Fingerprinting is an mobile identification technique that relies on matching a “snapshot” of the user’s device at the time of the click. The snapshot collects information such as: user agent, operating system, and IP. If possible, other parameters like screen size may also be captured. This is then used to attribute installs.
For example, if a user interacts with an advertisement and gets directed to install the app, a fingerprint is taken of the user’s device. After the app is opened a similar snapshot is taken and the attribution provider scans its database of recent clicks to find matching fingerprints. Once a match is found, the advertiser gets attributed to the install.
Fingerprinting is very efficient when the timespan from click-to-install is relatively short—roughly within a few hours. Here’s how fingerprinting works:
Here’s the problem: these fingerprints are often so similar that 30-40% of them get paired to a completely different user (if you’re on shared wifi or a busy cell tower, the error rate can be over 50%). Fingerprints also start decomposing as soon as they are taken, which means they become pretty much useless within an hour or two. Attribution networks typically claim to offer some sort of advanced fingerprint filtering algorithm, but you can’t make gold out of dirt—the entire process is inherently inaccurate. Before you know it, fingerprint matching errors mean Jack is walking across that bridge you built for Sarah. Unfortunately this is a fundamental flaw and even with complex processing algorithms, it cannot be solved effectively.
It’s important that you find a cross-platform attribution solution that goes beyond fingerprinting, to minimize misattribution of app install sources.
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