3 app attribution “gotchas” to watch out for

By Saadi Muslu June 5, 2017

Mobile app attribution is one of the cornerstones for growth-oriented apps and a critical layer in the mobile marketing stack. Roughly 80% of the top 500 mobile apps on iOS have implemented an attribution solution, according to a study by mobile app analytics software Mobbo.

Briefly, mobile app attribution allows you track the source of incoming app installs or engagements. To identify the channels of user acquisition that work best in the long-term, attribution also measures in-app events that occur after the download, also known as post-install events.

Yet when it comes to mobile app attribution, there are “gotchas” that can trip up even the most seasoned digital marketers, leading to wasted time, skewed or opaque analytics and under-performing campaigns.


App opens vs. app installs

Marketers have to keep in mind that mobile app attribution systems define an “install” as the first time the app is opened on a user’s mobile device. But actually, a mobile app open is just the earliest time a third-party attribution platform can track a new user, so they take this first open and call it an install.

The reality is that the only systems that know about actual installs at the precise time of app install are the app store owners, Google Play and Apple.

As a result, discrepancies often exist between the statistics in your attribution platform and App Store dashboards. For instance, a user might have installed the mobile app on Tuesday, but launched it a few days later on Friday. The App Store dashboard would attribute the install to Tuesday, while the attribution platform would attribute the install to Friday.

Or if a user installed the app, but never launched it — attribution platforms wouldn’t register the download, while App Store dashboards would.

(And, of course, we’re not even talking about the situations when a self-attributing network claims an install via view-through attribution but the install is actually more directly caused by a click on another ad network’s ads. More on that later.)

While marketers should seek to reduce mobile app install data discrepancies wherever possible, it’s important to recognize that a host of reasons make minor data discrepancies inevitable. Marketers, then, are tasked with identifying thresholds for acceptable levels of discrepancies. When a discrepancy between two data sources — for instance, your attribution platform and your network dashboard — exceeds a certain threshold, it usually means something is wrong and needs fixing.


What’s my app attribution window?

The Attribution Window is the amount of time that can pass between a user’s click or view of an ad and their install. Consider the example of a user who clicked a mobile ad on the 10th of December, but didn’t install the app until the 13th of December.

If the attribution window is set for 3 days or more, the install will be attributed to the ad. But if the attribution window is set for only 1 day, the install will not be attributed to the ad. Instead, it’ll look like an organic install.

Data discrepancies can also arise when the attribution window in your attribution platform is not aligned with the attribution window in your network. In many cases, networks will set as a default an attribution window that is different than the attribution window in your attribution platform. It is advisable to first work with an attribution platform that allows you to customize your attribution window and second, to ensure that you have the same attribution window set up in your ad network and attribution platform.


Whose click is it anyway?

Advertising networks don’t know about user interactions with ads on other ad networks. As a result, the same mobile install might be attributed to two or more ad networks.

Consider the following example: yesterday the same user clicked on a Facebook ad and then a Google AdWords ad before installing the mobile app today. In this instance, Facebook will take credit for the install in the Facebook dashboard, while AdWords will also take credit for the install in the AdWords dashboard.

Attribution platforms that operate according to a “last click” attribution model will “de-duplicate” the conversion and attribute the install to AdWords activity. That means you know which ad network had the last and presumably most important impact, but it also means a discrepancy can arise in the number of Facebook-driven installs that appear in your attribution dashboard and the number of installs that appear in your Facebook dashboard.

To monitor such discrepancies, marketers should work with attribution providers like Singular.

Singular displays both figures: the statistics reported by the network and the statistics reported by our attribution solution alongside each other. Now marketers don’t have to toggle back and forth between their attribution platform and their network dashboards to see what’s actually happening. In addition, using Singular, marketers can customize which source they want to use as the source of truth and set alerts when discrepancies between sources exceed a given threshold.


Summing up …

In sum, mobile attribution is complex … with plenty of “gotchas” that can create major headaches when attempting to perform data analysis and optimizations based on inaccurate or misleading data. In order to succeed, marketers must stay cognizant of the intricacies and leverage partner tools that are both transparent and make it easy on marketers to spot broken campaigns and illegitimate data.

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