NEW WHITEPAPER: How to Design a Geographic Randomized Controlled Trial
Download the whitepaper here (no registration required).
After years of advocating for better advertising measurement, I'm excited to share a comprehensive guide that doesn't just explain WHY geographic RCTs are superior for measuring true incremental ROI, it shows exactly HOW to implement them.
This 50+ page whitepaper includes:Step-by-step design frameworks for "Rolling Thunder" and other experiment designs
Detailed Python code examples for randomization, analysis, and power calculations
Statistical methodologies that deliver unbiased, transparent, replicable results
Implementation checklists to ensure experimental integrity
Real-world case studies demonstrating the approach in action
For too long, marketers have relied on observational and quasi-experimental methods like matched market tests, synthetic controls, and attribution models, which tend to systematically overstate performance. As I've written previously, these approaches might be "customer pleasing," but they're leading to billions in misallocated ad spend.
The truth is that geographic RCTs aren't comparatively difficult or expensive to implement, they're just unfamiliar to many practitioners. This guide demystifies the process and provides everything you need to start measuring true incremental impact.
Download the whitepaper here (no registration required).
If you're responsible for major advertising investments and want to know what's really working, this is your roadmap to better measurement and better results. For questions, training or support implementing these techniques, please reach out. I'm always happy to discuss how this methodology can transform your measurement approach and marketing effectiveness.
#MarketingMeasurement #Incrementality #ExperimentalDesign #AdvertisingEffectiveness #DataScience #iROAS