Articles exploring data quality through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
3 articles
How AI-powered anomaly detection catches Sample Ratio Mismatch, traffic quality issues, and instrumentation errors in real-time before they invalidate experiment results and lead to costly false positives.
Data discrepancies between platforms, the observer effect in measurement, and how to build a single source of truth when every tool tells a different story.
Why tracking plans fail, how naming conventions compound, and the hidden cost of retrofitting analytics. The architectural decisions that determine whether your data is an asset or a liability.