Details
Traditional experimentation is already hard. Now add AI: product changes ship faster, personalization increases the number of variations in the wild, and teams are expected to prove impact quickly across more segments, channels, and edge cases. In that environment, relying on slow, brittle data movement and disconnected analytics stacks makes it easy to fall behind, or worse, make decisions on inconsistent metrics.
In this webinar, we will show how running experiments directly on your warehouse helps teams keep pace with AI-driven change. You will see how warehouse-native approaches improve trust in results by using governed, up-to-date data and shared definitions, while enabling faster analysis at scale without copying data into separate systems.
Presenters:
Audrey Do
Product Manager
Alexander Bock
Advisory Director for Feature Management and Experimentation
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