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

174: Joshua Kanter: A 4-time CMO on the case against data democratization

Joshua spent the earliest parts of his career buried in SQL, only to watch companies hand out dashboards and call it strategy. Teams skim charts to confirm hunches while ignoring what the data actually says. He believes access means nothing without translation. You need people who can turn vague business prompts into clear, interpretable answers.More

168: AI’s talent crunch: Marketing jobs on the brink and those set to thrive

At risk are campaign operators, generic content creators, and report-pulling analysts. Set to thrive are resident AI implementation experts who select worthy tools, data orchestrators connecting proprietary data to AI, product/customer marketers with genuine empathy, ethics guardians preventing bias issues, and localization specialists understanding cultural nuances.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