Can AI accurately predict marketing incrementality without running a randomized controlled trial?
In this episode, Pranay Piyush and Sundar Swaminathan break down a new marketing science paper introducing Predicted Incrementality by Experimentation (PI) and discuss what it means for marketers, ad platforms, and measurement teams.
They cover:
How PI predicts incrementality using historical experiments Why the model achieved an 0.88 R² Whether AI can reduce the need for randomized controlled trials (RCTs) What this means for Meta's incremental attribution Why benchmarks can be misleading Which companies can benefit from predictive incrementality today Why RCTs remain the gold standard
If you're a CMO, growth leader, marketing scientist, or performance marketer, this episode offers a practical breakdown of one of the most interesting developments in marketing measurement this year.
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