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February 3, 2023

🧐 Open Rate. It’s important. But is it accurate?

Learn more about why your Open Rate might be artificially inflated.

Maybe you’re planning email marketing goals for the year. Maybe you just launched your first newsletter. You know Open Rate is important. It tells you how many people are opening your emails. Click-to-Open Rate too. That shows how many readers are engaged with your content. These metrics help measure quantitative success for your email marketing efforts.

But what if they’re not accurate?

You may or may not remember Apple Mail Privacy Protection (MPP), or your newsletter may not have existed when it was announced, but it rolled out ~September 2021 alongside the iOS 15 update.

Currently, ~64% of email opens are coming from Apple, and of that ~59.53% have Apple MPP-enabled, according to Litmus. This may not be the case for your subscriber base, but take comfort in knowing it is calculated from over 1.6 billion opens in Litmus Email Analytics in December 2022 post-Apple MPP launch – meaning it is a fairly accurate depiction of the general market.

In a nutshell, there's a high probability that ~two-thirds of your subscribers are Apple users creating inflated metrics. Meaning…

Your Open Rate is most likely inflated.

🍎 This is due to Apple MPP.

Most ESPs embed a tracking pixel into email sends, so when you send your newsletter or an email marketing campaign, a pixel automatically gets sent along with the email. This pixel sends information back to the ESP and generates information in your dashboards, such as Open Rate.  

Typically, data from an email was loaded only when the recipient opened the email and the images from the email were downloaded. This data includes the tracking pixel, which allows ESPs to detect that the email was opened, what device was used and where the subscriber was located when they opened the email.

If a subscriber has Apple MPP-enabled, Apple will preload the images and content of emails - including the pixel – regardless if the recipient actually opened the email or not. This means a subscriber could have a 100% Open Rate due to Apple preloading the emails and triggering the tracking pixel for each email.

The more subscribers with Apple MPP-enabled, the more likely your open rates are inflated. And based on Litmus’ analysis that ~two-thirds of email opens in December 2022 are coming from Apple, it’s likely this is impacting your metrics along with any workflows, subject line testing or emails based on Open Rate or Opens.

We encourage you to take a look at your Email Service Provider’s dashboard. Do they mention in their documentation how Open Rate is calculated, or a way for you to sort by device?



🙃 Yes, Click-to-Open Rate is impacted.

Wait, what is Click-to-Open rate? Isn’t that Click Rate?

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Side note: x100 for a percentage.

For # of Clicks, it’s important to decide if it is going to be calculated as Total Clicks or Unique Clicks.

With Open Rates becoming less reliable, you may think to start using Click-to-Open Rate, but it is important to note that Opens are being factored into the equation.

Apple users with MPP-enabled might appear to open your emails, but they may or may not click links.

As your Open Rate artificially inflates, your Click-to-Open rate will artificially drop.

Click-to-Open Rate has been a great method to measure how effective content was at motivating users to click, but since it uses Email Opens, it’s now an unreliable metric.

However, Total Clicks are not impacted by Apple MPP.

You can still analyze Total Clicks across campaigns with a similar number of recipients or audience cohort as a way to assess which campaigns are getting the most engagement.

As you shift focus towards clicks as more of a primary metric for your emails and newsletters, it may be helpful to start building benchmarks for Total and Unique Clicks and Click Rate. Don’t be alarmed if Click Rates are below 1% or just lower in general than Open Rates. It’s a different metric!

Also, if you’re reporting Open Rate to dashboards, clients or sponsors, think about trying to use different success metrics like Click Rate, Conversion Rate or engagement through polls, surveys, etc.

Now, we’ve mentioned using Clicks instead of Opens a lot.

Your newsletter’s purpose may be getting all the content in that email, and not having to leave the inbox. You’re not linking out to a blog to continue reading, or linking out to a store to check out merchandise or a digital product.

That’s okay! There are other ways. Try to create opportunities for readers to click:

  • You can create a section that links out to other blogs or sites with content that fits your audience. If they didn’t have an opportunity to click elsewhere, this section may be a prime spot for readers to click in the email.
  • Encourage readers to take a poll or survey. This is a win-win because you also can learn more about your readers via the poll or survey.
  • Simply ask users to click. Tell them that you noticed they haven’t been engaging with the content, and you want to make sure it’s valuable.

😅 What about Subject Line testing? Subject Line testing is good, right?

OoOOOoh Subject Line testing. Yes, split testing subject lines has been heralded as a way to see what resonates with readers and how to get more readers to open your emails.

The subject line is the front door to your email, along with the preheader.

It’s one of the first things a reader may notice and may be a determining factor in opening an email from you, but the way some subject line testing is being done is not an accurate depiction of what’s going on with your emails.

For example, it’s common to take a percentage of your subscribers and run a subject line test with that cohort. You determine that whichever subject line has the highest Open Rate after X amount of time is the “winner”, and the rest of the list will receive emails with that winning subject line.

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If the winner of the subject line test is based off of Open Rate, and we know Open Rate is potentially being artificially inflated by Apple MPP-enabled subscribers – the output is not accurate.

You may also need to check you have a sample size to yield statistically significant results.

If you want to test a subject line:

  • Try a 50/50 approach. Send Subject Line A to 50% of the list and Subject Line B to the other 50%. Yes, send the campaign to the entire list and analyze post-send.
  • Also try to test two subject lines that are different in demeanor. When you test two subject lines, what are you learning? When testing anything in your emails – do it for a reason. Don’t just test to test.

Think about why you are testing these two subject lines. Is one asking a question? Is one in a different voice or tone? Is the word order different? What about character length? Does one include an emoji? Where is the emoji placement?

Try to make them two different approaches, and be prepared to test more than once with these theories. If you want to test emojis in your subject line, don’t let one email determine the success of using an emoji in your subject line. You may need to test it for a bit.

