Great product decisions start with understanding what users need — but in a world of infinite data, finding that truth is harder than ever. In this talk, we’ll explore how product managers can partner with machine learning to uncover deep user insights, not just dashboards full of noise.

You don’t need to be a data scientist to benefit from ML. I’ll break down practical use cases — from segmenting users based on behavior to predicting churn before it happens — that can elevate your product decision-making. You’ll learn how to ask the right questions, set up the right data pipelines, and evaluate ML outputs with a critical lens.

We’ll also discuss the limitations: when ML can mislead, and how to keep the human element alive in data interpretation. If you’re working with cross-functional teams that touch data, this session will help you become a more confident, insight-driven product leader.

Whether you're in fintech, SaaS, or consumer products, this talk will give you the tools to move from raw data to real direction — and build products that serve what users actually need.