Google Ads, YouTube, agentic AI, and marketing strategy — written to connect dots, not confirm what you already know. The essays here feed the operating manuals in the Frameworks collection and the live experiments in the Lab.
Every marketing KPI in common use measures activity, not decisions. The gap between the two is where margin and competitive advantage quietly leak out of the modern enterprise — and it has been that way since the discipline was instrumented. Agentic AI is the first technology that makes the correction operable, not aspirational.
"Marketing KPIs and business KPIs have been structurally misaligned since the discipline was instrumented.
AI is what makes the correction operable."
AI Max for Search, the SQR shift, and the prose-input change ship together this quarter. One prediction layer, three surfaces, one sealed auction — and one decision every marketing team has to make before September.
Consumer FinTechs run on Cost Per Lead. The business runs on funded, retained accounts. The space between is where neobanks burn working capital chasing the wrong applicant — every quarter.
Retail marketing runs on Cost Per Click. The business runs on retained margin per cart. The Retail Decision Stack rewrites the KPI hierarchy for an AI-mediated funnel — for DTC, big-box, and CPG.
Health plans run their marketing on Cost Per Enrollment. The business runs on member-years. That gap is where the budget gets spent on the wrong audiences, the wrong creative, and the wrong channels — every AEP, every cycle.
The five signal layers that determine whether Performance Max compounds or fails — and the audit checklist most teams skip.
Default attribution, modeled conversions, consent-mode gaps, and the specific places your data is over-crediting some channels and burying others. With the audit checklist.
Google's open-source Marketing Mix Model isn't just a measurement tool. It's the confidence infrastructure that lets enterprise teams finally stop defending budgets with broken attribution.
A marketing decision doesn't stop at marketing. It moves through CAC, LTV/CAC, working capital, and the multiple the market pays — the chain most teams never draw end-to-end.
Most organizations are running Google's products as separate channels. The ones pulling ahead are running the whole system.
Beyond prompts and chatbots — AI that acts, decides, and executes across systems. What this means for how marketing gets done.
Most teams are locking their workflows to a single model. That's the wrong bet. Here's how to build infrastructure that survives the next model shift.
In 2016, AlphaGo played a move no human would make. That single moment explains where AI and marketing are heading — and why most teams are still playing the old way.