How to compare Email Analytics campaigns
The All Analytics screen summarizes the performance of multiple emails and lets you save and share custom reports, making it easy to identify top-performing emails and to gain insights to help optimize future campaigns. The page displays aggregate statistics across multiple emails to inform your email strategy and across other channels in your marketing mix. In addition, you can drill down into a single email and view its performance from the table on the “All Analytics” screen.
On the “All Analytics” screen, you can compare email results and aggregate statistics over a designated time period. The "All Analytics" screen defaults to the last 30 days, but you can adjust this range to any time period you wish by clicking "Edit Filters." All date ranges selected are rolling and will display results based on the date viewed. For example, if I view a report with a date range of the past 30 days on June 30th, it would show me results from 6/1 to 6/30. If I view the same report on November 30, it would show me results from 11/1 to 11/30.
You will see your total opens along with the average read, skim read, and glanced rates at the top of the dashboard with individual email tracking code performance below.
Filtering Email Analytics
Use the “Edit Filters” button to adjust which emails you want to see. After you select a date range and any additional filters (i.e. keyword or tag), the screen aggregates total opens along with the average read, skim read, and glanced rates for the displayed emails. The statistics are shown at the top of the dashboard with individual email performance below.
There are two tabs of aggregated statistics and results. The main “Overview” tab shows aggregate statistics and the “Details” tab shows a graphic representation of the selected emails.
Sorting and selecting emails
Click on the “Date” or “Opens” columns to sort your emails. Sorting by “Opens” helps you narrow down your top-performing campaigns and the engagement metrics columns help you hone in on which campaigns you should analyze further.
You can also select specific emails and click “Aggregate” to compare and analyze. For example, you could compare all of your transactional emails or email newsletters to compare performance from similar campaigns.
View your report summary
The “Details” tab visualizes campaign performance for campaigns in your selected filter and date range. If you’ve filtered out specific campaigns on the Overview page, the visualizations will reflect data just from the filtered emails. These visual breakdowns of your campaign performance are great for sharing data with your team.
Create and share custom reports
Easily access and share the insights that matter most by creating saved custom reports. Filter by date, tag, or tracking code keyword or manually select similar emails and click “Save Report” to create a new custom report.
Choose “Share” at the top right of the custom report to share it with other team members. The user that created the report can rename, delete, or edit the report parameters at any time.
Accessing analytics of an individual email
Click on any individual tracking code from the "All Analytics" screen to access the detailed individual email report. If you prefer, you can also access a full list of all email tracking codes in the Tracking Codes tab.
What are the definitions of read, skim read, and glanced?
Click here to learn how email engagement metrics are defined.
How are the total opens and engagement % rates calculated?
Total open counts in email analytics reports include every email that was opened, regardless of the engagement metric. For engagement reports specifically, the % rates for read, skim read, and glanced are calculated using only the opens where engagement rate tracking was supported by the email client. Therefore if you add up the counts for each of those three engagement metrics, you may not always get the same total open count as reported elsewhere. This is because for engagement rate calculations, we do not include the opens where we cannot accurately measure how long the recipient had the email open, and therefore are unable to categorize them as read, skim read, or glanced.