Data Tech 2026

Your model is lying to you. Not intentionally—but somewhere in your company, a model is telling you something matters when it doesn't. This talk exposes the gap between correlation and causation in product analytics, and shows you how to think causally about product decisions. Using two real-world case studies, we'll walk through why feature importance misleads you and how to design experiments that isolate true causal effects. Learn the framework that turns data scientists into product strategists.