Also, again, think about doing a 50/50 split with the subject lines. This looks like sending 50% of readers Subject Line A and 50% of readers Subject Line B.

This means you don’t pick a winner based on the first X% that open because there’s a high probability that the opens being counted are not real opens.

If you take the 50/50 approach, you can then analyze the data after the fact. You can take a look at the tests impact on Click Rate, Unsubscribe Rate, Conversion Rate.

If your ESP has this functionality, can you remove subscribers with Apple devices from the sends and see what those results are? How do they vary?


⏸ Hold up, I have automated workflows. Does this impact automated workflows like my Welcome Series, Winback Campaign, Cart Abandonment?

Yesssss.

If any of your workflows are based off of Opens or Open Rates, try Clicks or time-based triggers instead.

A common workflow that utilizes Opens is a Sunset Policy.

We’ll get more detailed about Sunset Policies in a future post, but in a nutshell, it is a policy to remove unengaged users from email lists. This practice is good for engagement metrics, making sure you are sending pertinent emails to engaged users along with deliverability and overall sender reputation.

Engagement is typically defined as opening or clicking emails within a certain amount of time.

An example Sunset Policy might be:

  • Identify users that haven’t opened an email in the last 90 days.
  • Send them an email asking if they would like to continue receiving emails.
  • If they don’t open or click in the email, we remove them from the list.

Since Opens is being factored into the workflow, and we know Apple MPP-enabled subscribers generate false opens, we recommend not using Opens and just using Clicks.

A new example Sunset Policy might be:

  • Identify users that haven’t clicked an email in the last 90 days (this works if you have content for users to click on!)
  • Send them an email asking if they would like to continue receiving emails. Ask them to “Click here” to remain a subscriber.
  • If they don’t click, you could send one more message letting them know you’re removing them from the email list and this will be the last email unless they “Click here” to remain subscribed.
  • Then, remove them from the list.

Clicks remain a reliable metric regardless of MPP. If readers are clicking, they are engaging with the content.

Knowing that a large portion of users use Apple Mail and most likely have Apple MPP-enabled, basing anything off of Open Rate – like a Welcome flow, Sunset Policy or Cart Abandonment – is creating a workflow relying on inaccurate information and could make for some funky email experiences for users.

For example: If you think through an email flow knowing that some of your users have Apple MPP-enabled, therefore each email is going to be counted as opened even if they didn’t really open the email, what would that experience be like for the user?

Try to rethink it from a Clicks or Conversion Rate perspective. Something other than Opens.

Due to Apple MPP preloading and “opening” emails, the open timestamps are also not reliable. This means you won’t be able to easily identify the best time of day to send emails since the timestamps aren’t accurate.

📈 Apple MPP impacts nearly all metrics and workflows

What does Apple MPP impact?

For users with Apple MPP-enabled:

  • Open Rate. It is artificially inflated. Apple MPP generates false opens.
  • Click-to-Open Rate. Since you’re calculating Opens in this metric, and Opens are not accurately calculated, this is skewed.
  • Open times. If you’re using Send Time Optimization or have been trying to identify the best time to send emails, it’s hard to identify since subscribers with Apple MPP-enabled open all emails, and you don’t really know what time the email is actually being opened by the reader.
  • Geolocation. Due to Apple sending through various servers, the IP being served up in your ESP is likely an Apple server.
  • Device usage.
  • Workflows. From your Welcome series to a Winback campaign to a Sunset Policy and more, anything that uses Open Rate or Opens is impacted.
  • Segmentation. Whether creating audience cohorts by location, # of email opens, those that haven’t opened an email in the last 30 days – Apple MPP impacts this.

💭 So what do I do?

Great question.

  • Continue to monitor Open Rate, but don’t think of it as something to define your newsletter or emails success by.
  • Think about how you can incorporate other metrics, besides Open Rate, into defining success. Reflect on the goal of the email.
  • Audit workflows to make sure they are not based on Opens or Open Rate.
  • Subject line test with a 50/50 approach instead of picking a winner based on Open or Open Rate.
  • Remember that each audience is unique. What works for one company may or may not work for yours.

It’s key to consider why you’re sending an email and what metrics to focus on.

Here are some other metrics to measure success:

  • Conversion Rate. The percentage of email recipients who purchase, download the PDF, etc. You can define what it is that is converting.
  • Growth Rate. How quickly are you adding email subscribers compared to subscribers that are unsubscribing?
  • Revenue. How much revenue is being generated for every dollar spent?
  • Click Rate. The percentage of email recipients who click // # of emails delivered
  • Unsubscribe rate.
  • Email replies.
  • Email referrals.
  • Email forwards.

🔑 Key takeaways

  • Open Rate is not a reliable metric. Your subscribers may not be using Apple Mail, but based on overall high market share it’s likely they are a percentage of your subscriber base, so it is something to think about.
  • Privacy updates like Apple MPP are not novel. We will continue to see companies prioritize and release features and functionality that help protect user data.
  • Every audience is unique. What one company does and applying it to your own won’t always yield the same results. Take it as an opportunity to test hypotheses with your own audience.
  • After testing, it’s important to use the data from tests, reflect on it, figure out what happened, why did it work? That way you can incrementally become more knowledgeable about your users along with getting a better understanding of what resonates and what doesn’t.  
  • Measuring your email’s success will always be important when determining which areas to improve on for future campaigns. Think beyond opens and clicks.
  • Open Rate was great to gauge engagement via subject line and the timing of sends. Click Rate was great for overall engagement to see if content was resonating with readers.
  • But if these emails yield high unsubscribes, users are not signing up for a webinar, purchasing an eBook or driving brand awareness, it might be time to think about the goal of your emails and newsletters.


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