Customer interviews say one thing, usage data shows another, and both sides feel confident in their interpretation. The team is split on which direction to follow for the next iteration. When qualitative and quantitative data conflict like this, what do you prioritize?
1
Quant lies/misses context. I’d consider the questions asked and the qualitative insight provided and as long as the context/question was clear go with that
Quantitative data is usually more accurate IMO. A lot of people have a “feeling” about how users behave or about the importance of certain features, but the actual usage data will tell you the truth. I had a feature B that paired with feature A and was told that I couldn’t launch a refreshed version of feature A without also releasing feature B at the same time because they were so important and “always” used together. The data showed that Feature B was only used with feature A around 5% of the time. I refreshed feature A and had 60% adoption of the new version over the next 3 months until I finished feature B. If I had listened to my qualitative data, I would have missed out on a lot of adoption during the busiest time of the year. My boss was happy I “trusted my instincts and followed the data” over all of the scary stories that clients told us going into the effort.