Apple continues to send shockwaves throughout the digital marketing ecosystem with each new iOS rollout. Acquisition marketers were first to feel these effects, and with the recent iOS 15 updates, retention marketers are next in line.
When iOS 15 users opt in to privacy mail protection, open rates for mobile Safari and Apple Mail users will, by default, appear as 100% opened. And, because email marketing service providers use a combination of click- and view-through attribution windows—instead of breaking them out separately—this will lead to complications when connecting revenue to email campaigns and flows. With Apple Mail accounting for approximately 40% of email client market share, this is cause for concern.
Inflated open rates lead to over-attribution
Here’s an example of how this change can skew revenue attribution in Klaviyo, a leading email marketing platform that we often recommend to our clients.
Acme Widgets uses Klaviyo’s default five-day click/view attribution window. On Monday, Frank, Acme’s email marketing manager, sends an email promoting a big sale. Jane, an opted-in iOS 15 user, receives the email—but she never opens it. However, she wakes up Wednesday and remembers—completely unrelatedly—that she’s been meaning to buy some new widgets. Jane goes straight to Acme’s website and places an order for $200 worth of product.
At the end of the week, Frank checks his campaign’s performance. Klaviyo informs him that Jane’s $200 purchase was attributable to his email. Frank has no way of knowing that this isn’t true: Because Jane has Apple Mail privacy protection enabled, Klaviyo reports that she opened the email, even though she didn’t. And because she happened to make a purchase within the five-day window, that $200 is mistakenly attributed to the campaign.
One or two mis-attributed purchases is no big deal. But multiply the scenario above for a brand with 100,000 subscribers—approximately 40% of whom are Apple Mail users—and things start to get hairy.
From click/view to click-only: What’s the problem?
One way to ensure accurate email revenue attribution is to switch from click/view attribution to a click-only attribution model. This means that instead of simply opening (or “opening”) your email, users must click through to your site and make a purchase within five days for Klaviyo to assign credit to the campaign.
Here’s the challenge: Going from click/view to click-only means you’ll see a drop in reported email revenue. How can you be sure that decrease is directly related to the attribution switch, and not other factors like poor subject lines, messaging fatigue, or unappealing offers? Remember, Klaviyo doesn’t share historical breakdowns of which revenue is attributed to clicks and which is attributed to views; it reports one aggregated revenue metric. Purchases like Jane’s are combined with purchases made by people who actually place an order after clicking through from an email. Lacking proper context, planning for this expected drop in reported revenue—and more important, assessing future performance—can be daunting.
Things would be easy if Klaviyo reported that, historically, 30% of Acme’s revenue is driven by email views and 70% by clicks. If that were the case, and Acme saw a 30% drop in attributable email revenue after switching to click-only, Frank could be confident that the only reason for the change was the difference in attribution model. He would not have to worry about rethinking the content and timing of his campaigns. However, if Acme saw a 50% drop in attributable email revenue after making the switch, it would be clear that something about the campaign itself had contributed to the decline, and Frank would need to reassess his strategy for the month.
Even though Klaviyo doesn’t provide this information, with a little effort (and math), you can find historical click-to-view percentage breakdown for email revenue. Then, you can use this data to inform your strategy going forward.
Predict the impact of click-only attribution on revenue reporting
First, head into your Klaviyo dashboard’s analytics and pull up Total Placed Order by Attributed to Message Type. Filter the visual to only display orders attributed to campaigns and flows, and add up total placed orders year to date. This total serves as the number of click- and view-through orders attributable to email, year to date. Save this number for the final step.
Next, open Google Analytics and locate Conversions on the left-side panel. Open Multi-Channel Funnels, then Assisted Conversions. Set the report date range to year to date. Make sure you have selected Transactions as the conversion type, and set your lookback window to match what is set in Klaviyo. In the screenshot below, I’m using the default five days.
Next, scroll down in the report and locate the Email channel grouping. Add up assisted conversions and last click or direct conversions for this row. This number is the approximate number of click-through purchases attributable to email, year to date. Save this number for the final step.
We have now effectively pulled the number of click and view-through orders from Klaviyo, as well as click-only orders from Google Analytics. Dividing the Google Analytics number by the Klaviyo number will give a fair and accurate estimation of click-through attribution percentage for the year to date.
In the example screenshots above, the number I got from Google Analytics is 1,201, and the number from Klaviyo is 1,652. So, for the year to date, approximately 73% of total email revenue is attributable to clicks.
With this benchmark in mind, I can switch to a click-only model and get a more accurate representation of email’s impact on top-line revenue. This metric is useful on its own, and can also inform big-picture revenue forecasting.
Understanding email marketing performance is more important than ever, as is using data analytics to drive insights. If your business has a lot of Apple Mail subscribers, and you’ve noticed a sudden spike in open rates and revenue attributable to email, that’s a flag that iOS 15 is having an impact on your reporting. But before you jump headfirst into click-only attribution, take a moment to run this quick calculation. Then, when you see those lower figures, you won’t be alarmed—and you can be confident that you know what’s really behind them.