212: Tobias Konitzer: The Causal AI revolution and the boomerang effect in marketing decision science

Tobi challenged marketing’s fixation on prediction. He has built highly accurate LTV models, but accuracy alone does not move revenue. Marketing is intervention. Correlation shows patterns; causality tells you what happens when you pull a lever. That shift reshapes experimentation, explains why dynamic allocation can outperform static A B tests, and highlights how self learning systems can backfire or get stuck in local maxima.More

182: Simon Lejeune: Wealthsimple’s VP of Growth on 2 keys to be a top 5% marketer

Simon Lejeune learned early that chasing small wins keeps growth teams stuck, a lesson that landed hard when Hopper’s CEO dismissed his price‑point test as a “local maximum” and pushed him toward ideas bold enough to reshape the business. That experience drives how he leads at Wealthsimple, where he tells teams to stop polishing the same hill and start climbing new mountains.More

176: Rajeev Nair: Causal AI and a unified measurement framework

Rajeev believes measurement only works when it’s unified or multi-modal, a stack that blends multi-touch attribution, incrementality, media mix modeling and causal AI, each used for the decision it fits. At Lifesight, that means using causal machine learning to surface hidden experiments in messy historical data and designing geo tests that reveal what actually drives lift. Attribution alone can’t tell you what changed outcomes.More

162: Rich Waldron: How to build and manage AI agents from a single, composable platform without coding

Marketing ops folks stand at a crossroads where iPaaS platforms and AI agents are colliding in crazy ways. Rich pulls back the curtain on what happens when workflows become agent “skills”: Imagine your carefully built automations transformed into autonomous assistants that diagnose tech issues, provision applications, and manage complex Salesforce campaigns without manual intervention. More