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Sampling Bias in Product Research
Early in my product career, I assumed that talking to 10 or 15 customers would give me a reasonable picture of what users wanted. Then I learned an uncomfortable lesson: the people you talk to can matter just as much as what they tell you. If your sample doesn’t represent the broader user population, even…
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Qualitative Research: Understanding What the Numbers Can’t Tell You
Early in my product career, I spent a lot of time looking at dashboards. Usage was up. Conversion had improved. Retention was moving in the right direction. On paper, everything looked fine. Then we spoke to customers. The story wasn’t quite as positive. Customers were completing the workflow, but many found parts of it confusing.…
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Stop Segmenting Customers by Who They Are. Start With the Problem They Need Solved
For a long time, customer segmentation seemed straightforward. Industry. Company size. Job title. Location. Age. These categories are easy to collect and even easier to put into a spreadsheet. But while working on products, I’ve found that these labels often tell us less than we expect. Two customers can have the same job title, work…
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Engaged vs Disengaged Users: What Your Product Data Is Really Telling You
One of the first things I learned about product analytics is that an “active user” isn’t necessarily an engaged user. A customer might log in every day but barely use the product meaningfully. Another might log in twice a week and complete everything they need. If we simply look at login frequency, we can easily…
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Your Most Active Users Aren’t Always Your Power Users
One of the first things I used to look at when analyzing product usage was frequency. Who logs in the most? Who spends the most time in the product? Who uses the most features? It seemed logical to assume that the most active users were also our most valuable users. Over time, I realized that…