Android apps downloaded from Google Play and some other app stores are usually attributed by the install referrer method. The referrer provides the original URL, clicked before redirecting to the Android store. This is the primary method for Android attribution. Currently, Google Play, Huawei app store, Samsung Galaxy Store, and Xiaomi GetApps Store, support install referrer attribution. Alternative app store attribution using the referrer.

The ad network, which has access to the user's device, sends the device ID to AppsFlyer on the click URL, or when notifying AppsFlyer that an impression has been served. This allows AppsFlyer to match the click device ID with the device ID fetched by the AppsFlyer SDK.

Device ID matching is the primary attribution method on iOS.

Available IDs are:

• iOS devices: IDFA, IDFV
• Android devices: having Google Play services: GAID 
• Android devices without Google Play services: OAID, Android ID, IMEI, Fire ID 

Device IDs can be hashed using SHA1 or MD5 on attribution links.

• The identifier for vendors (IDFV) is available in iOS 6.0+. It is not subject to Apple ATTrackingManager and LAT mechanisms. It is always available and can be used for cross-promotional advertising of apps from the same vendor. 
• AppsFlyer SDK collects IDFV by default. 
• According to Apple, The value of this property is the same for apps that come from the same vendor running on the same device. 
• An IDFV is generated by Apple when the user installs the first app of a given vendor. Meaning, Apple checks that there are no other apps from the same vendor on the device. As a result, deleting all the apps of a given vendor and then installing an app from the same vendor results in a new IDFV. 
• You should send IDFV if available. It improves attribution. We make use of IDFV in a number of scenarios including: 
  • Cross-promotion attribution.
  • Reinstall attribution on the same device.
  • Raw data reporting.
  • Audiences.

Upon the first app launch, AppsFlyer checks in the app settings if traffic is expected from any of the self-reporting networks (SRNs), like Meta ads, Snapchat, and Google Ads. 

AppsFlyer queries the relevant SRNs using the unique device ID of the new install. The query uses Mobile Measurement Partners (MMP) APIs as defined by the SRNs. Based on the response, AppsFlyer may attribute the new uses to an SRN.

Probabilistic modeling is a statistical technique leveraging machine learning to estimate campaign performance. Probabilistic modeling parameters are collected:

• Initially on the click or ad view (if enabled)
• Again when the app is launched

Note for iOS apps:

Starting iOS 14.5+ probabilistic modeling is limited to the context of owned media, cross-promotion, and consented web-to-app flows. In other contexts, Aggregated Advanced Privacy is used.

Implementation characteristics

• Uses statistics and is not based on unique IDs.
• Is a fallback method, used in the absence of a referer or advertising IDs. Deterministic attribution methods, i.e., clicks with referrer or ID matching, are given priority if they occur within the lookback window. 
• The attribution window is determined by AppsFlyer dynamically, based on the user network. The window duration is adaptive but shorter than the window of other methods (up to 24 hours).
• Click-through probabilistic modeling is always enabled. 
• View-through probabilistic modeling needs to be enabled in the app settings page and in the integration tab of non-SRNs. For CTV, PC, and console apps, this is enabled by default.

Aggregated Advanced Privacy (AAP) exposes campaign performance results in an aggregated manner, preventing any option to track users across apps and websites owned by different companies, and the ability to uniquely identify a user or a device.

AAP utilizes the Apple SKAdNetwork privacy levels as a minimum benchmark for its privacy-preserving thresholds. AAP is the default attribution model for Apple devices operating on ios 14.5+, except in cases that are explicitly permitted by Apple, such as owned media, and ATT consented users.

Unlike the other attribution methods described, the AAP machine learning algorithm's goal is to maximize the accuracy of the campaign’s aggregated performance, not the end-user attribution accuracy.

In preload campaigns, the app is installed on the device by a preload partner either at the factory or upon device activation. Preload partners are:

• Original Equipment Manufacturers (OEMs)
• App discovery platforms
• Mobile carriers

There are 3 ways to attribute preload campaigns:

• AppsFlyer referrer preload
• Google Play auto-install (PAI)
• Preload in factory via System Property

The AppsFlyer referrer preload solution provides visibility and measurement capabilities between first device activation and first app launch. This solution enables recording how many devices were activated by a certain partner with the app preloaded on the devices, and then when a certain app is launched for the first time, This data enables AppsFlyer to accredit the partner that drove the preload.

