You will be able to explain how privacy features inflate open rates and what to look at instead.
Mei Ling looks at the report for her latest newsletter and feels pleased. The open rate is the highest she has ever had. Then she looks at the orders that came in that week, and there are fewer than usual. The clicks on the order link are about the same as every other month. Did people read the email or not?
The honest answer is that the open rate cannot tell her. For years it was the first number every email marketer checked. Today it is the least reliable number in the report, and this lesson explains why.
An email cannot report back when someone reads it. So email tools use a workaround. Each marketing email contains a tracking pixel: a tiny, invisible image unique to that email and that recipient. The image sits on the email tool's server. When the email is displayed with images switched on, the reader's email app fetches the image from the server, and the tool records that fetch as an open.
That method was always approximate, since what it records is an image loading and nobody can see whether a person read anything. For a long time, though, the two were close enough that open rate was a useful guide.
Apple Mail Privacy Protection, a feature in Apple's Mail app, changed that. When a user turns it on, Apple's servers load the images in their incoming emails in the background, whether or not the person ever opens the message. The tracking pixel loads, and the email tool records an open.
So for subscribers who read email in Apple Mail with the feature on, many emails count as opened even if they were never looked at. The open time is also unreliable, because it reflects when Apple fetched the images, not when the person read anything.
Apple Mail is used on iPhones, iPads and Macs, and a large share of many lists read email there. For a list like Mei Ling's, where many customers use iPhones, a meaningful part of the open rate may be machine opens. That is why her open rate rose while her orders did not: more of her subscribers had the feature on, and their emails counted as opened automatically. Your email tool's reports may show how your own list splits by email app, which gives you a sense of how much this affects you.
Other apps cause the opposite problem. Some email apps and settings block images until the reader chooses to load them, and some readers keep images off to save mobile data or for privacy. When images are blocked, the tracking pixel never loads. A person can open the email, read every word, even click a link, and the open may not be counted.
Most tools count anyone who clicks as having opened, which fills part of that gap. People who read without clicking and with images blocked stay invisible.
So the open rate is pushed up by machine opens and pushed down by blocked images, by amounts you cannot see precisely. It is no longer a measure of how many people read your email.
That does not make the open rate worthless. If your list and its mix of email apps stay roughly the same, a sudden large drop in opens from one month to the next can still be an early warning, for example of a delivery problem where your mail started landing in spam. Treat it as a rough trend at best.
For judging whether an email worked, use actions that need a person. Clicks are the main one: Apple's privacy feature does not click links for people. Replies are another, especially for emails that ask a question, like Priya's welcome email asking which topic a child finds hardest. And the actions that follow: bookings, orders and enquiries traced back to the email. Lesson 8.2, The numbers that link email to money, covers how to measure those.
This affects choices you made earlier in the course too. Lesson 5.2 told you to test subject lines on clicks, not opens, and this is the reason. Lesson 3.4 told you to define quiet subscribers by clicks, replies and purchases, because someone whose Apple Mail opens everything automatically never looks quiet by opens, even if they have not read anything in a year.
Some email tools now try to identify machine opens and show them separately, or exclude them from the open rate by default. Others report all opens together. Some let you choose. The labels vary: you might see terms such as machine opens, privacy opens or Apple opens, or a note in the report's help text.
Knowing which applies to your tool tells you how much weight to give the number at all. In the activity below you will open your email tool's report for your last send and check whether it separates machine or privacy opens from other opens.
Check your email tool's report for your last send and note whether it separates machine or privacy opens from other opens.
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