To find out whether marketing is changing a brand’s reputation, measure the perception the campaign is intended to affect, record a baseline, and compare responses from people exposed to the campaign with a suitable unexposed control group. A simple before-and-after change can be a clue, but it does not by itself show that marketing caused the change.
Decide what “reputation” means for this campaign
Reputation is broader than ad recall, reach, clicks, or engagement. Choose a specific perception or relationship outcome that matches the campaign’s purpose, such as awareness, favourability, trust, consideration, satisfaction, recommendation, perceived quality, or perceived value. The DMA’s 2025 Guide to Best Practice Measurement treats reputation and consumer impact as part of brand measurement and discusses measures including awareness, satisfaction, and purchase intent.
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Keep delivery metrics separate from reputation outcomes. Google Ads, for example, describes Brand Lift as measuring goals such as ad recall, brand association, awareness, and consideration—not as a substitute for traditional delivery metrics. See Google Ads’ Brand Lift overview.
Choose a design that can answer the question
For a campaign-level effect, compare exposed and control groups
A lift study compares survey responses from people exposed to a campaign with responses from an unexposed control group. Amazon Ads describes this approach as surveying both groups to measure advertising’s effect on customer perceptions; see its Brand Lift product page. The strength of the conclusion depends on whether the groups are comparable and whether the study measures the intended audience and outcome.
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Randomized experiments can support a stronger causal claim than an uncontrolled before-and-after comparison. Google Research authors Rachel Fan, Tim Hesterberg, Ying Liu, and Lu Zhang describe their method as estimating ad effects using randomized experiments in Methods for Measuring Brand Lift of Online Ads, presented at the 2018 Joint Statistical Meetings. The paper also discusses potential response bias and discrepancies between intended and actual treatment—issues that can weaken an experiment.
For reputation over time, use continuing brand tracking
Ongoing tracking helps show how brand health changes across time, audience segments, and competitors. It answers a different question from a campaign lift study: tracking describes broader movement, while a lift study estimates campaign-related change against a control. The DMA’s 2025 guide discusses continuous tracking, segmentation, and competitor analysis.
Run the evaluation in a consistent sequence
- Set the intended outcome. Choose the reputation measure before launch and make it specific—for example, perceived product quality or consideration among a defined audience. Do not treat impressions, clicks, or engagement as evidence that reputation improved.
- Record a baseline. Measure the selected outcome before the campaign. If the decision requires a causal estimate, plan for a suitable unexposed comparison group, preferably using random assignment where feasible.
- Keep the measurement comparable. Use consistent question wording, target population, geography, and timing across the groups or measurement waves. If those change, explain how that limits comparison.
- Report the result with its scope. State the exact metric and question, audience, geography, survey window, exposed and control response counts, and the absolute difference between groups. Include whether the provider’s reporting threshold was met.
- Check other plausible explanations. Note concurrent campaigns, public relations, product or service changes, pricing, competitor activity, and major news. These may coincide with reputation movement; a before-and-after trend alone cannot separate their effects.
- Separate perceptions from behavior. Consideration and purchase intent are survey responses, not observed purchases. If the decision is about sales or profit, add relevant behavioral or commercial evidence instead of inferring it from a positive lift result.
Interpret sample sizes and inconclusive results carefully
Small effects are harder to distinguish from noise and generally require more responses. Provider figures are tied to their own methods and detectable-effect assumptions; they are not universal sample-size rules.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problems| Provider guidance | Reported response volume | How to interpret it |
|---|---|---|
| Google Ads Brand Lift, current help page accessed in 2026: response requirements | About 2,000 survey responses per lift metric for high-performing campaigns; 4,100 at the recommended budget minimum. The page also says that 16,800 responses per metric without detected lift may mean lift cannot be detected under the study conditions. | These are Google Ads platform figures, not general requirements. No detected lift at that response volume does not prove the true effect is zero. Google says results can fluctuate during a study and recommends using the final report. |
| Display & Video 360, current help page accessed in 2026: Brand Lift study requirements | Guidance lists 1,200–2,800 responses for detectable absolute lift above 4%, and 45,000–180,000 responses for 0.5% lift. | These are provider-specific estimates; the required volume varies with the effect being detected and the study conditions. |
A result marked provisional, still collecting responses, or below a reporting threshold is not the same as evidence of no effect. Google says response requirements vary with lift size and that results may change before completion. Read the final result in light of its sample, comparison, and stated uncertainty.
Compare study options before choosing a provider
Platform studies can be useful when the campaign ran on that platform and the account, market, budget, and response conditions are met. Availability is not universal: Google Ads says Brand Lift is not available to every account, while providers may also limit supported markets, campaign types, or inventory. Check current eligibility and study rules directly before planning around a specific product.
- Design: How is the control group formed, and how credible is the comparison?
- Audience: Does the sampled population match the people whose reputation perceptions matter? Are geography and segments appropriate?
- Measure: What exact question and metric are used? Do they reflect the intended reputation outcome?
- Statistical sensitivity: What response volume and minimum detectable change apply? What happens if the study does not reach its threshold?
- Eligibility and timing: Which campaign types, markets, accounts, and budgets qualify, and how long does data collection take?
- Scope: Do you need an estimate for one campaign or continuous brand-health and competitor tracking?
For example, Amazon Ads says Brand Lift results may be available as soon as 10 business days after submission, subject to advertiser and campaign conditions; its product page also lists supported markets and exclusions, including Sponsored Products. Treat the timing as a provider statement, not a guaranteed turnaround for every campaign.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Build a conclusion that matches the evidence
A defensible conclusion names the measured perception, the audience, the period, the exposed-versus-control difference, and the limits of the comparison. Say that the study found a measured lift in a specified survey response if that is what it establishes; do not expand that into a claim that the entire brand’s reputation improved or that sales increased unless separate evidence supports those conclusions.
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