For the two other methods, attribution is determined only after the user launches the app for the first time, and there’s no visibility of the number of devices that had the app installed before the first launch.

All three methods can be used simultaneously without interfering with each other’s mechanisms.

Use the following table to differentiate between different preload attribution methods in raw data reports:

Note that it can take days or weeks, starting from the time the user turns on their device for the first time, until they open the preloaded app for the first time. Consequently, AppsFlyer gives preload campaigns the highest priority in determining the attribution, with longer lookback windows.

For re-engagements only, users aren't redirected to an app store to download the app. Therefore, the information in the URL can be directly connected to the click (and subsequent app open). This attribution method is referred to as deep link, since it's the deep link URL that carries the information used to attribute the re-engagement.

Most installs are the result of user clicks on ads, like banners, videos, and interstitials.

Upon the ad click, a click lookback window opens having a default duration of 7 days. Installs occurring within the lookback window period are non-organic and are attributed to the media source. Installs that occur after the duration of the lookback window are considered as organic installs. Often referred to as being organically attributed. 

• A seven-day click lookback window is regarded as the industry standard. Set the window duration in accordance with your agreement with the media source. 
• Align SRN lookback windows with the duration determined by the SRN. 

Related reading: Lookback windows

Users who view ads, but do not click on them, can be attributed to the ad network serving the ad.

The lookback window for view-through attribution:

• is shorter than that of click-through attribution
• is configurable.

To enable the view-through attribution, set the lookback window in the configuration window.

This is especially helpful for video ad networks that traditionally have low CTRs on their video ads, but also for traditional ad networks serving regular ads.

In cases where both a click and an impression occur, the click always prevails, as it is an active engagement.

Related reading: View-through attribution

AppsFlyer creates a unique AppsFlyer ID for an app install that is associated with attribution details. This enables the platform to attribute in-app events to the original media source. Advertisers can use this information to follow user journeys in their app's raw data.

For more information about event attribution, click here.

AppsFlyer fully attributes only one media source per install, usually using the last ad click or the last ad impression (if there were no clicks).

Assisted Installs (AKA multi-touch attribution) are installs where the media source/campaign was not the last touchpoint but touched the user before the install and the touch took place within the attribution lookback window.

Assisting networks are shown as contributors to the install in AppsFlyer.

For more information, click here.

A reinstall occurs when a user installs the app, uninstalls it, and then reinstalls it. Reinstall attribution is regulated by the re-attribution window as follows:

• If the reinstall occurs after the expiry of the re-attribution window: a new install is recorded.
• If the reinstall occurs during the re-attribution window, one of the following applies:
  • If the user engaged with a retargeting campaign before the reinstall: a retargeting reinstall (AKA re-attribution) is recorded.
  • If the user did not engage with a campaign or engaged with a UA campaign: no install is recorded. Depending on the Post Reinstall Events Attribution state, in-app events of these reinstalling users are either attributed to organic or to the original install. 

For device testing and multiple installs, register the device in AppsFlyer. If you don't register the device only the first install is recorded.

Note that AppsFlyer enables better accuracy for attributing iOS reinstalls without advertiser ID. You can enable this feature on the App Settings page.

Reinstalling iOS apps that are backed up in iCloud

When an application is backed up using iCloud and later restored (on the same device or on another device), AppsFlyer doesn't count it as a new install or reinstall. A user who restores an app from iCloud maintains their AppsFlyer ID and attribution data.

A user who re-installs an app within the re-attribution window (90 days by default) is considered a re-attribution. If this install occurs after engaging with a retargeting campaign, it is recorded as a retargeting reinstall AKA re-attribution and is reported in retargeting. 

• When existing users update the app to a subsequent version, this is not treated as a countable attribution event, if the user was previously attributed by AppsFlyer. Note! If you migrate to AppsFlyer from a different MMP existing users on the first app-open, after migration, are attributed to organic. 
• Metrics relating to the number of users per app version are available in the SDK Information dashboard.