Brand lift & incrementality
Exposed and control groups, weighting and repeated audience cuts can turn lift reporting into a separate production job. The MX8 Labs Research Platform calculates lift as responses arrive, with matching, weighting and audience comparisons in the same report.
See exposed and control group counts, response rates, lift and statistical results together.
See lift report setup and outputsChoose exposed and control groups, matching variables and the outcomes you want to report.
Configure weighting and significance settings, then inspect rates, lift and uncertainty.
Add audience cuts and labels, then export the group rates, lift and statistical results.
Choose how to identify exposure: random assignment to a stimulus inside the survey, matched ad-server records, or reported exposure. Specify the control group and matching variables before fielding.
Recruit respondents through 70+ integrated panels with real-time fraud and attention checks. Set the fieldwork schedule around campaign reach and the sample needed for each comparison.
Weighting, matching, and significance testing run automatically as responses land. Lift is reported alongside group rates and statistical results, ready to inspect and export.
Your analysts define the comparison and interpret the findings, checking AI-generated report drafts against the statistical results. Randomized designs support stronger causal claims; matching may leave other differences between groups. Plan the comparison and matching variables before inspecting results.
The full method — treated-group definition, control construction, computation, and the strength of causal claim each design supports — is public in our lift measurement methodology. Pair campaign measurement with creative testing before launch and check your campaign's measurability before you field.
Our brand lift overview explains the measures. The practical planning guide walks through exposure groups, sample requirements, and interpretation limits.
A brand lift study compares awareness, consideration, favorability, intent, and ad recall between respondents exposed to a campaign and a control group. The difference is reported as lift, with significance testing. Whether it supports a causal claim depends on the study design: matching alone does not remove all possible confounding.
Attribution assigns credit for conversions to observed touchpoints. Incrementality testing uses a control group to estimate what would have happened without the campaign. Survey-based brand lift measures brand outcomes such as awareness and intent, rather than tracked conversions. Exposure may still be identified through ad-server records, and causal claims depend on how the study assigns or identifies exposure.
Results update as responses arrive, with weighting and significance testing applied automatically. Fieldwork can take hours to days, depending on the audience and required sample. Wait for enough exposed and control respondents before using the results to make campaign decisions.
Yes. Our lift measurement methodology documents exposure definitions, control matching, lift calculations, significance testing, and the claims each design supports. Your analysts can review the method and its limitations before the study starts.
Define your audience, exposure data, and the brand outcomes you want to measure.