Case Study: WHOOP achieves faster AI/ML forecasting and lower data costs with Snowflake

WHOOP Improves AI/ML Financial Forecasting While Enhancing Members’ Experiences

WHOOP, a fast-growing health and fitness company, needed a data platform that could keep up with rapid member growth, expanding international operations, and a large increase in data volume. Before Snowflake, its data was spread across a warehouse, data lake, and production databases, making governance, scaling, and forecasting difficult and costly, especially for a small data team.

Snowflake helped WHOOP centralize data on a scalable, secure platform with Snowpark, Horizon Catalog, role-based access control, and support for Apache Iceberg tables. The company also gained clear cost visibility through Snowsight dashboards and reduced operational burden, improving feature development and achieving 3x faster financial forecasting with a new AI/ML model built using Snowpark.

WHOOP

Matt Luizzi

Director of Business Analytics