What Does The Impending IOS 17 Privacy Update Mean For Marketers?

We’ve been hearing whispers and rumors of a looming Apple privacy update that could complicate things (to put it mildly) for marketers. In fact, if you believe the rumors, most of the data in UTM (aka, Urchin Tracking Module) parameters will be stripped, making it extremely difficult to track the behavior of the customers/leads you drive from your ads, emails, and pretty much every other digital campaign you run. Naturally, this concept fills we marketers with a combination of emotions. Our team at IDLab feels a combination of dread, resignation, deja vu (remember IOS 14?), and, strangely enough, confidence. 

Why are we confident, you ask? Because we are preparing now, and that’s exactly what we’re going to do, together, in the upcoming pages. We’re going to go over exactly what the IOS 17 update will mean for you in the coming year, and how to continue to drive exceptional results for your businesses and, as importantly, your customers. 


Here’s The Scoop on IOS 17

According to Apple’s recent announcement, 

“Some websites add extra information to their URLs in order to track users across other websites (e.g. UTMs). Now this information will be removed from the links users share in Messages and Mail, and the links will still work as expected. This information will also be removed from links in Safari Private Browsing.” 

To put it in clearer terms – users can select a setting, at their discretion, that will eliminate all UTM parameters, click IDs, and link variables from links to your site or landing pages. The default privacy setting is currently off, but it may change at any moment, as seen with the IOS 14 update. Obviously, that poses a problem for all marketers since we are data-driven individuals, and our ability to fine-tune our marketing is based on data. If we can’t see the data, how will we iterate? 

This is even more problematic with the recent launch of GA4, which forced marketers to learn and restructure analytics for the new events-based format. Since GA4’s data is already more limited than that of a traditional Universal property, IOS 17 will compound some issues and will pose more potential issues with GA4’s data accuracy (if the data isn’t accurately segmented, that is). Think about it: How will you know how many conversions you couldn’t track (aka, 21.67% of the population that uses smartphones)? Without Google’s detailed attribution models, the overall picture gets even murkier. 

The Solution To Getting The Most of Customer Data Post-IOS 17

Don’t worry, not all hope is lost! Now that we’ve gone through the issue in-depth, let’s go through the most important part: how to continue to execute your marketing campaigns with as much visibility as possible. 

Step 1: Separate Out iOS 17 Traffic in Non-Search Paid Campaigns

First things first, preserve the data you have access to at all costs for users that have other types of devices (e.g. Android).

Meta:

Segment your campaigns to target Apple devices specifically, focusing on iOS 17. By doing so, you can maintain the cleanliness and accuracy of UTMs, IDs, and data for all non-iOS 17 traffic. While this setting in Meta Ads may be somewhat hidden within the ad set parameters, you can locate it under device-level targeting.

Google Video & Display Campaigns:

Similarly, create dedicated campaigns for Apple iOS 17 device traffic. This approach will allow you to segment data effectively within these campaigns.

Google Search Campaigns:

Unfortunately, Google Search Campaigns do not offer native device segmentation options. The best way to isolate the traffic is by using custom Google Analytics that separates the data based on device type.  

Email Campaigns:

Most CRMs typically do not provide device segmentation options. Ask your ESP (email service provider) if you are one of the lucky ones. If not, there are no workarounds at this point. 

SMS Campaigns:

Your SMS provider should have the capability to identify the device receiving the message. Utilize this data to parse your campaigns appropriately.

Other Ad Platforms:

For ad platforms other than Facebook and Google, whether or not you can segment by device will depend on the platform’s capabilities. If available, apply similar strategies as mentioned above.

Organic Social Posts:

Consider using redirect links in your organic social posts to guide users to the appropriate destinations, ensuring that your attribution and data remain accurate. These redirect links are links that you control and build within your site (pro tip, use a site plugin if you can). By using specific URL naming parameters, you can have a better chance of isolating and tracking IOS 17 traffic.

These segmentation strategies will help you manage iOS 17 device traffic while keeping your data clean and maintaining marketing attribution visibility for other devices.

Step 2: Make The Most of The Data You Do Have From Non-IOS Devices

We are realists and know that you, along with many marketers, may try to avoid or delay implementing the campaign segmentation approaches above (after all, it’s hard and puts additional demand on resources). However, if you put in the extra effort and do implement tracking mechanisms for non-Apple devices and can discern the ROAS improvements in well-segmented campaigns, you will discover that you have less competition for these audiences than expected. Advertisers who did not segment their iOS 17 traffic, and consequently observe lower reported ROAS, are likely to reduce their ad spend.

