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I suspect there's also a fear about the accuracy of self-reported data. If you ask a user if he does XYZ, he may say 'no', because of a myriad of reasons (misu
by hakfoo 5y ago
I suspect there's also a fear about the accuracy of self-reported data. If you ask a user if he does XYZ, he may say 'no', because of a myriad of reasons (misunderstood the question, embarrassed, not allowed to disclose, etc.), but if you instrument it up and see he clicks it 200 times a day, that's probably the truth.
The problem is that analytics in a vacuum are just as misleading as testimonial data, if not more so. "0.6% of users touvh XYZ and only use it for an average of 17 seconds per year" could mean that it's an unloved feature that can be sunset, or that it solves a single niche task very completely and perfectly, and ripping it out will cost those 0.6% of users five hours each to replace.
- skohan 5y agoI think there's also the risk of talking yourself into bad decisions with data as a justification. For instance, if you have a KPI to increase X, and making your UI harder to understand confuses users into doing X more often, from a data-driven perspective you've done the right thing, but you've made the product worse.