Viewer Frequency Report

Viewer frequency reports track impression frequency and performance during the reporting period. Impression performance can be evaluated in terms of conversion rates, click-through rates (for display ads), or completion rates (for video ads).

Every viewer frequency report is defined by a frequency window and the reporting period.

  • The frequency window specifies the time period over which frequency is calculated. Viewer frequency reports support one day, seven day, thirty day, and forty-five day frequency windows.
  • The reporting period specifies the time frame of the report. Frequency is calculated based on user and impression data drawn from the reporting period.

Viewer frequency report data is charted in two charts that share a common x-axis that represents impression frequency, the rate at which users are exposed to an ad during the frequency window.

Select a time range of data

The Viewer Frequency report plots users and impression performance by frequency window in two charts:

  • The user bar chart displays the distribution of users by frequency window for the length of the reporting period.
  • The performance line chart displays the percentage of successful impressions per frequency window for the length of the reporting period.

By comparing the data displayed in the user distribution chart with that shown in the performance line chart, advertisers can assess whether the campaign benefits from higher impression rates.

User Distribution Chart

The user frequency bar chart shows the distribution of users by frequency (rate of ad exposure) for the duration of the reporting period. In short, this chart enables you to see at a glance how frequently users were exposed to your ads.

The bar chart in the Frequency Bucketing Report

Frequency is the rate at which a user views an ad during the specified frequency window (1 day, 7 days, 30 days, or 45 days). Frequency is always defined by a frequency window that determines the how users are aggregated.

The distribution bar chart shows the distribution of users to impression frequency during the reporting period.

  • The horizontal x-axis represents frequency, the rate of impressions per frequency window for the duration of the reporting period.
  • The vertical y-axis represents the approximate number of users that viewed ad impressions at each frequency. (The user count is only an approximation of the total numbers of users, with a 5% error rate, enough accuracy to provide insights.)

Note

The bar chart aggregates users by frequency. During the reporting period, the same user may view impressions at different rates during different frequency windows. Consequently, the same user may be counted towards. If you select a 1 day frequency window and one user sees one impression on day one of the campaign, and the same user sees two impressions on day two of the campaign, that user will have two entries: one in frequency bucket 1, and one in frequency bucket 2.

Performance Line Chart

The performance line chart shows the success of impressions per frequency.

The performance line chart enables you to assess the success of an impression based on its completion rate, conversion rate, or click-through rate.

Viewer Frequency performance chart by CTR

In the performance chart, the horizontal axis represents the frequency of impressions per user during the reporting period. The vertical axis represents the success of that those impressions as measured by one of success metrics.

Success metrics are key performance indicators (KPIs) that measure the relative success of each impression. Impressions that result in click-throughs are naturally more valuable and more successful than impressions that do not result in click-throughs.

Viewer frequency performance can be measured by three different success metrics, that measure the percentage of impressions that deliver desirable outcome:

Success Metric Description
Completion rate The percentage of video ads that play through to completion.
Conversion rate The percentage of users who complete a desired action (e.g., purchase or registration) compared to all users who were exposed to an online ad.’ acc. to iab
Click-through rate The percentage of users that click an ad.

To change the success metric, select an option in the dropdown list.

Using the performance chart, you can identify the frequency bucket that returns the best performance during the reporting period.

Tip

Optimize on a frequency bucket to provide the optimal number of impressions per day, or per 7 days, 30 days, or 45 days.

How Does the Viewer Frequency Insight Work?

The reporting period specifies the time frame of the impression and performance data. Data may be drawn from the previous month, week, day or a custom range of dates.

During that reporting period, a number of users will see your ad once, a certain number will see it twice, three times, and so on. The report aggregates these users by frequency, the number of ad impressions per frequency window. Each set of users is represented by a “frequency bucket” in a bar chart.

The viewer frequency report enables you to compare user and impression performance data across frequency buckets.

Select a time range of data

The report displays aggregated user and performance data grouped by frequency.

The line chart that shows the performance as measured by the specified success metric across all the different frequency buckets.

  • If you hover over a bar, the report displays information about the users in that bucket. For example, 1492 users saw the ad twice during the selected time period.
  • If you click a data point in the line chart, the report displays impression performance statistics.

To compare frequency buckets, look for the buckets that yield the best performance for your viewer frequency success metric.

Sometimes increasing the number of impressions yields lower performance. Other times, increasing the number of impressions yields higher performance, but the increase in performance may not be high enough to justify the increase in impressions.

A comparison of the performance yielded by different frequency buckets:

Comparision of performance yielded by different frequency buckets

Consider the example, where the best performance to frequency ratio seems to occur at several distinct points:

  • Users who saw two (2) impressions converted at .62%
  • Users who saw 14 impressions converted at .66%
  • Users who saw between 36 and 40 impressions converted at .62%

How Do I Create a Viewer Frequency Report?

The DSP enables you to can create and run viewer frequency reports in the Dashboard and Insight pages.

Follow the steps in this section to run a campaign report from the Insights tab.

To create a Viewer Frequency Report:

  1. From the DSP Insights tab, select the Viewer Frequency Report subtab.

    viewer-frequency-report-subtab

    Note

    You can also run the report from the dashboard. Check out run-reports-from-the-dashboard.

  2. Start typing the name of the campaign you are working with, and then select the campaign name from the dropdown list.

  3. Select a frequency window (1 day, 7 days, or 30 days). The frequency window determines the length of time over which DSP calculates the frequency that each user is exposed to impressions from the campaign.

    Tip

    It’s best to select the same frequency window that you selected when you set up the campaign so that you can compare actual delivery to the frequency you set for the campaign.

    Example: If you select a 1 day frequency window, the report groups users by the number of impressions they saw per day. For example, 100 users saw one impression per day, 150 users saw two impressions per day, and so on. If you select a 7-day frequency window, the report groups users by the number of impressions they saw in 7 days. For example, 80 users saw 2 impressions every 7 days.

  4. Select the date range for which you want to see data. Select an option from the Date Range menu, or enter a custom range.

  5. Click Run Report.