Demand Gen Drove 3.3× 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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