What Is Android Advertising ID (AAID)?

By Vungle | February 17, 2022

Here’s everything you need to know about the ad-centric identification feature for Android users, and what changes are coming its way.

A pillar of any advertising philosophy is ensuring that the right people see the right ads at the right time. The Android Advertising ID (AAID) has been a central component of making that happen, but growing privacy concerns have led Google to rethink parts of AAID’s implementation.

Advertisers not only need to adapt to how Google’s changes to AAID are impacting campaigns now but also how they’re likely to influence strategy in the future. This article provides a fundamental understanding of how AAID functions, the role it has played in targeted advertising, and what the changes to the Android operating system mean for marketers.

Jump to a section…

What is Android Advertising ID?
What is AAID used for in mobile advertising?
Why is Android changing how apps can access AAID?
How Vungle helps advertisers work better even without AAID

What is Android Advertising ID?

An AAID is a unique 32-digit string of characters that is automatically assigned to each Android device. A specific Android Advertising ID example of “38400000-8cf0-11bd-b23e-10b96e40000d” is used in Google’s Android developer documentation, with real IDs following a similar format. AAIDs were first introduced in the Google Play Services 4.0 update in 2013 to give users more control of their advertising experiences while still providing advertisers an effective means of identifying audiences.

AAID is not the same thing as an Android Device ID, which is a feature meant to uniquely identify devices for technical purposes rather than ads. Android users are permitted to freely reset their AAIDs or delete them entirely from their device settings menu. They’ll still see ads afterward, but those ads will either have a new AAID to work from or none at all, depending on which option the user chose.

What is AAID used for in mobile advertising?

Demand-side platforms and ad networks can use AAID to match Android users with advertisements. AAIDs help third parties track the individual users’ interests throughout the apps they use and the browsing they do, among other factors. Ideally, this is a beneficial arrangement for both advertisers and users: Advertisers serve ads to users who are more likely to engage with them, and users see ads that inform them of products and services they’re interested in.

AAID lets advertisers build databases of customer profiles with the kinds of content and experiences their devices were used to access. These customer data platforms collate info from across just about anything users do on a mobile device. For example, when someone opens a Japanese language learning app from Google Play, Google will send the same device ID out to advertisers when that user begins browsing travel blogs.

With this portfolio of information in place, advertisers know that they’ll be much better off serving Tokyo hotel ads to this particular device than Colorado kayak rentals. No demographic specifics are needed — though a customer data platform will likely track those too when available — as networks can simply match the user and the best ads for them based on these known interests. AAID also aids advertisers with attribution or knowing what particular ads led users to visit pages or make transactions for payment. However, that part of the business is also rapidly changing.

Why is Android changing how apps can access AAID?

Mounting privacy concerns among the public, as well as associated high-profile data leaks, have led more people to feel uncomfortable with the level of tracking information ad providers have access to. On the other hand, Google has been hesitant to make advertisers’ lives more difficult, and it likely isn’t a coincidence that ads accounted for 80% of Google’s total revenues in 2020 according to a financial statement from their parent company.

Recent moves from Apple to increase iOS’ emphasis on user privacy have left Google in the position of playing catch-up with their mobile operating system. Android’s first major change came in the form of a late 2021 Google Play services update which fully restricted apps from seeing the AAID of users who had opted out of personalized ads, even for “essential non ads use-cases such as analytics and fraud prevention.” Those changes only applied to apps running on Android 12, the latest version of the OS, but they will begin to affect all other supported versions of Android beginning in April 2022.

On Wednesday, Google announced that they’re taking Android ad privacy further, introducing plans to build their Privacy Sandbox initiative — which was first introduced for Chrome — on Android. Google said the multi-year initiative aims to build new technologies that satisfy both improving user privacy as well as allowing effective, personalized advertising. While Google works on the initiative, they plan to “support existing ads platform features for at least two years” such as AAID.

Even after Google’s announcement of Privacy Sandbox on Android, the search giant’s changes are still a far cry from Apple’s Limit Ad Tracking (LAT), which requires users to specifically opt in to ad tracking on an app-by-app basis. Early studies indicate Android users are adopting the platform’s ad-limiting features at a much lower rate than on iOS. Regardless, this is unlikely to be the last change Google makes to how it handles Android Advertising IDs as it keeps pace with privacy concerns throughout the tech industry.

How Vungle helps advertisers work better even without AAID

With Google’s AAID and Apple’s Identifier for Advertisers seemingly on an inevitable descent from ubiquity, the mobile ads industry needs new solutions to produce the best possible results. Fortunately, the standard of contextual advertising practices is rapidly rising, and Vungle stands at the fore ready to help you with the transition. GameRefinery by Vungle is a leading contextual ad intelligence platform that targets ad campaigns more effectively through thousands of unique variables and tags competitors can’t access. On top of that, the predictive intelligence of AlgoLift by Vungle produces over 95% accurate LTV predictions, helping you meet and exceed your ROAS goals.

Contact us today to learn more!