Article

How Apple’s Mail Privacy Protection impacts today’s reporting and analytics

Trendline Interactive

4 minute read

Marketers have been relying on open rates in campaign reporting as a proxy for subscriber engagement for years now. Starting on September 20, 2021, as a result of the upcoming privacy updates from Apple, email opens will no longer be a reliable metric to report on since these numbers will be inflated. What does the privacy change mean for email marketers? And more importantly, what does it mean for your campaign reporting and analytics?

Apple users who update to iOS 15, iPadOS 15, or MacOS Monterrey will soon see the option to “Protect Mail activity” when they open the Apple Mail app for the first time. Any email delivered to an address that collects email in the Apple Mail app on an updated device will register as an “Open,” and no user information will be passed back through the open. This includes the IP address, location, device, etc. This does not affect other email apps on Apple devices, such as Gmail and Yahoo, just their native app.

Trendline predicts approximately 40-50% of your total email audience uses Apple, and we expect close to 100% adoption among Apple users. In this article, we address how to get ahead of the changes that will occur in your analytics’ reporting and modeling solutions. 

Redefining email engagement for reporting

In anticipation of this change, the Trendline Interactive Analytics team will no longer report open rates (ORs) or click to open rates (CTORs) and, instead, we will focus our reporting and insights on clicks and downstream activity post-click. Furthermore, any and all reporting defining engagement or active customers based on opens will need to be redefined and widely socialized. We will also continue to focus on website activity metrics and purchase behavior stats, where applicable, to round out our clients’ reporting needs. 

Truthfully, open rates have always been a bit of a “lazy metric.” They are easy to obtain but don’t really explain much and can, in fact, be misleading. For example, an open email does not equate to a read email. In many cases, spam filters (who can ‘open’ emails to scan them) or image downloads (not flagging an email as opened if the images were not downloaded) tamper with this metric. Therefore, the loss of this metric is not altogether a bad thing. However, companies do rely heavily on it, so this change will have a few downstream impacts. 

Revisiting email engagement activity in AI/ML analytics

This topic is at the forefront of marketers’ minds when it comes to reporting and campaign analytics. Email open activity comes in the form of a response metric, an active status definition, and as derived inputs to modeling. Below are some examples of how this privacy change will impact Trendline analytic capabilities. 

1. Subject line regression identifies words in email subject lines that significantly impact open rates. Similar to reporting, Trendline will change the model to identify words that impact click-through rates instead. 

2. Churn predictive AI/ML modeling helps companies identify and learn more about customers who are at risk of leaving so they can target them with messaging/offers for retention. In cases where churn’s  “inactivity” is based on email opens (the typical definition of engagement) and the goal is to re-engage the subscriber, a new targeted outcome will be required. Using click-throughs as an engagement metric is the best option. One should conduct an analysis to determine the amount of lapsed time without any click-through activity that best represents churn or attrition 

3. Most email journeys have a cadence based on timing. However, there are those that are triggered after an email has been opened, or not opened (as in the case of resending unopened emails). In these cases, email open activity can be supplemented with email clicks or post-click activity, or a new strategy may be to switch to a timing cadence.  

4. Again, if engagement is defined based on email open rates for analyses predicting or providing insights on deepening and increasing engagement, it needs to be redefined.

5. Cross-sell and upsell predictive AI/ML, propensity modeling, & next best action solutions depend on sales or adoption activity. However, in AI/ML, email open activity is often a predictive variable. These types of variables are defined as how many times and/or how recently a customer opened a marketing email. As with the other analytic solutions above, these can be re-programmed to represent how many times and how many days have passed since the subscriber clicked through a marketing email.

6. Response/uplift AI/ML modeling can identify customers’ segments who are persuaded by meaningful content, others who will be actively engaged no matter what, and those who prefer to be left alone. This provides companies pertinent information for optimizing companies’ marketing ROI. Trendline typically uses revenue-based metrics as targeted behavior. However, if email open response is the first layer of this type of modeling, then it is important to redefine engagement. Use business goal responses, such as purchased or subscribed. 

7. Any segmentation that is based on business rules or AI/ML algorithms will need to be revisited to ensure the artificially raised open rates do not cause Apple email app users to all of a sudden migrate into more engaged customer segments. Email open rates, engagement, and an active or non-active status are all often based on email open rates and then used as a factor to define groups. 

Moving forward without losing a step

To have a successful transition, identify impacts to your organization and address changes in data and reporting as soon as possible. Trendline has been running email analytics tests to predict the overall impact of the Mail Privacy Protection changes for many clients. This has been instrumental in allowing Trendline to efficiently identify the specific areas of the email programs that have been impacted, make necessary changes, and test the impacts in advance. 

It’s also important to plan and set expectations due to click-through rates being lower than open rates. Pay particular attention to two areas: 1) If there are triggers and/or segments that rely on opens, there may be a loss of opportunity. 2) When testing, larger control groups may be needed to reach statistical significance when migrating from opens to clicks.

If you need support in navigating the impacts this will have on your email program, please get in touch with us. We would be happy to help!

Changes Starting Mid-September 2021

Trendline Interactive

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About the Author(s)

Trendline Interactive

Built from email marketing, Trendline Interactive is an agency and consultancy that inspires brands to create meaningful engagement through cross-channel communications. Our passion is that every single message sent is not only meaningful to the audience, but drives success for our clients.

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