The Basic Mechanism
Conversion Lift uses a randomized controlled trial methodology to measure the true impact of your advertising. Here's the process:
When you start a test, Meta will automatically divide your target audience into two groups:
Test Group: People who can see your ads
Control Group: People who won't see your ads (also called the holdout group)
The groups are created using randomization to ensure they are statistically similar in terms of:
Demographics
Geographic location
Past behaviors
Other relevant characteristics
Throughout the test period, Meta tracks conversions using your selected Meta Pixel.
The difference in conversion rates between these groups represents the "lift" - the true incremental impact of your advertising. This shows you which conversions wouldn't have happened without exposure to your ads.
Creating a Conversion Lift Test
Prerequisites
You must have:
An active Meta ad account
A campaign with $5,000 USD minimum spend in the past year
At least 500 optimized conversions
Proper Pixel event tracking setup
Step-by-Step Setup Process
1. Navigate to the Meta Attribution Page
2. Select the Experiment Column(s)
Navigate to Select Columns and either:
Select Experiments preset columns
Or find Experiment inside Customize Columns
3. Configure your Conversion Lift Test
Select the campaign to test
Name the Ad Study
Select the Pixel that aligns with the primary conversion event you want to measure
Select your preferred holdout group and test duration:
Holdout group: The percentage of audience that won't see your campaign
Test duration: Time period to run the test with reduced campaign reach
Choose either:
Optimize for Speed: Faster results, with potential for higher negative impact on revenue
Balanced Approach: Recommended for new users
Minimize Revenue Impact: Slower results, with least impact on revenue, but results might be less statistically significant
Manual Configuration: Customize your holdout and duration
4. Launch & Monitor
Review your configuration settings
Click "Run Test" to begin
Monitor results in the Experiments columns
Wait for the test to gather sufficient data for statistical significance. It is recommend to let the test finish running, but you can stop the test if you are satisfied with the results.