Google Ads Conversion Lift estimates the conversions or conversion value that ads added by comparing outcomes for an ad-exposed treatment group with an unexposed control group. It is an experiment, not another attribution report. Self-service setup is available only to eligible accounts, and Google’s current user-based guidance lists minimum volume, budget, compatible campaign and conversion requirements.
What Conversion Lift measures—and what it does not
In a user-based Conversion Lift study, Google assigns users to a treatment group that can see the selected ads or a control group held back from them. The difference in outcomes over the study period estimates the campaign’s incremental effect. It is not a perfect count of every conversion caused by advertising: Google may model outcomes that cannot be directly linked to ad interactions, including because of browser restrictions or cross-device behavior.
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Standard conversion reporting answers a different question. It allocates credit according to the account’s conversion tracking and attribution settings. Conversion Lift compares experimental groups. A campaign can therefore have attributed conversions without producing a conclusive lift result, or show incremental impact that differs from its ordinary reported conversion total. See Google’s explanation of Conversion Lift and its conversion reporting guidance.
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Google Ads Help’s user-based setup guidance, accessed October 8, 2026, says Conversion Lift is not available to all accounts and advises advertisers to contact their Google account representative. The same guidance gives these current eligibility requirements; they are not a guarantee that a particular account will be granted access.
| Requirement or restriction | Current user-based guidance |
|---|---|
| Observed conversion volume | At least 1,000 observed conversions |
| Campaign budget | Minimum US$5,000 campaign budget |
| Supported campaign types | Display, Search, Video, Demand Gen, App Campaigns, and Performance Max |
| Unsupported campaign types or targeting | iOS-targeted App campaigns and Travel Ads |
| Concurrent studies | A campaign can be in only one Brand Lift, Search Lift, or Conversion Lift study at a time |
These thresholds and supported types reflect Google’s guidance as accessed on October 8, 2026, and may change. Check the live Conversion Lift setup requirements and your account access before planning around them.
Prepare measurement before creating a study
Choose conversion actions that are both compatible with the study and meaningfully influenced by the ads. A conversion action that is rare, poorly tracked, or only weakly related to the selected campaigns may make the study less informative. Google recommends enhanced conversions for web and leads, consent mode, and related measurement improvements to strengthen observed data and modeling. These measures can improve measurement inputs; they do not guarantee a lift result or remove every limitation.
Some outcomes, including store sales and offline leads, may be modeled through Supplementary Conversion Reporting. If a report includes modeled outcomes, distinguish them from directly observed conversions rather than presenting the entire result as directly measured. Google describes this reporting in its setup help.
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Google’s interface labels can change, but the documented workflow is through the Lift studies area in Google Ads:
- Open the Lift studies area in Google Ads and choose to create a study.
- Select Conversion Lift, then choose the user-based study type.
- Name the study and add the eligible campaigns you want to evaluate.
- Choose a compatible conversion action and review the Study Power estimate, including the proposed duration and holdback.
- Confirm that campaign eligibility, conversion measurement, and study timing fit your measurement question before launching.
Including all eligible campaigns that could reach the study’s control users can reduce the chance those users see other ads from the same advertiser, which can blur the treatment-versus-control contrast. Google’s setup details are in Create a Conversion Lift study.
Use Study Power to judge feasibility
Study Power estimates the chance of obtaining conclusive results; it does not predict how valuable a campaign will be. Google says its estimate depends on the conversion actions, daily budget, duration, holdback percentage, account-level historical data, and estimated lift. The setup estimate is shown from 50% to 95% in five-point increments. Google recommends aiming for 90% certainty; it describes results from 50% to below 90% as directional. Decide whether that uncertainty is acceptable for the business decision the study is meant to inform.
Google defines lift certainty as 1 minus the p-value. Under its guidance, results below 50% certainty are reported as “no lift.” That label means the study did not reach Google’s reporting threshold for a positive lift result; it does not establish that the ads had no effect. Google explicitly notes that “This doesn’t necessarily mean that your ads were ineffective.”
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To improve the chance of a useful readout, Google recommends choosing conversions directly influenced by ads, including eligible campaigns, and extending study duration where appropriate—up to 56 days in its certainty guidance. If conversion volume is insufficient, repeating a study with greater volume may help. These are design considerations, not a promise that the study will become conclusive. See Google’s guidance on interpreting lift certainty.
Read the lift metrics without confusing them with attribution
| Metric | Meaning | How to read it |
|---|---|---|
| Incremental conversions (absolute lift) | Treatment-group conversions minus control-group conversions | The estimated additional conversions associated with ad exposure in the study. |
| Relative lift | Incremental conversions divided by control-group conversions | Can be very large when the control group has few conversions; compare carefully across studies with different control volumes. |
| Incremental CPA (iCPA) | Total ad spend divided by incremental conversions | Spend per estimated additional conversion, not spend per attributed conversion. |
| Incremental conversion value | Treatment-group conversion value minus control-group conversion value | The estimated value added across the study groups. |
| Incremental ROAS (iROAS) | Incremental conversion value divided by ad spend | Uses incremental value. Ordinary ROAS instead divides attributed conversion value by spend. |
These definitions come from Google’s Conversion Lift measurement guidance. In practical terms, do not substitute the campaign’s ordinary attributed conversions or ROAS for the experiment’s incremental outcomes when deciding whether the study detected added impact.
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Account for the statistical method used in your report
Google says its Conversion Lift studies began a gradual transition to Bayesian statistical methodology in 2025. Its methodology guidance says most accounts currently use frequentist methodology and advises advertisers to ask their account manager about transition timing. Do not assume every account uses the same method; verify the method used for your study before interpreting interval language.
Under Google’s description, the Bayesian approach combines study results with historical campaign information such as campaign type, performance metrics, and product vertical. Bayesian credible intervals have a probability interpretation, while frequentist confidence intervals are interpreted differently. Treat an interval according to the methodology named for your account, not as though the two labels were interchangeable. See Google’s Conversion Lift methodology overview.
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Interpret segments and delayed conversions carefully
Certainty is not a score for business value and should not be used alone to rank audience segments. Google warns that segment sizes differ and confidence intervals may overlap. A segment with greater certainty is not automatically the better performer; consider the estimated effect, uncertainty, and business objective together.
Google currently describes delayed incremental conversions as a feature for Demand Gen-only studies. It models conversions expected after the official study end date using conversion lag observed during the study, and reports them as delayed incremental conversions where available. Do not assume this feature applies to other campaign types. Details are in Google’s Conversion Lift reporting help.
When user-based Conversion Lift is the right design
A user-based study is suited to a question about the effect of ad exposure on users assigned to treatment and control groups. It is different from standard conversion reporting, which assigns credit under attribution settings, and from a geo-based experiment, which concerns geographically assigned exposure. Google also offers geo-based Conversion Lift, but its account-specific requirements and setup should be checked in the live Google Ads documentation or with a representative; the details here do not establish geo eligibility.
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