Incrementality
ConceptIncrementality measures the true causal sales an ad generated above and beyond what would have happened naturally without any advertising.
What is Incrementality, in plain English?
Imagine handing out coupons outside a pizza shop to people already walking in the door. They use the coupon, and your report claims 100% of those sales were "caused" by your coupon! Incrementality testing tests whether those customers would have bought anyway, proving true ad value.
Incrementality example
You run ads in 5 cities and turn off ads in 5 similar holdout cities. If the ad cities generate 25% more total sales than the holdout cities, that 25% difference is your true incremental lift.
Common Incrementality mistakes
Ad platforms take 100% credit for brand search terms (e.g. users searching for your exact company name). While the ROAS looks astronomical (15x+), the incrementality is often near zero because those customers were already looking for you.
What is a good Incrementality?
Incrementality is expressed as the share of attributed conversions that would not have happened without the ad. There's no universal good figure, but expect brand search and retargeting to show far lower incrementality than prospecting — and measure it with tests, not platform dashboards.
Incrementality FAQs
How do you measure incrementality?
With a controlled test: hold out a group — geographies, audiences or time periods — that doesn't see the ads, and compare its sales with an exposed group. Platform conversion-lift studies, geo holdout tests and simple on/off pause tests are common approaches.
What is the difference between incrementality and attribution?
Attribution decides which touchpoint gets credit for a sale that happened. Incrementality asks whether the sale would have happened without the ad at all. A campaign can collect plenty of attribution credit while adding few incremental sales.
Can a small team test incrementality without a data scientist?
Yes. A pause test on one channel, or a geo split comparing matched regions, read against your own order data over a few weeks, gives a usable estimate. Keep everything else constant while the test runs.
- Incrementality vs. Last-Click for Teams Without a Data Scientist
- What “How did you hear about us?” is really for
- Half your conversions are estimates.
- Frequency, Reach and Saturation: Reading the Curve Before You Scale Spend
- Retargeting steals credit from prospecting (and how to prove it)
- View-through conversions: when to count them, when to ignore them
- AI Max turned on: new demand or rerouted exact match?
- Where your PMax money actually goes
- ChatGPT is sending you customers, and GA4 calls them Direct
Last reviewed October 3, 2026.