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Making SKAdNetwork performant without fingerprinting (and getting 80% accurate pLTV)

By John Koetsier August 20, 2021

Can you get great performance out of SKAdNetwork? And can you make it as performant as IDFA or fingerprinting?

It’s a valid question, because as we saw in a recent Singular webinar, a huge percentage of the mobile marketing ecosystem is still using fingerprinting whenever they can to attribute app installs … in spite of the fact that Apple has explicitly forbidden tracking without consumer opt-in.

 

Making SKAdNetwork performant

According to Singular CTO Eran Friedman, you can actually make SKAN performant, and the top mobile marketers at major brands are doing exactly that today. And while — let’s be honest — it’s tough to approach the IDFA-powered levels of marketing measurement mobile marketers enjoyed in iOS 13 and earlier … you can get 80% accurate predictive lifetime value, and smart marketers are learning the ropes on SKAdNetwork now.

That’s important because those who aren’t jumping on the SKAN bandwagon now run the risk of cratering their performance in a few months when iOS 15 or 15.3 or 15.6 destroys marketers’ ability to get accurate fingerprinting-based marketing measurement.

“It’s not that easy for sure.

I think most of the industry today is struggling with SKAN trying to make it work.”

– Eran Friedman, CTO, Singular

Elephant in the room first: it’s tough. It’s not easy. It’s a massive change in thinking, in technology, in process, and even — in some cases — in how your mobile app experience is engineered, particularly for the onboarding and first few experience stages. But early adopters who jumped on SKAdNetwork early and have been working at it for some time have seen success, says Friedman.

Better success than some might think, in fact.

“For the marketers who could make it work … definitely they’ve been able to get comparable results [to] IDFA, without the device-level data.”

– Eran Friedman

That’s a big statement. IDFA is still the gold standard, along with AAID/GAID on the Android side, of course. Full access to a fairly persistent device identifier which allows you to see impressions, clicks, installs, and basically unlimited post-install events is powerful. It’s addictive. It’s the One Ring of mobile marketing that connects all the dots and makes everything possible.

Or, it did.

In the past.

 

The risk of just doing fingerprinting for attribution

On iOS, that’s just simply not there anymore. While some marketers are turning to fingerprinting to solve the problem, it’s risky — Apple could start enforcing its rules at any time — and it likely comes with an expiration date. iOS 15 will bring additional intelligent tracking prevention, HTTPS upgrades, privacy reports, Private Relay for running web traffic in a VPN, and more. Most of iOS 15’s new privacy features are focused on the web, but given that Apple continually innovates and iterates, you can safely assume they will come in app environments as well.

Apple, after all, is not unaware of the fact that people spend most of their smartphone time in apps.

So saying that top marketers who are using SKAdNetwork for mobile marketing measurement are achieving results in the same ballpark as IDFA — even if not quite as good — is a big deal. It’s surprising, even shocking.

But it’s also very, very good news.

It means that the death of mobile measurement has been greatly exaggerated.

Making it happen, Friedman says, requires work: lots of it. And time: plenty of it. And significantly good BI teams who help you generate good insights from highly predictive behaviors. Importantly, it also requires persistence: many who invested early in integrating SKAN into their growth tech and data stacks got horrible results at first. Initial models were “a complete wreck,” with data that didn’t make any sense.

 

pLTV is the key to making SKAN work

But the first step was building the reporting to see the data. The second step was figuring out how to make it accurate, despite privacy thresholds, timing delays, and other gaps.

While top brands with the best teams and most money are over-represented on the list of those who have now figured it out, there’s some smaller companies who have done well, Friedman says. Including some hyper-casual companies.

“If you’ve invested the time in your BI, in your prediction models, then it becomes much easier to optimize your campaigns.”

– Eran Friedman

And that’s the third stage: optimizing.

Here, pLTV, or predictive lifetime value, is absolutely essential.

“Now that you have data that you can trust, then the companies are thinking: how can I optimize and scale, which is kind of the next big challenge,” Friedman says. “And for that, you actually need the networks to optimize a lot on your campaigns … and for that, you need to give them proper signals and the best signals really are ROAS or LTV, right? If you can tell them what’s the predicted LTV of that user within the 24 hours as part of the SKAN postbacks, then the networks find it much easier to find more of these users.”

Which is challenging, of course.

But, clearly possible.

The critical component, obviously, is a pLTV model that reliably highlights your most valuable users and customers very early on in their experience with your app.

“The holy grail, the ideal, is to actually encode the conversion values in real time, based on pLTV … basically you’re already notifying to the ad networks when they get postbacks, what the predicted value of that user. That requires a bit more engineering.”

– Eran Friedman

Top marketing and product teams are able to boost reliability of those predictions to around the 80% level, Friedman says. Which is startling good: better than I ever expected in the early days of iOS 14.5. And it has the potential to get better, as Apple continues to add features and functionality to SKAdNetwork over time.

Which, potentially, shows the carrot and the stick, right?

The stick might just be iOS 15 or 15.5, where it becomes harder and harder to circumvent iOS 14.5’s privacy rules. The carrot might just be an increased ability to accurately measure mobile app install marketing in a privacy-safe way.

 

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