معلومات عن هذه الحلقة
Brett Gordon is a Professor of Marketing at Stanford University's Graduate School of Business. He sat down with Haus’ Chief Scientist Joe Wyer, CMO Olivia Kory, and Head of Science Strategy Phil Erickson to discuss his landmark research around advertising measurement, including his “close enough” paper and “predictive incrementality with experimentation” (PIE) paper. (Both are essential reading around Haus — in fact, we hand it out to new hires.)
In this episode, they dig in to:
Brett’s background (1:04)
Brett’s landmark “close enough” paper (5:09)
Why marketing data is so bad (15:45)
Brett’s “Predicted Incrementality by Experimentation” (PIE) paper (20:09)
What marketers can learn from the PIE paper (24:34)
Attribution is biased…but can we learn from that bias? (28:30)
Generalizing PIE using experiments (31:06)
About Brett:
Brett Gordon is the Robert A. Magowan Professor of Marketing at Stanford University’s Graduate School of Business. His research focuses on pricing, advertising, promotions, retailing, and experimentation, using methods from causal inference, machine learning, and empirical industrial organization. He partners with companies to measure and enhance marketing effectiveness. His recent work examines digital advertising measurement methods while developing new evaluation approaches.He served as a co-editor at the Journal of Marketing Research from 2023 to 2026 and is the co-creator of the “How I Wrote This” podcast, which goes behind the scenes with authors to understand how great academic marketing papers came to be. Listen on Apple or Spotify.
About Haus:
Haus is the causal marketing measurement platform built for performance-driven brands and enterprises. From GeoLift incrementality testing to Causal MMM, Haus helps marketing and finance leaders understand what's actually driving growth — so they can make smarter business decisions.
🔗 Learn more about Haus: https://www.haus.io
📅 Book a demo: https://www.haus.io/demo
💡Follow Haus on LinkedIn: https://www.linkedin.com/company/haus-analytics