This scenario could lead to the potential for lower costs per conversion or, at the very least, an increase in revenue from your existing ad spend, resulting in higher ROAS.

In addition to decreased competition, you can extrapolate (we hate to use that word, but it’s unfortunately come to this) the data from your users with non-IOS devices to have a better understanding of what is happening with your IOS users. 

Here’s how you do that: 

  • Note the amount you spend on non-IOS traffic. Look at your conversion rate and revenue. Since you segmented the non-IOS audience, you know exactly where your revenue came from, and you can optimize from there. 
  • By subtracting the accounted-for non-IOS revenue from the unaccounted revenue, you have a better understanding of how your audience of “blocked” IOS users behaves and converts on your site. You don’t know exactly how much your ROAS is, but you have a workable estimate and can continue spending if there is a decent amount of implied return. 

Step 3: Create Dedicated URLs for Each Campaign

While this approach can be effective, it comes with some notable drawbacks such as: 

  • It demands a significant amount of time
  • Carries inherent risks
  • May limit the depth of optimization that can be achieved. 

Furthermore, its applicability in search campaigns is somewhat challenging, requiring the creation of individual campaigns for closely related keyword groups and potentially resulting in less precision in targeting. The increased number of URLs to manage tends to get messy on the back-end of your site and becomes a full-time job in itself. 

Bottom line, this is an option but think thru the return in relation to the investment on this one.

Step 4: Rely More Heavily on MER 

The marketing efficiency ratio (MER), also known as the media efficiency ratio, is a metric used to measure the overall performance of a marketing strategy or campaign from a more universal standpoint. It calculates the return on investment (ROI) of marketing efforts and helps determine how effective they are. In simple terms, the MER indicates how much money a marketer or marketing department has to spend to achieve their desired outcomes. The formula is total revenue divided by total ad spend.  

Think about it: If your campaigns are performing well overall, then you know that you’re on the right track, regardless of whether you can see the IOS devices. This process takes a more holistic approach to supplement the granular device-by-device segmentation. If MER is solid overall, then you can consider increasing spend. Consider running cohort analyses and conversion time analyses to forecast conversion increases to supplement your MER calculations. 

Step 5: To Heck With It, Just Use AI 

AI definitely has its place, and it could play a role here. It’s important to note that AI represents ‘intelligence,’ not ‘superior intelligence.’ It can’t magically generate missing data to solve the entire IOS 17 attribution challenge. All it can do is make an educated guess. With that said, you can (partially) abdicate your role in this new IOS 17-induced guessing game to AI. Although AI still makes mistakes, it makes less mistakes than you do. 

How to use AI in this instance… If the algorithms are meticulously trained on Lifetime Value (LTV) data and capable of cross-referencing pre-iOS 17 and non-iOS 17 traffic to construct precise models, a compelling argument can be made for its potential utility. However, contrary to what the news has said, we are far from finding a perfect AI-based solution. 

Although the IOS 17 situation seems bleak, there’s still hope if you apply our recommendations above and take the time to prepare NOW. 

Is IOS 17 a Good Thing for Marketers?

If we have learned one thing as marketers, it’s that we have to constantly innovate to survive the rapidly changing marketplace. Also, things aren’t always as difficult as they seem. After all, IOS 14 wreaked major havoc among marketing professionals back in 2020. We got through it, and we’ll do the same with this latest update. 

Isn’t that what makes this profession so interesting? The best marketers have learned to evolve and generate interesting and innovative solutions over the years. It’s sink or swim, but the best of us tend to rise to the top. And that’s how it should be. 

This IOS update will be particularly profitable for AI technology. If someone savvy puts together a solid algorithm that predicts customer LTV accurately and forecasts the values coming from IOS traffic for you, they stand to make a significant payday. We can’t expect miracles, but we can expect significant progress in AI forecasting out of necessity, and we also predict that an AI solution will come fast. 

It has also been said that the increase in privacy regulations will contribute to the return of “ole skool” marketing with less reliance on digital “hacks” and the newest, shiniest tech. Of course, digital know-how will continue to be helpful in the future. 

Only time will tell if you’re on the right track. However, if you need to fast-track the process, we’re here when you need us. Let’s talk

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