Ensuring you have clean reporting and analytics in iOS14

Since Apple launched their App Tracking Transparency (ATT) rules last week, developers and app marketers have been calculating its impact on the industry. But while the initial effects are starting to be seen, the long-term ramifications are still becoming clear.

Over the past year, we have been talking to a number of advertisers and ad networks about how they foresee the app marketing ecosystem changing in the near future. This is the latest installment in our blog series where we help shed some light on some of the most complex topics.

In our earlier blog, we talked about duplication and billing, so let’s tackle reporting and analytics.

With fewer users sharing their IDFA, how can advertisers analyze their campaign performance with the limited dataset and measurement window provided by SKAdNetwork (SKAN)? It’s important that advertisers across the entire ecosystem are educated on all the options so that they can decide what’s right for their business.

We’ve broken down the most common options, and how they work together, to give our clients and partners an idea of how they should be thinking about analytics in the post-IDFA world — and how Adjust can help.

We provide full support for SKAdNetwork’s features via our new Data Canvas visualization tool (now Datascape) and our existing Adjust Automate product.

Apple introduced SKAdNetwork in 2018, ushering in a different approach to campaign measurement where data at the user level is not available. With iOS 14, the SKAdNetwork framework has been developed and expanded as Apple attempts to lessen the impact of reducing developers’ access to the IDFA.

SKAdNetwork provides space for 6-bits of downstream metrics, a number between 0 and 63 (or between 000000 and 111111 in binary), with an initial 24-hour timer. This ‘conversion value’ can be assigned any value that can be expressed in binary. Every time the conversion value is updated, to a fresh six-bit code defined within the app, this extends the timer window by a further 24 hours.

Once the first timer expires, a second 24-hour timer for attribution starts counting down. Within this 24 hour window, randomly, the SKAdNetwork returns the attribution data. The idea behind this random timer is to obfuscate the time of install, so that event triggers cannot be linked to individual users. The SKAdNetwork system shares this data in the aggregate, with no granular data accessible at the user level.

Advertisers running SKAdNetwork only will have little to no analytics on their new users. All metrics such as Cohorts, ROAS, LTV will either not be possible at all, or inaccurate, which will make it hard to analyze performance. One potential exception is for advertisers who buy CPI and have most users trigger the relevant conversion within the first 24 hours. In this case, SKAdNetwork only might work well enough.

In this approach, SKAdNetwork will be the billing source of truth, provided that network partners support SKAdNetwork fully — ensuring clean billing. However, for optimization there will be the possibility to rely on Adjust’s Extended Privacy Measurement solution. In addition to SKAdNetwork data, we will also provide actionable analytics to all advertisers.

Using Extended Privacy Measurement, advertisers can then analyze their campaign performance both in aggregate and raw data in order to improve their app experience. This method will not share any information with third party channels — except for SKAdNetwork data.

Similar to the case above, SKAdNetwork will be the billing source of truth on the media partners, even if Probabilistic Attribution is being used. And with Probabilistic Attribution, advertisers will get similar postbacks to those via Extended Privacy Measurement. However, this method will also send postbacks to media sources. This will help them understand how their campaigns are performing and optimize their models accordingly to provide the best results for their advertisers.

The main downside is that this is not deterministic and is merely a best guess at attribution. This will mean it will not match up precisely with SKAdNetwork installs. In some cases, we have seen pretty significant differences due to both the nature of the attribution method as well as the difference in attribution window. However, it will still provide all media channels with some level of information on their audience so they can attempt to optimize campaigns on behalf programmatically on behalf of advertisers.

We believe it is best practice that networks use Probabilistic Attribution for optimization but rely solely on SKAdNetwork for billing purposes, thereby avoiding the duplication of billing we warned of in the last blog post.

If you have any questions about the implementation of iOS14, don’t hesitate to reach out to your CSM or account manager. And pay attention to the Adjust blog in the coming weeks for more information about how to prepare for the imminent launch of iOS14’s privacy changes or check out our always up-to-date iOS and SKAN Solutions.