Demand Gen campaigns have high visibility across YouTube, Discover, and Gmail. However, they pose a key challenge: the “attribution illusion.” You’ll often question whether reported conversions in the platform are truly incremental or if these users would’ve converted through search either way.
That’s why in November, Google launched asset uplift experiments, giving you the ability to measure the impact of Demand Gen creative through an A/B split test. This means you can replace assumptions with a clearer view of what’s actually driving incremental results.
Relying too heavily on creative instinct or default reporting can lead you down an inefficient path and divert valuable creative resources toward poor-performing assets. Using Google’s A/B testing capabilities helps you isolate the impact of individual assets and avoid that outcome.
Why attribution doesn’t equal incrementality
If a user views a Demand Gen ad on YouTube and doesn’t click but then searches for the brand and converts, Google may attribute partial or full credit to the Demand Gen campaign and creative. This attribution more so reflects correlation rather than causation.
Accurate measurement and the scientific method show the need to understand the scenario in which the creative isn’t shown. By withholding the test assets from a segment of the target audience, it’s possible to establish a baseline.
The difference in conversion rates or any primary KPI between the treatment group — those who were exposed to the ad — and the control group — those who weren’t exposed — shows the actual incremental lift the creative is driving.
Dig deeper: Why incrementality is the only metric that proves marketing’s real impact
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What you need before testing creative uplift
One common mistake is launching experiments without enough data to reach statistical significance. To avoid inconclusive or invalid results, make sure your campaign meets these prerequisites before setting up the test.
Conversion volume
Google recommends having at least 50 conversions across treatment and control arms during the experiment to measure lift accurately. If your primary conversion doesn’t receive this volume, consider optimizing the test around high-intent micro-conversion actions, such as “Add to Cart.”
Budget minimums
Experiments should run with continuous, uninterrupted spending. If your Demand Gen campaign is limited by budget and stops early each day, the control group data will be skewed.
The campaign must have a sufficient budget to run for at least four weeks, or until a statistically significant result is achieved.
Creative isolation
Test only one…
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