By analyzing reach and frequency data you can better understand how many people were shown your ads and how frequently the same people were shown them over a certain time period. Whether you’d like to focus on reinforcing a message or on reaching new people, this information can help you get a clearer picture of how you’re meeting your reach goals.
Unique reach and frequency metrics
Unique reach and frequency metrics measure the total number of people who were shown an ad and the frequency at which they were shown an ad. These metrics go beyond basic cookie measurements to help you understand how many times people were shown your ad across different devices, formats, and networks.
Our unique reach models measure the total reach of an ad by accounting for cases when people may see the same ad on different devices or when multiple people are co-viewing: watching ads together on connected TV devices.
Unique reach and frequency metrics include:
- Unique users
- Avg. impr. freq. per user
- Avg. impr. freq. per user (7 days)
- Avg. impr. freq. per user (30 days)
- Frequency distribution 1+, 2+, 3+, 4+, 5+, 10+
How Google calculates reach
How unique reach is calculated
To calculate unique reach, Campaign Manager 360 uses statistical models that account for user behavior across many browsers and devices. These models are created by observing aggregated user behavior across Google products to determine cross-device usage patterns. Google Ads combines behavior observations with other signals and local inputs (such as census and probability surveys) to deduplicate an audience across sessions, formats, networks, and devices. The result is the number of unique users (not cookies) who saw an ad.
Why you may not see reach and frequency metrics
Most reach and frequency metrics can only be reported for a date range of 92 days or less. You may not see reach data in your table if you’ve selected a date range that’s longer than 92 days.
Reach and frequency metrics may not immediately show data for some line items, depending on a few factors, including the availability of data by country and whether your ad has reached a minimum threshold of impressions and unique users. This is because unique reach models don’t support every country and also need to meet certain impression minimums.
Accounting for reporting delay
Due to the modeling involved in our calculations, it typically takes up to 3 days for reach and frequency metrics to be available in your account. Keep this delay in mind if your date range includes the last few days.
For example, if your date range is set to “Last 7 days”, consider that data from the last 3 days may not be complete. So the numbers shown for the last 7 days may not include the most recent 3 days of the last 7 days.
About reach and location targeting
Unique reach and frequency metrics use statistical models based on observing aggregated user behavior at the country level. Because the models are calculated at the country level, in a small percentage of cases the metrics may appear inconsistent, particularly for campaigns that target small geographical areas, such as a single city or zip code.
In other cases, a large volume of temporary visitors to a particular location may make unique reach appear inflated. We provide our best estimates of unique reach for these cases and we’re continuously working to improve our models to provide more detailed location estimates.
Frequency capping and viewable impressions
For Display line items, only impressions that were viewable count towards frequency caps. Other frequency reporting data may look higher than your frequency caps, because it is counting both viewable and unviewable impressions.
Reach quality metrics
In instant reports, estimated numbers with lower confidence are included for unique reach and frequency metrics.
For reports containing one or more of these metrics you can use the “Unique Reach Sample Size” dimension to filter your reports with two values:
- Unique Reach
- Unique Reach (Lower Confidence)
While numbers adjust for cases when people may see the same ad on different devices or when multiple people share one device, in some situations they are calculated with lower confidence.