Incrementality Testing
A measurement method where a marketer makes a specific change to a Test Group, as opposed to the Control Group, in order to determine the incremental value of a marketing strategy or tactic. The method is a popular alternative to using cookies and consumer data tracking.
What is incrementality testing?
Incrementality testing relies on a test-and-learn framework, where marketers use test and control groups to compare the results of marketing campaign elements (channel, message, ad, etc.) against each other. By measuring these elements, you can understand the incremental value a specific element has on the performance of your overall marketing mix.
How does incrementality testing work?
To get started with incrementality testing, you’ll first need to decide what to test. A few examples include: adding one new channel to your mix, investing more in a particular channel, spending less in one area, updating creative, and targeting a new audience. To keep everything running smoothly, you’ll want to set up a project tracker spreadsheet, meet regularly with the team working on the testing strategy to review results and next steps, and consider investing in an incrementality testing platform.
How to calculate incrementality
Incrementality is calculated by comparing the results of a test group that receives a marketing treatment with a control group that does not. The difference in performance between the two groups represents the incremental impact of the marketing activity being tested.
For example, if a test group exposed to an advertising campaign generates 1,000 conversions and a similar control group generates 800 conversions without seeing the campaign, the campaign’s incremental lift would be 200 conversions.
A simplified formula is:
Incremental Lift = Test Group Result − Control Group Result
Marketers can use incrementality testing to measure a wide range of outcomes, including sales, conversions, app installs, website visits, customer acquisitions, and revenue. The key is ensuring that the test and control groups are as similar as possible so that any difference in performance can be attributed to the marketing activity being measured rather than outside factors.
Why does incrementality testing matter?
As privacy regulations evolve and third-party cookies become less reliable, marketers need measurement strategies that can accurately demonstrate marketing effectiveness without depending on user-level tracking. Incrementality testing helps fill that gap by showing whether a campaign is actually driving results that would not have happened otherwise.
This distinction is important because not every conversion attributed to a campaign was necessarily caused by it. Some customers may have converted regardless of whether they saw an ad. Incrementality testing helps marketers separate correlation from causation, providing a clearer view of true marketing impact.
Why is incrementality testing effective?
Many marketers are turning to incrementality testing, which does not require cookies or tracking, as a replacement for multi-touch attribution. New innovations in AI and machine learning have made incrementality testing faster and less expensive, giving marketers near-real-time insights on how to target and make better spending decisions based on intelligence from their active campaigns.
What are the benefits of incrementality testing?
Incrementality testing helps you better manage your marketing budget by showing you campaign performance in real time, so you can decide where to pull back spending on underperforming campaigns and where to push more budget on campaigns that are seeing the best results.