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Sending first party data to MMPs in a post iOS 14.5 world

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Moloco
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June 11, 2021

Since the announcement of iOS 14.5, there’s been no shortage of confusion in the mobile marketing world. Despite Apple’s efforts to clarify expectations, there remains a good deal of ambiguity around what’s acceptable in the post-IDFA landscape when it comes to optimizing mobile ad campaigns. To some marketers, one particularly important question remains unanswered:

Can I send my first-party data to MMPs and other strategic growth partners?

At Moloco, we believe that the balance between user privacy and marketing insight isn’t complicated. iOS users have the right to decide whether or not app developers know who they are and whether or not they can be tracked. Apple’s new ATT framework has ensured that.

App developers, on the other hand, have a right to know how users engage with the apps they create. In fact, it’s their responsibility. Without it, developers couldn’t address issues impacting the user experience. Post-install activity data is key to effective product evolution, and it belongs to app developers. It’s their data, they own it, and it’s up to them how to use it. Based on the wording of Apple’s own privacy guidelines, we believe this includes sharing that information with strategic partners. Here’s why:

First-party data transmission is not tracking

Providing MMPs with post-install activity data streams that include IDFV does not constitute fingerprinting/tracking and therefore would not contradict Apple’s privacy requirements for advertisers. Apple’s definition of tracking as it states in its User Privacy and Data Use guidelines (emphasis ours) is centered around combining first-party data with external data: 

“The ID for Vendors (IDFV), may be used for analytics across apps from the same content provider. The IDFV may not be combined with other data to track a user across apps and websites owned by other companies unless you have been granted permission to track by the user.” 

What IDFV and first-party data does allow for is the development, enrichment, and validation of persona-based app marketing strategies. These are common-place in all industries, involving the construction of fictional profiles made up of common traits shared by target customers that can be referenced when making key marketing decisions. It’s so common, in fact, that Apple does it too, and here’s how.  

Sharing data facilitates the same strategies Apple uses

Apple depends on personas just as much as anyone else for the effective management of their owned iOS advertising products. Personas are the building blocks of market segmentation, which is the practice of subdividing an addressable market in order to tailor communications and optimize resource allocation for maximum impact. Examples of common market segments include:

 

  • Affluent females living in New York
  • Socially active males from San Francisco
  • Early tech adopters living in rural Canada
  • Crime fiction fans from southern California

 

This is the very practice that Apple uses in the operation of its own ad networks, as clearly noted in its advertising and privacy support page, in which it explains how an Apple user’s name, address, gender, device information, and download history are used to create user segments that help them optimize targeted advertisements in the App Store:

“We create segments, which are groups of people who share similar characteristics, and use these groups for delivering targeted ads. Information about you may be used to determine which segments you’re assigned to, and thus, which ads you receive.”

It’s worth noting that unlike the opt-in nature of ATT, Apple’s personalized ads are enabled by default. Regardless, developers would be within their rights to employ the same advertising strategies used by Apple itself. It’s all the more important, in fact, given what can be achieved when first-party data is combined with machine learning while still respecting the user’s right to privacy.

What’s made possible by first-party data 

Given access to post-install activity data streams, MMPs and the advertising partners they support are afforded a wealth of options when it comes to optimizing user acquisition in the post-IDFA world. In the case of automated buying platforms that leverage machine learning for campaign optimization, like Moloco Cloud, it allows for powerful persona-based marketing strategies to be deployed at scale, especially when conversion values and campaign data from SKAdNetwork are involved.

Using persona-driven machine learning models, Moloco Cloud can empower advertisers to create the same types of anonymized segments based on aggregated activity data that Apple’s own ad solutions use for targeting. These segments can then be leveraged in the open programmatic ecosystem to tap into valuable pockets of inventory otherwise invisible to automated media buying solutions. This includes optimizations for device models, location, and more. All without ever violating a user’s right to privacy or relying on a data set that would allow them to be tracked beyond a developer’s app portfolio.

Moloco is committed to keeping channels open

These are admittedly uncertain times for app marketers. Trepidation is natural, and while some developers may opt to pause transmission of first-party data to MMPs, Given access to post-install activity data streams, MMPs and the advertising partners they Our goal is to provide as many options as possible for developers looking to leverage the power of their first-party data. Contact us to learn more.

Moloco

Moloco

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