Brand lift studies: Cost, measurement, & FAQs

Q: How large does my brand lift study sample size need to be for reliable results?

The answer varies widely. We've seen sample sizes as low as 30, but Google says YouTube brand lift studies may begin detecting lift at around 2,000 survey responses per metric, and should detect it at about 5,600 responses per metric at its recommended budget minimum. If you need multiple breakouts, such as by audiences or creatives, you'll need a large overall sample size to have enough data for each.

Q: How do I measure ad exposure across channels?

Tracking ad exposure typically involves placing pixels on creative assets, but many social media platforms restrict this, and traditional channels like TV, radio, and out-of-home don't support digital tracking. The common alternative is an opportunity to see (OTS) methodology, where survey respondents' reported media consumption is matched against media placement timing. In our experience, OTS works well for channels like TV or radio but yields inconsistent results for social media. Test and control groups should be matched on demographics, geography, or online behaviors, and results can be contaminated by exposure to ads on other channels.

Q: How do I connect brand lift metrics to business outcomes?

Pair brand lift results with mid-funnel metrics like web traffic, customer acquisition rates, and customer acquisition cost (CAC); the more you invest in your brand, the lower your CAC should be. Marketing mix modeling aggregates many sources of data to show how different marketing channels contribute to overall business growth. Loyalty indicators like customer retention, online reviews, referrals, and a consistent price premium also show brand strength.

2 days ago

5 min read

Learn what brand lift studies cost, how many survey responses you need, how to measure ad exposure across channels, and how to tie results to growth.

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Key Takeaways

A brand lift study measures how an ad campaign changes brand metrics such as awareness, favorability, consideration, and purchase intent by comparing survey responses from people who saw the ads (the test group) with a similar group who didn’t (the control group).

Google, Meta, LinkedIn, and Amazon Ads offer brand lift studies at no added cost to campaigns that meet minimum spend thresholds. Independent cross-channel studies from research partners like Nielsen, Kantar, and DISQO typically cost from about $30,000 to more than $150,000.

Platform-run brand lift studies can’t account for people who saw the same campaign on other channels, so multichannel campaigns often need a third-party study to measure incremental lift across all media.

Brand lift results become evidence of business growth when they’re paired with customer acquisition cost (CAC), marketing mix modeling, and loyalty indicators like retention and referrals.

The challenge of tracking brand health
What are brand lift studies?
How much does a brand lift study cost?
How large does my brand lift study sample size need to be for reliable results?
How do I measure ad exposure across channels?
How do I connect brand lift metrics to business outcomes?

The challenge of tracking brand health

We’ve all moved past the tired brand vs. performance debate, and most marketers now accept that brand strength drives sustained business growth. The harder question is how to measure what upper-funnel paid media actually does for your brand.

Common brand health metrics include awareness, favorability, perceived quality, and advocacy. These metrics are hard to measure because they rely on either direct consumer feedback (surveys, panels, and focus groups) or indirect behavioral signals like branded search volume and social listening. Neither method is perfect, and neither shows whether your media caused the change. That’s why Exverus by Brainlabs takes a scientific approach to brand measurement with brand lift studies.

Blue-purple promo graphic reading exverus by brainlabs is officially a Tracksuit Partner, with smiley and peace stickers. — Exverus is an official Agency Partner of Tracksuit, a brand health tracking platform which saves our clients money and gives them a competitive edge. Click to learn more!

What are brand lift studies?

A brand lift study measures an advertising campaign's impact on brand awareness and favorability using a test-and-control methodology, comparing a test group (people exposed to the ads) against a control group (people not exposed to the ads but otherwise similar).

This approach offers significant advantages:

It controls for external factors that might impact brand perception, such as negative press or viral content
Unlike brand search trends or social listening, it specifically accounts for media exposure, allowing us to isolate the impact of marketing campaigns

How much does a brand lift study cost?

A brand lift study costs nothing beyond your media spend on platforms like YouTube, Meta, LinkedIn, and Amazon Ads, as long as your campaign meets the platform’s minimum spend. Independent studies from research partners like Nielsen, Kantar, or DISQO run from about $30,000 for a simple digital-only study to more than $150,000 for a complex multichannel study.

Google Ads, Amazon Ads, and Meta offer free brand lift studies to advertisers who meet minimum spend and impression thresholds, which ensure enough data for a statistically significant result. In the US, YouTube brand lift studies require at least $10,000 in campaign budget over a 10-day period to measure one brand metric, and the minimum rises with each additional question. Minimums vary by country.

LinkedIn Ads offers Brand Lift Tests at no added cost to accounts that meet a minimum cumulative budget (historically about $90,000 in the US). Campaign Manager calculates the exact requirement based on your test dates and number of brand metrics.

The main disadvantage of platform-run studies: they can’t account for people who saw your campaign on other channels, and that exposure can contaminate results.

Research partners like Nielsen, DISQO, or Kantar can measure incremental brand lift across many media channels holistically (CTV, digital audio, out-of-home, radio, you name it!). This gives your team a more complete picture of how ad exposure connects with real-life consumer sentiment. Studies for online channels, where ads can be tagged, usually cost less. Offline channels such as TV and out-of-home are more expensive to measure.

Long campaign flights, interim reports, online dashboards, and the larger samples needed to break out results in more detail all add to the cost of a study.

How large does my brand lift study sample size need to be for reliable results?

This question is complicated because the answer can vary so widely and depend upon many considerations.

We’ve seen sample sizes as low as 30, but Google says YouTube brand lift studies may begin detecting lift at around 2,000 survey responses per metric, and should detect it at about 5,600 responses per metric at its recommended budget minimum.

If you need multiple breakouts, such as by audiences or creatives, you'll need a large overall sample size to have enough data for each.

black and white chart against blue background — Source: Google DV360 Help

How do I measure ad exposure across channels?

Tracking ad exposure typically involves placing pixels on creative assets to digitally monitor viewership. However, this approach isn't feasible across all channels:

Many social media platforms restrict this tracking capability
Traditional channels like TV, radio, and out-of-home don't support digital tracking

The common alternative is an opportunity to see (OTS) methodology, where survey respondents' reported media consumption is matched against media placement timing.

In our experience, OTS works well for certain channels like TV or radio but yields inconsistent results for others like social media.

The methodology assumes test and control groups are identical except for ad exposure. We attempt to ensure this through sample matching based on demographics, geography, or online behaviors—but no two samples are 100% alike! The goal is similarity, not perfection.

And beware of cross-channel contamination: Modern consumers fluidly move between mobile, video, and TV multiple times daily, making channel-level impact testing challenging. When we're trying to compare ad-exposed versus non-exposed individuals, channel-level brand impact testing can be contaminated with other ad exposures.

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How do I connect brand lift metrics to business outcomes?

Mid-funnel metrics like web traffic, customer acquisition rates, and customer acquisition cost (CAC). The more you invest in your brand, the lower your CAC should be.
Marketing mix modeling (or media mix modeling) aggregates many sources of data to provide a comprehensive, full-funnel understanding of how different marketing channels contribute to overall business growth. AI-powered predictive analytics tools model different scenarios to help us choose the right course.
Loyalty indicators like customer retention, online reviews, referrals, and consistent price premium. Your brand is strong if consumers think of you long after they've made a first purchase.

Media mix modeling (MMM): A guide for brands over a laptop and shopping cart with colorful app icons on a blurred desk background — Learn how MMM, multi-touch attribution, and incrementality serve different, but equally necessary, media measurement purposes.

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