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Incrementality Testing 101: A Simple Process to Validate Ad Effectiveness

by Kylie Carrasco •

Most brands have no idea if their ads are actually driving growth. They look at ROAS and assume their ad dollars are justified, but without measuring incremental lift, they’re just blindly guessing. Incrementality testing is how you cut through that noise and see if ads are truly making you money.

Here’s a basic 101 process for incrementality testing:

Step-by-Step Incrementality Test Process

  1. Pick a Channel
    Start with one high-cost channel, like Meta or Google.
  2. Turn Off Ads in 50% of Your Markets
    If your ads run in New York and California, pause them in California.
  3. Run the Test for 2–4 Weeks
    Give it enough time to reveal meaningful changes—two to four weeks is usually enough.
  4. Compare Revenue in Active vs. Paused Markets
    Check revenue from markets where ads are active versus those where they’re off.
  5. Calculate the Revenue Drop in Paused Markets
    The revenue dip in the paused markets is your incremental lift from ads.
  6. Assess Incremental ROAS (iROAS)
    Use the revenue gap between markets to measure true incremental ROAS.

Example: Measuring Meta Ads’ Incremental Impact

Say both New York and California bring in $1M monthly with Meta ads on. You turn off Meta ads in California, and after four weeks, California’s revenue falls to $700K. The $300K difference is your incremental lift from Meta ads. If you’re spending $100K monthly on Meta, that’s a 3x iROAS. Now, you know that the ads are adding $300k in value above and beyond what would have been generated without them.

Congratulations, you just validated the incrementality of Meta.

 

In reality, it’s a lot more complicated than this. But, I see a lot of brands try to go to the data-science 401 level with Bayesian methodologies, collinearity, blah blah. Unless you’re doing like $10M a year that’s not really necessary, and doing the above is better than nothing.

 

Sure, incrementality testing can get much more complex than this. Some brands immediately dive into advanced methods like Bayesian, causal inference, synthetic controls, on and on. But honestly? Unless you’re a business doing $10M+ a year, that’s not really necessary, and doing the above is better than nothing.

 

This basic test gives you clear results without a complex setup. Incrementality testing is about one thing: proving ads are worth their cost.

 

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