Gauge Conversion Lift with Holdouts
A description of Primer's Conversion Lift Analysis, a new feature in Beta
Beyond raw conversions, the Overview helps you understand whether marketing exposure actually influenced outcomes.
Conversion Lift measures how much more likely companies that were exposed to your marketing are to convert compared to similar companies that were not exposed.
This allows you to evaluate the true impact of your audience and marketing strategy, not just volume of conversions.
If the Primer Pixel is not connected, lift analysis will not be available.
Within the ICP section, you can toggle between
Conversions – shows specific conversion activity
Lift Analysis – shows Conversion Lift
What is Conversion Lift Analysis?
Conversion Lift Analysis is a feature designed to help you measure the true impact of your Primer-powered campaigns. It uses classifies audience records into two key groups:
Exposed Group: Records with a high likelihood of matching to ad platforms, likely to have seen your ads.
Control Group: Records with a no chance of matching, serving as a holdout baseline as they won’t have seen your ads.
By comparing the conversion rates of these two groups, you can determine the incremental lift in conversions attributed to your ads—a concept known as incrementality.
Why is Incrementality Important?
Traditional touch-based attribution methods (e.g., UTM parameters, first-touch, last-touch) have limitations, particularly in cross-device scenarios. For example, a user might see your ad on Instagram (mobile) and later convert on desktop without the Instagram ad receiving credit.
Conversion Lift Analysis overcomes this by providing a more comprehensive view of your ad’s impact, independent of device or channel tracking. Incrementality testing is what’s beyond first-touch and last-touch attribution.
How Does It Work?
Install the Primer Pixel: Your personalized script is in the Connections page. Installation instructions are here.
Audience Overlap with Conversions: Your targeted audience in Primer should closely align with your target ICP (Ideal Customer Profile) to ensure a meaningful overlap with actual conversions (e.g., signups, demo requests).
Get Sufficient Conversion Volume: Primer use chi-square to gauge statistical significance and shows if statistical significants has or has not been achieved.
3 dots green = statistically significant
1 dot yellow = not statistically significant
Adjust the Time Period: Expanding the time period allows more conversions to accrue, increasing sample size and making performance differences more statistically reliable.
Learn More: For a deeper dive into incrementality testing, check out our blog post here.
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