Why Marketing Attribution Models Need Counterfactuals

Lucas and Luna explore why traditional attribution models—even multi-touch—fail to answer the most critical question in marketing analytics: what would have happened if you hadn't run that campaign at all? They dive into the concept of counterfactual reasoning, using concrete examples from e-commerce and B2B SaaS. Lucas explains how companies like Amazon and Booking.com use holdout groups and synthetic control methods to isolate true campaign incrementality. The episode breaks down the difference between correlation and causation in marketing data, and why relying on attribution alone can lead to budget misallocation. Listeners learn one practical framework for building counterfactual tests into their own measurement stack—without needing a PhD in statistics. Perfect for marketers and analysts tired of attribution models that overcredit channels and underdeliver insights. #MarketingAnalytics #AttributionModeling #Counterfactuals #IncrementalityTesting #MarketingMeasurement #CampaignAnalytics #DataDrivenMarketing #CausalInference #HoldoutGroups #SyntheticControl #Amazon #BookingCom #B2BSaaS #EcommerceAnalytics #ROIMeasurement #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo