Marketing measurement, attribution & decision science
Practical guides for CMOs, founders, and marketing leaders in e-commerce, DTC, and retail: evidence-based insights on attribution, incrementality, and decision science.
Geo Holdout Testing: A Step-by-Step Guide for E-Commerce Brands
Geo holdout tests answer the question attribution dashboards can't: does your ad spend cause revenue? This guide covers market selection, test design, runtime, and reading the results, with no data science team required.
The Platforms Grading Their Own Homework: Why Your Attribution Data Is Structurally Broken
A peer-reviewed paper from NeurIPS 2025 formally proves what performance marketers have suspected for years: the mechanism that decides which of your ad platforms gets credit for your conversions is mathematically designed to be gamed.
Incrementality Testing 101: What Every E-Commerce CMO Needs to Know
Incrementality is the question every marketing team should be asking: would these customers have converted without our ads? Here's how to find out, without a data science team.
The A/B Test You're Running Is Wrong: A Guide to Statistical Power
Most A/B tests stop too early, run with too little traffic, or declare winners on noise. Here's how to design tests that tell you something true.
CAC Reduction: The 4-Step Framework That Cut Acquisition Costs by 35%
A step-by-step breakdown of how we helped one DTC brand identify and eliminate non-incremental spend, reducing CAC by 35% without cutting revenue.
Marketing Mix Modeling for DTC Brands: A Practical Guide
MMM was once only accessible to large CPG companies with dedicated data science teams. Here's how modern DTC brands can run it with smaller budgets and faster timelines.
How to Audit Your Marketing Data Stack (Without a Data Engineer)
Most e-commerce brands have significant gaps in their measurement setup without realising it. This checklist shows you where to look, and what broken data costs you.
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