These two challenges weigh heavily on MMPs

Author: Steffen Meyer, Mobile Marketing Content Specialist

A Mobile Measurement Partner (MMP) is essential for your app marketing since it lets you centrally manage your advertising. However, the app marketing world is changing and this brings challenges for MMPs. You should know about these to make informed decisions when partnering up with them. 

There are two most pressing challenges which we will explain here. These are:

  • Self-Attribution
  • Privacy initiatives


Usually an MMP collects all clicks from ad sources, so it can attribute them accordingly when a user installs an app. For example, a user clicks on an ad from advertiser A but then browses around the internet for a while. After a while, he clicks on another ad by advertiser B and installs the advertised app. Since the MMP knows that advertiser B came after advertiser A, it can attribute the last click before the install to advertiser B.

However, this is different with self-attributing networks, so-called SANs. These networks don’t report every click to an MMP. Instead, when an MMP registers an install, it sends this information to a SAN, and the SAN will report all clicks that – according to their insights – correspond with this install.

So the MMP basically has to trust the data the SAN reports to them, making the whole process way less transparent – and some say even more prone to possible fraud with fake numbers.

You might wonder: Why would anyone cooperate with a SAN then? 

Well, the bigger the network gets, the more powerful it becomes, the more likely it will become a SAN. Basically, all large networks follow this self-attribution process: While Facebook was the first, Twitter, Google and Snapchat followed suit, and Tiktok is about to.

So if you don’t want to miss out on these big networks (which you probably don’t), there’s no way around SANs – and the lack of transparency that comes along with it.

Privacy initiatives

Not only lawmakers but companies themselves implement new privacy rules, making it harder for MMPs to gather as much data as before.

With iOS 14.5, Apple introduced the app tracking transparency network (ATT): Users are now prompted when starting an app the first time if they let advertisers track granular device data, the IDFA (read more on this in this blogpost). As you might expect, not many users opt-in when presented with this option.

In the beginning, only four percent of users agreed. According to a study by the MMP Adjust, this number rose to around 25 percent. 

But even though more and more are willing to share their data, it is still only a fraction of all Apple users that do so. That is why the companies’ proprietary SKAdNetwork got more attention: It has access to 100% of the users but it reports with a time delay and provides less granular data.

This makes the job for MMPs harder since their whole business model is based upon gathering valuable data.

Apple isn’t the only company with new privacy rules. Google announced this year its Privacy Sandbox. Though it takes a different approach than Apple’s ATT: Instead of asking the users if they want to share their GAID – the Android’s pendant to IDFA -, Google answers for them automatically. With a No. 
But compared to Apple’s initiative, Google explicitly mentions the role of an MMP and seems to see them as partners, though it remains to be seen what happens after the release of this initiative.

MMPs are still useful

Whatever the described challenges are, MMPs keep on being a vital element in your app marketing since still they offer advantages:

  • Without an MMP you would have to manually install the Software Development Kits (SDKs) of all ad networks you want to use. With an MMP, you just need to install one SDK and manage all your networks from one central tool.
  • Furthermore, if you want to disconnect an ad network from your app, an MMP lets you do this easily. Otherwise you would have to delete the network’s SDK and actually wait until all users have upgraded to the latest version. Quite a hassle.
  • And even with the challenges of self-attribution and privacy initiatives, MMPs try to adapt with so-called probabilistic modeling. Though it’s hard to say much about the reliability, it shows that MMPs don’t just stick their head into the sand but rather try to adapt to the new attribution world.

And of course, we at Customlytics aren’t sleeping either. So if you want to know more about MMPs, the challenges, and how to combat them, just drop us a line.

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