When I first started working with product experiments, statistical terms like p-values felt more complicated than they needed to be. I’d see statements like, “The experiment has a p-value of 0.03,” and the immediate question was: “So, did the experiment work?” Not necessarily. Understanding p-values isn’t about becoming a statistician. For Product Managers, it’s about…

One mistake I’ve seen product teams make repeatedly is tracking everything. Every click, page view, button press, hover, scroll, and interaction gets captured. The analytics dashboard looks impressive, but when it comes time to answer a product question, nobody knows which events actually matter. More data doesn’t automatically create better insights. The goal isn’t to…

How to Read a Retention Curve Early in my product career, I used to look at retention as a single percentage. “30-day retention is 25%.” It sounded useful, but it didn’t tell me much about what was actually happening to users. Over time, I realized that the shape of the retention curve often tells a…

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.…

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…