Demand Gen Drove 3.3x More Revenue Than Reported
Incrementality testing proved Demand Gen was outperforming its CPA target—and worth scaling.
The Challenge
Platform Reporting Said “Underperforming.” The Business Question Was Bigger.
This multi-location entertainment and retail brand has aggressive growth goals and zero room for wasted media spend. Every dollar needs to drive incremental revenue—not just look good in-platform.
They were testing Google Demand Gen as a new channel. Based on Google Ads reporting alone, the channel appeared to be underperforming, coming in above the target cost per purchase.
But we had a different hypothesis.
Because Demand Gen relies heavily on YouTube placements, we suspected click-based attribution was significantly under-reporting the channel’s true impact. The risk was clear: pulling back on a channel that was actually driving meaningful, incremental revenue.
The Solution
We Tested Incrementality Instead of Trusting Click-Based Metrics
We cut through attribution noise with incrementality testing. Silverback designed and executed a scale-up matched market test to measure Demand Gen’s real impact:
- Increased Demand Gen budget in test markets
- Held spend constant in matched control markets
- Kept the rest of the media mix unchanged
- Ran the test over a focused two-week period
Instead of relying on platform-reported conversions, we measured actual revenue lift between test and control markets to isolate true incrementality.
Their Words, Not Ours
The Results
Incrementality Testing Unlocked a Scalable Revenue Channel
The results told a very different story than the platform metrics. Demand Gen drove 328% more revenue than Google Ads reported. As a result:
- The channel was actually well below the target cost per purchase
- Demand Gen was confirmed as a true incremental revenue driver
- The brand gained confidence to increase investment in the channel and scale revenue
Silverback helped the team make a smarter budget decision—grounded in real business impact, not misleading platform data.
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