Understand your Brand Lift measurement data

If you’ve already set up Brand Lift measurement, you can add helpful reporting columns to determine how much your ads have influenced or "lifted" your audience’s positive feelings towards your brand or product. Generally, more responses are required to correctly detect smaller amounts of lift. If there are only a few responses to your Brand Lift surveys, it can be hard to accurately determine accurately what influence your ads had on those responses.

Refer to the following guidelines about how many responses are required to detect your lift.

  • For high-performing campaigns, you can expect to detect lift once you receive about 2,000 responses per lift metric.
  • At the recommended budget minimum, you can expect to detect lift once you receive 4,100 responses per lift metric.
  • If your campaign has not shown any lift after reaching 16,800 responses per metric, you may not be able to detect your lift.
Note: In general, you may notice lift results once your surveys reach 2,000 responses. Learn more about Brand Lift survey response count and absolute lift

In this article you’ll learn about all the metrics and how to use them to improve your results.

Lifted users

This column shows you the estimated number of users in a sample survey whose perception of your brand changed as a result of your ads, extrapolated to the overall reach of the campaign. It shows the difference in positive responses to your brand or product surveys between the group of users who were exposed to your ad and the group who weren't. For example, your ads could result in a lift in consideration (awareness or ad recall) with regard to your brand or product after exposure to your ads.

The Lifted users metric doesn’t necessarily measure unique users. A user may become lifted more than once during the course of your campaign.

Note: You can’t use your data to re-engage with Lifted users.

Cost per lifted user

Cost per lifted user is the average cost for a lifted user who's now thinking about your brand after viewing your ads. Cost per lifted user is measured by dividing the total cost of your campaign by the number of lifted users. You can use this metric to understand the cost to change someone’s mind about your brand in terms of brand consideration, ad recall, or brand awareness.

Absolute brand lift

This metric shows the difference in positive responses to brand or product surveys between the group who viewed your ads (the exposed group) and the group withheld from viewing your ads (the baseline group). This metric is calculated by subtracting the positive response rate of the baseline group from the exposed group. Absolute brand lift measures how much your ads influenced your audience’s positive feelings towards your brand or product. For example, an increase from 20% to 40% in the positive survey responses between the two surveyed groups represents an absolute lift of 20%.

Absolute brand lift and campaign performance

Absolute lift doesn’t necessarily reflect your overall Brand Lift performance. It's better to focus on a metric like Cost per lifted user as the primary success metric of your campaign, because it factors in both reach and cost. Refer the following table for more details.

Campaign

Cost Cost per 1,000 impressions (CPM) Reach Absolute lift Lifted users Cost-per-lifted user
Campaign 1 $100 $15 6,666 10% 667 $0.15
Campaign 2 $100 $5 20,000 5% 1,000 $0.10
Difference n/a 66% 200% 50% 60% 33%

If you look at absolute lift only, Campaign 1 seems to perform better than Campaign 2. But at the same cost, Campaign 2 drove 50% more lifted users, at a 66% lower CPM, and with a 33% more efficient Cost per lifted user.

Headroom brand lift

Headroom brand lift is the impact your ads had on increasing positive feelings towards your brand or product compared to the positive growth potential your brand or product could have gotten. This metric is calculated by dividing absolute lift by 1 minus the positive response rate of the baseline group. For example, an increase from 20% to 40% in the positive survey responses between the exposed group and the baseline groups represents a headroom lift of 25%.

Relative brand lift

Relative brand lift shows the difference in positive responses to brand or product surveys between users who viewed your ads, versus users who were stopped from viewing your ads. This difference is then divided by the number of positive responses from the group of users who didn’t view your ads. The result measures how much your ads influenced your audience’s positive perception of your brand. For example, an increase from 20% to 40% in the positive survey responses between the two surveyed groups represents a relative lift of 100%.

Since survey responses can’t be collected for the entire exposed and baseline groups, this data is extrapolated from the responses that have been collected, which gives you an estimated number within a certain range. Usually, the confidence interval is 80%. So you can expect that in 80% of the cases, the true lift number will be within that range if you were to have reached everyone.

Baseline positive response rate

This metric represents how often users who were stopped from viewing your ads responded positively to your brand. Use this metric to better understand how positive responses to your brand were influenced by general media exposure and other factors, as opposed to actual exposure to the ads in your campaigns.

Exposed survey responses

Exposed survey responses is the number of survey responses from people who were exposed to your ads.

Note: If you notice a low number in this column, that indicates that there aren’t enough survey responses yet. Continue running your campaigns and check back soon.

Baseline survey responses

Baseline survey responses is the number of survey responses from people who were withheld from viewing your ads.

Note: If you notice a low number in this column, that indicates that there aren’t enough survey responses yet. Continue running your campaigns and check back soon.

Exposed positive response rate

Exposed positive response rate represents how often users who viewed your ads responded positively to your brand.

Confidence interval

This is the range in which your Brand Lift estimates fall. For example, you may notice that your relative lift is 38.41%, the point estimate. In brackets, you may notice the confidence interval lower bound is 30.5% and the upper bound is 45.0%.

The confidence interval can be interpreted in three different ways:

  1. There’s an 80% chance that the actual result is between the lower and the upper bound.
  2. There’s a 90% chance that the actual result is higher than the lower bound.
  3. There’s a 90% chance that the actual result is lower than the higher bound.

This means that with high certainty, your true lift lies between 30.5% and 45%.

View your Brand Lift measurement data

Brand Lift measurement data is available in most tables in Google Ads, including "Campaign", "Ad Group", "Demographics", and more. You can also view results at the "Product" or "Brand" level in the "Lift Measurement" table.

To view your Brand Lift measurement data:

  1. Click the columns icon A picture of the Google Ads columns icon.
  2. Click Modify columns.
  3. Select Brand lift.
  4. Select the columns or metrics you’d like to view.
  5. Click Apply.

Segment your measurement data by Brand Lift type

To segment your measurement data by a specific metric, such as "Ad recall", "Awareness", "Consideration", "Favorability", or "Purchase Intent", click the segment icon and select Brand lift type.

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