Device Fingerprinting Methodology

Attribution Analytics uses device fingerprint matching as the fall-back method for attribution if none of the supported unique device identifiers are available. For a complete list of attribution methodologies, please visit Main Methodologies for Attribution.

For information about unique identifiers, please visit Unique Identifiers for Attribution.

Fingerprint matching is particularly useful for installs via a mobile web browser because these browsers are unable to collect unique device identifiers (so other attribution methods are not possible) and therefore, we rely on device fingerprint matching to attribute app installs to user clicks.

Attribution Analytics prefers device fingerprint matching over cookie-based measurement because fingerprint matching occurs asynchronously in the background of the app. Apple also adopts a policy of rejecting apps that use cookie-based measurement, making fingerprint matching the new standard when a device ID is unavailable.

Device Fingerprint Methodology
 

How Device Fingerprint Matching Works

Device fingerprint matching works by redirecting users through a TUNE link and collecting the publicly available HTTP headers about the device, which Attribution Analytics uses to create a unique fingerprint for the click of the TUNE link.

When a user installs the mobile app, the TUNE SDK collects the same data points from within the app and sends them to the Attribution Analytics platform, which generates a device fingerprint and subsequently searches for clicks with the matching fingerprint. Attribution Analytics attributes the install to the last click with a matching fingerprint.

By default, the look-back window (or attribution window) for matching device fingerprints is 24 hours. So to find a match, Attribution Analytics only considers the clicks that occur within 24 hours from the install.

While other ad networks and advertising partners (publishers) claim accuracy beyond 24 hours and apply look-back windows of 48 and 72 hours, we find that device fingerprint matching is not statistically accurate beyond 24 hours.

Gross vs. Unique Clicks

When a user clicks a TUNE link and gets redirected, Attribution Analytics sets a cookie to distinguish gross clicks from unique clicks. This cookie expires after 24 hours.

If a device does not have a cookie set, then Attribution Analytics considers the user a new user, and logs the click as both a unique and gross click.

If a device does have a cookie set, then Attribution Analytics considers the user an existing user (within the last 24 hours), and only logs the click as a gross click but not a unique click.

We measure gross clicks versus unique clicks to help determine if users are new or existing. If Attribution Analytics identifies the user as an existing user within the last 24 hours, then Attribution Analytics does not create an additional fingerprint for the same user; instead, Attribution Analytics updates the last click time for the fingerprint (previously created for the user). With this method, users who click multiple times do not create additional device fingerprint profiles, thereby limiting the number of false positive matches.

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