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GTM Strategy, Measurement & AI Workflows
Design the operating workflows that connect planning, campaigns, reporting, revenue data, attribution, MMM, and AI-assisted execution.
This is the strategy and operating layer: how growth teams decide what to measure, how campaigns move through QA, how reporting informs budget decisions, and where AI can safely assist the revenue workflow without amplifying bad data.
Related field notes
All published writing currently classified under this system layer.
Google Ads API v25 is live. Check your lifecycle goals, Demand Gen settings, and reporting queries.
Google Ads API v25 adds Loyalty Retention Goals, updates New Customer Acquisition Goals, expands YouTube reporting, and changes several older fields and resources. If your reporting pipeline or agency tooling touches Google Ads data, review this before something quietly breaks.
How to Build a Measurement Roadmap for a B2B SaaS Company
A practical framework for building a b2b saas measurement roadmap that reconciles marketing attribution, GA4, and finance-approved pipeline numbers.
Multi-Touch Attribution vs MMM: Which One Do You Actually Need
Compare multi-touch attribution and marketing mix modeling head to head to figure out which measurement approach fits your spend, channel mix, and reporting timeline.
Why Your Marketing Team and Finance Team See Different Revenue Numbers
Marketing and Finance report different revenue every month. It's not a communication problem—it's a measurement architecture problem with three specific causes and a concrete fix.
The Retargeting Fallacy: A Case Study in Incrementality vs. Attribution
High ROAS is often a signal of selection bias, not efficiency. In this case study, I break down how a luxury retailer's "profitable" retargeting campaign was actually a negative-leverage tax on their most loyal customers—and how we proved it with a simple RCT.
When Perfect Correlation Breaks Attribution: Why Most MMMs Randomly Assign Credit
When ad channels scale together, standard regression models fail to distinguish cause from effect. This post explores how correlated spend leads to random credit assignment and why you need randomized experiments—not just better models—to untangle the signal
Why I Write Long-Form Technical Content Instead of LinkedIn Posts
LinkedIn rewards recycled takes and AI-generated slop. I'd rather write the technical breakdowns that actually help someone fix their tracking stack.
