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What calculation method is used for email campaign statistics?

Here is the methodology used to calculate campaign statistics in Mailify Sunrise:

The measurement is simple: Mailify automatically and systematically adds a tiny image of a few pixels to each email campaign. It is not visible to the reader. When a recipient opens the email with their messaging service, the tracking image is called on our statistics servers at Mailify, it is recognized by our platform and stored in the statistical report of your campaign in Mailify.

The detection of the opening by the tracker image does not provide a 100% reliable result.

Some of the messaging services block the download of remote images by default and the recipient decides whether or not to upload images. Reading the email offline will not detect the opening of the campaign either.

As a result, the actual opening rate is still higher than that established by the tracking image technique.

Fortunately, several methods are used to make the number of openings more reliable and get closer to the actual number.

First, all clicks are counted as openings. This adjustment may seem simple, however, among the clickers, there is still a proportion of openers who aren't identified by the tracking image method for the above-mentioned reasons. For this reason and assuming that 100% of the clickers have opened the email, we operate a first recovery of the openings. All recipients who have made at least one click in the emails are considered to have opened the email.

A second method based on statistics makes it possible to make the rate and number of openings even more reliable.
There's a drawback though: it will not be possible to identify individually (and then list) the recipients corresponding to the discrepancy between the number made reliable and the number detected by the tracking image and clicks. This is why there's a difference in the ratio between the numbers and rates displayed in the summary of your campaign, and the number of openers listed in the "Behavioral tracking" tab.

Here is a very practical example explaining the statistics-based adjustment method.

An email campaign is sent out to 1,000 recipients.

The tracking image method identifies 350 openings of the campaign. 100 clicks are also detected. Among the 100 clicks, 25 recipients haven't been counted as openers by the tracking image method.

The number of recipients identified as openers is therefore 350 + 25, i.e. 375 recipients. This is the number of openers you'll find in the "Behavioral Tracking" tab in-app. Then we'll operate the adjustment using the method based on statistics and show the result in the Summary section.

As 25 of the 100 clickers were not identified as openers using the tracking image method, this means that, among the clickers, the number of openings detected represents 75 / 100, or 75% of the actual number of openings.

Since clickers are considered an indicative sample of all recipients (what we observe from them is observable from all other recipients), we can conclude that the number of openings detected by the tracking image method also represents 75% of the actual number of openings.

The number displayed in the summary of results is therefore 350 / 466 or 75% and the rate will also be adjusted.
Unfortunately, between the 375 recipients identified as openers by the tracking image and click method, which you will find in the "Behavioral Tracking" tab, and this adjusted number of 466 openers, there's a discrepancy of 91 recipients. The latter are among the 625 recipients for whom we have not detected any opening by the tracking image or the click, but they will never be individually identifiable.