Insights on product analytics and data modeling.
Semantic layers, user behavior models, and the statistics behind the metrics F2P teams live by.
Measuring Monetization Impact on Engagement: A New Approach
The mDAU/DAU ratio isolates the real effect of monetization on engagement from selection bias, and it is measurable without building a model.
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Modeling User Behavior Metrics in Freemium | Part 2
A dual-propensity model of engagement and payment behavior that reproduces real payer retention and cohort conversion curves with two parameters.
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Modeling User Behavior Metrics in Freemium | Part 1
Paying users retain far better than non-payers. A simple random-flagging experiment shows how much of that gap is selection bias rather than psychology.
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Why User-Centric Analytics Beats Event-Based Tracking
Discover why traditional event-based analytics may be holding back your product insights. Learn how user-centric analytics can simplify metrics, improve performance, and align better with business goals.
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New Approach to Semantic Layer Modeling
Why Asemic builds the semantic layer from business logic down: define metrics in business terms and let the application maintain the physical model in your warehouse.
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Data Modeling: The Essential Foundation of Effective Data Analysis
Discover how data modeling shapes analysis outcomes and why it's crucial for deriving meaningful insights from your data.
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