Brand Lift uses data from surveys to measure how your ads influence people. You can set up Brand Lift to show surveys to people about your product or brand.
In order to accurately detect your lift, a certain number of survey responses is required.
How Display & Video 360 measures your Brand Lift
Display & Video 360 can narrow down how much lift your Brand Lift metric generated based on the amount of positive survey responses between people who have seen your ads and those of people who were withheld from seeing your ads. Generally, more responses are required in order to accurately detect smaller amounts of absolute lift. Before your lift is detected, you will be able to see an estimation of it based on your response count.
When to expect detectable lift
View the following guidelines about how many responses are required to detect your lift.
- For high-performing line items, 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 5,600 responses per lift metric.
- If your line item has not shown any lift after reaching 16,800 responses per metric, you may not be able to detect your lift.
Required total responses for measuring Brand Lift
In order to measure Brand Lift accurately at various levels, the total response count must be within a certain range. The smaller the absolute lift, the more survey responses are required to ensure accuracy. The table below shows the required total response, given a detectable absolute lift:
| Detectable absolute lift | Required total response count |
|---|---|
| > 4% | 1,200 ~ 2,800 |
| 3% | 2,800 ~ 5,000 |
| 2% | 5,000 ~ 11,000 |
| 1.5% | 11,000 ~ 20,000 |
| 1% | 20,000 ~ 45,000 |
| 0.5% | 45,000 ~ 180,000 |
| < 0.5% | > 180,000 |
Example
For detectable absolute lift percentages not mentioned in the chart, you may need to estimate to find the total required response count.
Let's say you have .75% absolute lift and want to know the number of responses you need to detect the absolute lift. 45,000 responses would be more than what you need (since the minimum requirement to detect .5% absolute lift is 45,000 responses), while 20,000 responses wouldn't be enough (since the minimum requirement to detect 1% absolute lift is 20,000 responses).
Since .75% is halfway between 1% and .5%, you would need roughly between 20,000 and 45,000 responses to get .75% detectable absolute lift (or about 33,000 survey responses).
If your Brand Lift metric's absolute lift approaches 0, more survey responses are required to accurately measure absolute lift. This is because if there's only a small difference between the responses of people who have seen your ads and those of people who have not seen your ads, more responses are required to determine exactly what difference there is.
Brand Lift metrics
Absolute brand lift
This metric shows the difference in positive responses to brand or product surveys between the group of people who saw your ads (the exposed group) and the group withheld from seeing 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 insertion order performance
Absolute lift doesn't necessarily reflect your overall brand lift performance. It is better to focus on a metric like cost-per-lifted user as the primary success metric of your insertion order, because it factors in both reach and cost. See the following table:
| Insertion Order | Cost | Cost per 1,000 impressions (CPM) | Reach | Absolute lift | Lifted users | Cost-per-lifted user |
|---|---|---|---|---|---|---|
| Insertion Order 1 | $100 | $15 | 6,666 | 10% | 667 | $0.15 |
| Insertion Order 2 | $100 | $5 | 20,000 | 5% | 1,000 | $0.10 |
| Difference | n/a | 66% | 200% | 50% | 60% | 33% |
If you consider absolute lift only, Insertion Order 1 appears to perform better than Insertion Order 2. However, at the same cost, Insertion Order 2 drove 50% more lifted users, at a 66% lower CPM, and with a 33% more efficient cost-per-lifted user.
Lifted users
This shows the estimated number of users in a sample survey whose perception of your brand changed as a result of your ads, extended 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 saw your ad and the group who didn’t. For example, your ads could result in a lift in consideration (or awareness, or ad recall) with regard to your brand or product after seeing 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.
Lifted users (co-viewed)
The estimated number of users whose perception of your brand changed as a result of your ads, including lifted users from co-viewed impressions on CTV devices.Learn more about co-viewing.
Cost per lifted user
This shows the average cost for a lifted user who's now thinking about your brand after seeing 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.
Headroom lift
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
The difference in positive responses to brand or product surveys between users who saw your ads, versus users who were withheld from seeing your ads. This difference is then divided by the number of positive responses from the group of users who didn't see 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 the 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 90%, so you can expect that in 90% of the cases, the true lift number will be within that range (if you were to have reached everyone).
Baseline positive response rate
How often users who were withheld from seeing 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, not by seeing the ads.
Exposed survey responses
The number of survey responses from people who saw your ads.
Baseline survey responses
The number of survey responses from people who were withheld from seeing your ads.
Exposed positive response rate
This defines how often users who saw your ads responded positively to your brand.
Positive response rate
Out of all the people who responded to the survey, this is the percentage of people who responded with a positive answer in regards to your product or brand.
Confidence interval
This is the estimated range in which your relative brand lift and absolute lift estimates fall. For example, you may see your relative lift is 38.41%, the point estimate. In brackets you will see the confidence interval from at least 30.5% to at most 45.0%.