Case fainz: +17.2% true revenue uplift with PMax Non-Brand

Fainz is a growing D2C brand with high brand awareness, an environment in which Google Ads traditionally looks good. And that is exactly the problem:

• Brand traffic appears profitable in platform attribution.
• PMAX is favored in attribution.
• ROAS tells only half the truth.

The central question was: which Google campaigns really generate new revenue and which are overrated? It is a question many brands ask themselves. Only a few have the courage to measure the answer properly. Fainz wanted absolute clarity.

The approach: new revenue instead of platform attribution.

To make real impact visible, we used a geo-based incrementality framework. Not to “make the data look better” but to find out: which revenue is additional, and what would have happened anyway?

To do this:

• regions were activated selectively
• brand was deactivated completely
• PMAX was run exclusively as a non-brand setup
• real changes in sales were measured
• all results were statistically validated with p-values (<0.05)

We are not revealing any internal test logic or secret sauce, but the core is this: we measure behavior, not attribution.

‍

The results: Brand Search: strong numbers. No additional overall uplift.

Brand looked impressive, as it almost always does. But the analysis showed:

• apparent uplift: +16%
• p = 0.03 (the effect exists but adds no value)
• organic brand conversions rise as soon as brand is switched off
• PMAX prioritizes brand aggressively
• brand captures existing demand instead of creating new demand
• brand customers had already been paid for through other channels → no clear cost breakdown possible for Google brand campaigns (e.g. CPA)

Conclusion: brand is not a growth engine but a measurement artifact. Fainz is switching brand off permanently.

‍

PMAX Non-Brand: the only real growth driver.

As soon as PMAX ran without brand signals, the true picture emerged:

• +17.5% real incrementality
• p = 0.03 → not due to chance, with 95% confidence
• ~€20 CPO
• high share of new customers
• clean, undistorted effect
• measured conservatively (budget not exhausted)

Conclusion: PMAX Non-Brand is the only campaign type that demonstrably generates real, new additional revenue.

‍

Overall impact:

• +17.2% overall uplift
• p = 0.01

Almost all of the validated impact is attributable to PMAX Non-Brand. Brand does not contribute to scaling.

‍

What this means for Fainz: clarity instead of guesswork.

Fainz now knows:

• which campaigns drive growth
• which campaigns merely shift demand
• which campaigns are inefficient

A scalable Google setup:

• PMAX Non-Brand serves as the growth core
• brand stays deactivated permanently
• Shopping is tested separately in follow-up tests

‍

Marketing based on reality, not on ROAS.

Fainz’s decisions are now based on:

• real demand
• statistical validity
• real purchase paths
• robust business effects

Not on platform logic. Not on attribution bias.

‍

Why this is relevant for every D2C brand.

This case study shows a pattern we see in many accounts:

• platform ROAS overestimates performance, often massively
• PMAX reporting can be distorted by brand signals, which is why we separate brand and non-brand and test for incrementality
• without incrementality analysis, it is harder to optimize budgets for real business impact

Fainz has solved this problem in a structured, data-based and unambiguous way.

‍

Conclusion: brand shifts demand. PMAX Non-Brand works.

With a clean, statistically validated incrementality analysis, Fainz has a Google setup that:

• is profitable.
• is scalable.
• can be steered objectively.
• is based on real impact.