Meta’s Conversion Lift studies measure the incremental impact of your ads on conversions using test and control groups. The test group is exposed to your ads, while the control group is not. By comparing the conversion rates between these two groups, Conversion Lift studies help determine the additional conversions that would not have happened without seeing your ads.

As a government, political or nonprofit organization, you may use Conversion Lift to understand the true value of your Meta ads at driving incremental conversions, such as email sign-ups, donations, or report downloads. In order to set your Conversion Lift study up for success, please consider this list of best practices, to ensure you have the right structure and settings in place before you launch.

Gain internal alignment on the value of incrementality.

Meta’s Conversion Lift test can help you measure the incrementality of your ad performance, or put another way, the additional conversions specifically caused by exposure to your ads. Ensuring your stakeholders understand the value of incrementality before you present your results will make them not only interesting, but more importantly, actionable.

Start with a key question that you want to answer for your organization.

Before you design your test, articulate what it is you’re looking to learn. This could be as simple as are my Meta ads driving conversions that would not have happened otherwise, or something more complex such as whether creative theme A or creative theme B is more effective at driving sign-ups or pledges.

Ensure you have a high quality set-up with Meta through Conversions API, Meta Pixel, and/or SDK.

Conversion Lift uses these tools as the data source for reporting incremental conversions. Ensuring these tools are passing high quality and accurate data can lead to more reliable test results and maximize representativeness of measured outcomes.

Set your test up for success during campaign set-up.

• Run your test on a campaign that is long enough to cover 1–2 conversion cycles or 2-4 weeks.
• Ensure that your budget meets the testing requirements and is enough for your ad sets to exit the learning phase.
  • Please note that there’s no additional cost to run a Conversion Lift test, but ad campaigns or ad sets you use for conversion lift tests may have certain budget requirements, which you can find here. These requirements are in place to ensure a study has enough data and to minimize the chances of low confidence results.
• Target an audience that is not being used in other Meta campaigns. If you do, this may cause conversions to happen in the control group, inflating your baseline, and making it harder to detect lift.
• Optimize and measure conversion events that reflect your primary goal, not a proxy metric.
  • Include secondary goals in your test too. For example, if you are measuring an event tracking donations, also measure events tracking landing on the donation page, and starting the donation flow, as lift in these metrics can also help inform your decision making process.
• Use creative that has a prominent call to action and branding throughout.
  
  

Hold off on making changes to your campaigns while the test is live.

Adjustments, such as adding new creative, changing your budget, or updating your audience targeting, can cause your lift study results to change but you won’t be able to understand the exact impact. To properly isolate the variable you are testing, and to know definitively it was that variable that caused the results, wait to make adjustments until after the test.