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Medium
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The Mystery of User Behavior and The Detective’s Guide to Product Analytics
- Product analytics help PMs to find insights by analyzing data points from dashboards and spreadsheets.
- User funnels, similar to a suspect's trail of footprints in a crime scene, show how users move through an app and help PMs to identify where users lose interest.
- Trends in metrics are important to interpret and spot areas of growth or attention. Trends also help PMs to find out the "why" behind the data points.
- Two main classes of indicators are leading and lagging indicators. PMs should focus on leading indicators for future performance, and keep an eye on lagging indicators for performance summaries.
- Red herrings, or false clues in data points, should be avoided by using metrics that align with product goals. Frameworks like North Star, OMTM or HEART help PMs to choose relevant metrics.
- A product's key metrics should be prioritized, starting with essential ones like uptime and error rates, followed by higher-level metrics like ease of use and user satisfaction.
- Identifying a product's "A-Ha!" moment, where users realize its value, can help PMs to design their onboarding flows to guide users to that moment.
- Product analytics isn't just about numbers, it's about finding the mystery of user behavior by following funnels, analyzing trends and focusing on accurate metrics.
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