E-mail marketing campaigns are being re-evaluated in light of Apple’s Mail Privacy Protection (MPP). Also, MPP pre-fetches email content in order to generate a haystack of fake open times in order to hide the real open times by their users. When MPP went into effect in September, Apple Mail app users were more than 95% likely to enable MPP, and Apple Mail was responsible for about 50% of all email opens.
This has prompted marketers to rethink how they measure email marketing success. Now, let’s take a look at how things have changed and what’s stayed the same in the last year or so.
- Opens are still useful, if not essential, in today’s business environment
- Email clicks are partially filling the void left by open rates
- There are considerations for cross-channel behavior
- What comes next?
Opens are still useful, if not essential, in today’s business environment
Opens have become increasingly difficult to understand due to a chorus of people declaring them to be dead. At this point opens are still very much relevant for marketers. Most marketers will continue to see reliable open rates from at least 50% of their subscribers even after MPP adoption reaches its peak. To ignore this open information would be naive.
Opens are necessary for the following reasons:
Many B2B companies, CPG brands, media organizations, and other brands prioritized engagement over direct sales in their email marketing programs.
This includes campaigns whose primary goal is to engage rather than sell.
Advertisers who want to know how many people will see their ads and how much they should charge for their placement in emails.
When it comes to calculating CTOR, which helps you determine how well your envelope content aligns with your body content, as well as how efficiently your recipients are converted into clickers.
Identifying a group of subscribers that consistently open your emails will be an important part of using opens in the future, and then using that group as a proxy for all of your subscribers. Marketers frequently use subsets of their audience as a stand-in for the entire audience when running A/B tests. In order to comply with MPP, marketers must use the same methodology to track open rates as well as open-based metrics like CTOR.
Is the accuracy of open rate measurement affected by this method? Yes. This will help businesses make important choices, however. If you’re looking at a metric’s value, not its precision, you’re missing the point.
Even so, don’t write off Apple’s auto-generated openings as a waste of your time. For example, Apple Mail’s auto-open feature can verify an email’s authenticity and alert users to spam or block it. Auto-openings do have some use, but it’s marginal.
Email clicks are partially filling the void left by open rates
When it comes to email marketing, it’s not hard to see why open rates have been overused, despite their usefulness. High-frequency engagement indicators were easy to measure and easily quantifiable.
Opens were a common metric for gauging the success of subject lines. Due to the fact that the tests were able to reach statistical significance within hours, the winner could be implemented later that same day. A major flaw in this strategy is that campaign success is not accurately predicted by the number of campaign opens, making the achievement of statistical significance on this poorly aligned measure pointless. As a result, marketers were encouraged to use vague, mysterious subject lines that were more likely to pique subscribers’ curiosity than their interest.
Until now, the most important metric for figuring out when to send an email has been how many times it has been opened. Another issue is that most marketers do not want their emails to arrive at the time when subscribers are most likely to open them. They want their emails to arrive when their subscribers are ready to engage and convert. The two times are often in close proximity, but they aren’t always the same.
Send time optimization and subject line optimization tools now give disproportionate weight to email clicks while excluding auto opens as a result of MPP undermining opens. Now that these optimizations are more in line with bottom-of-funnel behavior, they will have a greater impact on the success of the brand’s marketing efforts. It will take these optimization engines longer to adapt to changes in subscriber engagement behavior because clicks are eight times less common than opens. Despite this, these tools are still extremely useful.
There are considerations for cross-channel behavior
Despite the fact that email clicks partially compensate for the loss of email opens caused by MPP, email marketers have lost a significant amount of insight into the engagement of emails. Cross-channel behaviors are therefore being used by marketers to fill the remaining void.
This is crucial, because of the importance of subscriber engagement, which is probably the most important factor affecting a sender’s deliverability out of the seven listed. The best way to know if a subscriber is safe to mail to is to look at their recent open rates. It’s important for marketers to take into account cross-channel actions when they have only auto-open data. It is a legal requirement that brands identify their most loyal and engaged customers as “active subscribers.” In the absence of mailbox providers altering their spam filtering algorithms, this is the best option. However, this isn’t ideal.
MPP is urging brands to look at subscribers in a more holistic way, not just in terms of their inbox placement. With today’s multi-channel world, this is long overdue. In an effort to better serve customers, email marketing is being integrated with other digital marketing channels. As a result, customer lifetime value (CLV) and customer data platforms (CDPs), which aggregate all customer data in a single location to provide a real-time 360-degree view of the customer, are becoming increasingly popular metrics for businesses.
What comes next?
Marketing via email relies on data in order to be successful. Apple and Google are leading the way in enforcing stricter privacy policies that limit or devalue data collection. This means that marketers will have to stay flexible if they want to keep offering consumers experiences that are highly tailored to their preferences.