How Ridge Uses Incrementality to Cut Waste and Scale What Works
OPERATORS · with Austin Harrison · June 3, 2026 · 72 min
Summary
This episode challenges conventional wisdom in ecommerce marketing measurement, specifically around incrementality testing. It provides actionable insights for ecommerce operators on how to accurately measure ad spend effectiveness, optimize campaigns across platforms like YouTube and Meta, and avoid common pitfalls that lead to wasted budget and inaccurate data. The discussion emphasizes the importance of clean test environments and layering incrementality with other attribution models for a holistic view of performance.
Key takeaways
Don't rely solely on in-platform data; layer incrementality testing with MTA to uncover hidden opportunities, as Ridge did with YouTube spend where in-platform metrics would have showed underperformance.
Prioritize clean test environments for incrementality tests. As Katy Mimari learned, a "botched first test" due to noisy conditions can render weeks of data useless.
For scaled campaigns on Meta, consider shifting budget to upper-funnel initiatives. The episode highlights how this strategy is outperforming conversion campaigns for fast-growing brands.
Regularly scrutinize your incrementality testing methodology; longer tests aren't always better, and holdouts aren't interchangeable. Focus on robust experimental design to ensure valid results.
Creative strategy is a key differentiator for top-performing ecommerce brands in 2026; continuously test and optimize your ad creatives to stay ahead in a competitive landscape.
Is your incrementality testing giving you accurate data or are you burning budget on a broken signal? Austin Harrison (CEO, Northbeam) joins Sean Frank (CEO, Ridge) and Katy Mimari (CEO, Caden Lane) to challenge the most repeated advice in ecommerce measurement: that longer tests are always better, holdouts are interchangeable, and incrementality alone is enough to make media decisions. They break down when a growing brand needs incrementality versus MTA, and how running tests inside a noisy environment can produce weeks of data worth nothing. Sean pulls from Ridge’s own results to show how layering incrementality on top of MTA unlocked YouTube spend that in-platform data never would have justified, while Katy’s botched first test proves clean test conditions matter as much as the tool itself. They also dig into why moving up funnel on Meta is outperforming conversion campaigns at scale, and what separates the fastest-growing ecommerce brands in 2026 on creative. Powered ByFulfilhttps://bit.ly/3pAp2vuSaras Analyticshttps://bit.ly/9OP-YtdescAftersellhttps://9ops.co/4i3bb5Richpanelhttps://9ops.co/richpanelNorthbeamhttps://www.northbeam.io/Postscripthttps://9ops.co/postscriptOperators Newsletterhttps://9operators.com/
What does this episode say about analytics & attribution?
Don't rely solely on in-platform data; layer incrementality testing with MTA to uncover hidden opportunities, as Ridge did with YouTube spend where in-platform metrics would have showed underperformance.
What does this episode say about paid acquisition?
Prioritize clean test environments for incrementality tests. As Katy Mimari learned, a "botched first test" due to noisy conditions can render weeks of data useless.
What does this episode say about dtc strategy?
For scaled campaigns on Meta, consider shifting budget to upper-funnel initiatives. The episode highlights how this strategy is outperforming conversion campaigns for fast-growing brands.
What does this episode say about analytics & attribution?
Regularly scrutinize your incrementality testing methodology; longer tests aren't always better, and holdouts aren't interchangeable. Focus on robust experimental design to ensure valid results.
What does this episode say about analytics & attribution?
Creative strategy is a key differentiator for top-performing ecommerce brands in 2026; continuously test and optimize your ad creatives to stay ahead in a competitive landscape.
