Prove causality with controlled experiments that isolate the true impact of your media. Understand how to plan, run, and interpret Conversion Lift so decisions reflect incrementality.
Conversion Lift measures incremental conversions by comparing a treatment group that sees ads with a control group that does not.
False—lift is just modeled attribution share
False—it compares two different campaigns, not audiences
True—lift is the causal difference between treatment and control
False—it measures only click-through conversions
Which split types are available for Conversion Lift in Google Ads (as reported in-platform)?
User-based and geography-based splits
Creative-based only (A/B assets)
Device-based and browser-based splits
Channel-based only (YouTube vs. Search)
A prerequisite for statistically useful Conversion Lift results is ______.
using only exact match keywords
running tests shorter than 7 days
sufficient recent conversion volume in the tested campaigns
disabling automated bidding entirely
Which metric is uniquely available in geo-based Conversion Lift reporting?
Invalid traffic rate
Incremental ROAS
Average CPC
View rate
True or false: Conversion Lift is automatically available to all accounts without any eligibility checks.
False—availability depends on eligibility and may require Google rep enablement
False—but only for App campaigns
True—any advertiser can run it without limits
True—it is enabled by default in all accounts
When running lift on YouTube or Demand Gen, a best practice is to align bidding/optimization to the same conversion you want to measure for lift.
False—optimize to clicks for more traffic
False—optimize to impressions for faster results
False—optimize to view rate for better sample size
True—optimize to the downstream action being measured
Which of the following is a valid use case for Conversion Lift?
Measuring creative approval turnaround time
Quantifying the incremental conversions driven by a new Demand Gen or YouTube campaign
Testing ad scheduling for manual CPC only
Estimating server-side tag latency
To ensure accuracy, you should avoid major targeting and budget changes mid-test because ______.
more changes always increase statistical power
they can contaminate treatment/control comparability and bias lift
lift automatically adjusts for any change
Google forbids editing campaigns under any circumstance
If a test shows positive incremental conversions but negative incremental ROAS, the likely issue is ______.
brand safety exclusions cause ROAS to drop by default
geo split cannot report value metrics
incremental value is too low relative to cost
measurement always overstates value in lift
Which statement about interpreting lift is most accurate?
Lift only applies when cookies are present
Lift estimates the causal contribution at the time of the test and should be re-run after major changes
Lift equals modeled conversions in attribution reports
Lift permanently proves lifetime causality
Starter
You understand the basics of lift. Revisit eligibility, volume needs, and split types before your next test.
Solid
Good grasp of setup and metrics. Tighten your guardrails and align optimization with the outcome you measure.
Expert!
Excellent. You can design robust lift tests, read incremental ROAS, and translate findings into budgets.
