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What is Incrementality Testing (w/ Calculations & Examples)

What is Incrementality Testing and How to Measure Incrementality?

  • FAQ
  • Incrementality
  • What is Incrementality Testing and How to Measure Incrementality?
3 minute read

What is Incrementality Testing?
Incrementality Testing creates an experiment which systematically withholds media channel exposure to a representative subset of users (the control group) while maintaining normal media channel exposure to the broader user set (the test group). If the control group is both sizable enough to be statistically significant and selected at random such that they are broadly representative of the user base, then the media channel’s incremental contribution can be determined by the difference in business outcome (conversion, revenue, profitability, etc.) between the test and control groups.

 
Incrementality Testing is sometimes referred to as Incremental Sales Lift or Uplift Modeling or A/B testing.
 
Difference between Incrementality and Lift
  1. “Incrementality” indicates the portion of Last Touch conversions that were truly driven by that Media
  2. “Lift” indicates the increase to the overall business that these Incremental conversions represent
Difference between Incrementality vs Lift

 

 

Incrementality testing, when executed properly, can account for the pixel related blindness that occurs when trying to use MTA to measure the effectiveness of Walled Garden media.

 
How Do You Calculate Incrementality?
In general the control group should represent a minimum of 10% of the total test and control reach. The test group will receive your ad, media in question; the control group will not receive the ad message. There are multiple ways to build a control audience. Some examples are:
 
  1. Flight a placebo ad or PSA ad (PSA is Public Service Announcement ad or a generic irrelevant to your business ad) to an exact replica or mirror audience of the exposed audience.
  2. Hold out a subset of the target audience and suppress from the ad exposure.
  3. Programmatic executions have counterfactual bid loss data for the target audience that did not win the media auction.
 
In order to calculate incrementality, we want to calculate conversion difference between the test group vs the control.
 
Incrementality Calculation Formula
 
(Test Conversion - Control Conversion) / (Test Conversion) = Incrementality
 
Incrementality Test Calculation Example
Your test group saw 1.5% conversion whereas your control group saw a 0.5% conversion. The control data suggests that without any media exposure, you would have seen a 5% conversion. (Keep in mind that conversion could mean leads, sales, profit; whatever metric that is important to your business).
 
So (1.5% - 0.5%) / 1.5% = 66.7% incrementality in conversions
 
Incrementality is volatile and it is important to look at it longitudinally over time within business context. Statistical significance has two primary variables: difference in conversion rates (%CR) and sample sizes. The larger the difference in conversion rates, the less sample you need. As a general rule, we like to see a control reach > 10% of the total test and control reach.
 
What Techniques Measure Incrementality Marketing Channels
Incremental sales driven by a media tactic is calculated using advanced marketing measurement techniques. There are 3 major types of advanced marketing measurement techniques.
 
Why is Incrementality Testing Needed?
Advertising where there are a lot of impressions but not immediate action like a click has brand value which ultimately leads to conversions or sales. Channels such as online display, video/YouTube, Facebook, TV, direct mail all provide impressions, impact but it’s not always measured at the click or direct response level. You can read more about the following channels here:
 
Measured Incrementality Testing
Measured provides incrementality measurement and testing with ease and speed. We are already plugged into 100+ media platforms which allows us to run 100s of audience-level testing with quick set up. Find out your incrementality across your media channels. Learn more here

Author

Trevor is a pioneer and expert in the cross-channel attribution category.