The PM’s Data Mindset: Practical Data Exploration with AI

​Product managers are expected to be data-informed — even when we’re not data analysts, don’t write SQL, and don’t have the luxury of waiting for “the perfect dashboard.” This event is about building the PM’s data mindset: how to scope a data task, validate assumptions, and use AI responsibly to get to clarity faster.

​We’ll explore this through two practical perspectives:

​First, a case study from Dima Yarovinsky-Yahel (VP Product & Design @ Loox): how he approached a feature where the feature itself is data - a request that required turning a data-heavy need into something shippable. He’ll walk through how he used LLMs to break down the problem, define what “MVP” means in a data-based feature, and fully develop an MVP.

​Then Nurit Lamy (Data Analytics Leader) will share practical frameworks that help PMs become more independent with data work: how to define the question behind the question, what to clarify before anyone pulls data, how to sanity-check results, spot gaps and bias, and make sure insights are trustworthy enough to drive product decisions.

​This meetup is for experienced PMs who:

• ​Make decisions with incomplete or messy data

• ​Need to scope data-related work clearly (with people or AI)

• ​Want practical frameworks to validate data and assumptions before acting