% of all users ran into this problem, but that’s different from how statistics works.

In addition, what if something critical happened to only 1/5 of the users? For example, you talked with four people aged 25–30 and 1 person aged 55. The 55-year-old might have uncovered some critical issues, but saying 1/5 users had trouble de-emphasizes your finding.


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