Why Loops - with Japna Sethi

Enjoy the Product Analytics Leaders' Meetup sessions in this "Masters Mini-Series". First up is Tom Laufer on how to deal with the correlation / causation problem by leveraging causal inference models.

In this session, we asked Casey Winters, the former CPO at Eventbrite, about what opportunity he sees in Loops for product and data teams. Casey shares a lot of valuable tips about how to approach experimentations, how to align product managers and data teams, and shares from his vast experience working in companies like Eventbrite and Grubhub. Enjoy.

When 18Birdies started working with Loops, the platform presented an opportunity to improve on 18Birdies’ pre-set KPIs with the “Goal Driver” analysis. This analysis automatically identifies the features that maximize a company’s KPIs using causal inference models, which enable you to get significant results with minimal traffic.

A Loops-empowered R&D Team pinpoints the specific code release behind a core KPI change

A customer's own dashboards indicated their A/B test experiment variant was losing. Fortunately, they looked at the Loops validation analysis. Ultimately, it drove a 12% lift in Conversion to Paid

This case study highlights that many firms may be losing money without knowing it. In this case, a customer of Loops avoided a $5M revenue loss by quickly identifying an issue before it impacted the majority of their client base.