Maximizing advertising ROI: Climbing the ladder of incrementality in ad measurement

In today's digital world, advertising is an essential aspect of any business's marketing strategy. Ads help reach potential customers and increase brand awareness—and creating effective ads is often the result of understanding what’s working and what’s not. And yet, many of the tools advertisers rely on to optimize their marketing investments don’t capture the true impact of their advertising.

That’s because measuring the effectiveness of ads and campaigns can be complex, and many businesses default to measuring correlation—not causation. Correlation does not reliably capture cause and effect, so relying on such measurement tactics can lead businesses to misunderstand the impact of their campaigns. This is where a concept called incrementality comes into play.

Incrementality is the degree to which a measurement approach can estimate the impact of your marketing. The more incremental an approach is, the closer it is to measuring actions that occurred because of your marketing, rather than actions that would have occurred regardless. For example, an incremental measurement method could help differentiate between sales that occurred as a result of a consumer seeing your ad from ones that came from a loyal customer who was planning to buy anyway.

The payoff of employing more incremental measurement techniques is more accurate forecasting and greater sales for the same marketing dollars. So, how do you know which measurement tactics are incremental and which are not?

At Meta, we think of incrementality as a ladder. To help advertisers climb that ladder, we've collaborated with MMA Global on a series of whitepapers: “The What and Why of Incrementality,” “The Ladder of Incrementality,” and “Climbing the Ladder of Incrementality.” The series explores a variety of topics, including how to improve the incrementality of the measurement methods you use through techniques like calibration or how to nurture an incrementality culture within your own organization.

At the top of the ladder are techniques like randomized controlled trials that organize your consumers into treatment and control groups, allowing you to see the precise difference in outcomes between consumers who saw your marketing and those who did not.

In the middle of the ladder are quasi-experiments that aim to estimate the effect of a marketing campaign while controlling for extraneous factors by using statistical techniques or interventions. Towards the bottom of the ladder are non-incremental models, which do not explicitly aim to estimate the effect of a campaign beyond a baseline behavior. For example, it’s common for advertisers to track conversion counts, but those counts don’t explain how many people would have converted without seeing your ad.

The goal is to continue to climb the ladder when possible, but sometimes you aren’t able to due to the constraints of a specific platform or campaign. Other times, you may have your hands or feet on multiple rungs, since no one tool or tactic will be right for all your measurement needs. That’s just the nature of measuring marketing success.

Ultimately, using more incremental advertising measurement can help businesses to get the most out of their advertising budgets and drive better business results.

Access the whitepapers here.