What is mobile ad attribution? An introduction to app tracking
Mobile attribution is how marketers understand the journey a user takes to arrive in their app and what they do once they’ve landed there. Web marketing uses the well-known cookie to track the user journey, but the same is not possible for mobile apps. Instead, mobile apps must use app attribution measurement in place of cookies. With this technology, there’s typically a data point for every action (known as app events) a user takes on their journey, from clicking an ad to making a purchase. When an event is attributed to a channel or campaign, it means that the channel or campaign caused the event.
We’ll take a look at how mobile attribution works from a technical standpoint, diving into how we find those data points and the information they contain. We’ll also delve into why mobile attribution is important, and the challenges marketers face with attribution.
Why is mobile attribution important?
Before we get into the nitty gritty of how it works, it’s important to keep in mind the value of mobile attribution. Your users will come from multiple advertising channels. If you cannot track the how, who, when, and why of their journey to your app, you cannot know which of your networks are delivering users, the relative value of those users, or how much of your marketing budget is going directly toward fake clicks and fake installs.
An app attribution tool gives you a platform to discover where your users come from. For example, if they arrived to your app via a video ad on Facebook or a static ad on the App Store. App attribution tracking lets you determine which are your best-performing marketing campaigns so you can pinpoint the most effective ads and iterate on them. With information from attribution reports, you’re able to optimize your creative assets and use hard data to get rid of failing ads while tweaking the good ones. Greater knowledge about how your ads perform allows you to practice smart retargeting and build segmented ad campaigns. Plus, you can see how a particular user’s journey compares to that of a user from a different user acquisition source.
How does app install attribution work?
To get the most value out of your attribution data, you’ll need to partner with an attribution provider. Working with a mobile app attribution provider like Adjust enables you to make well-informed business decisions in real time. For these reasons, we’ll explain how attribution works through the lens of an Adjust client.
Let’s say that you’re using your iPhone to play a game. A video ad pops up within the game. You watch the video and click the call to action (CTA) at the end of it to download the app. The link takes you to the app’s page in the App Store, but briefly redirects you through Adjust. This takes a fraction of a second but is a key step; it’s how the attribution provider receives the first data point – the user interacting with the ad.
By clicking the link, going to the app store, downloading the app, and opening it for the first time (referred to by Adjust as the install), the attribution provider will receive the following data points:
- Device ID: A string of numbers and letters that identifies every individual smartphone or tablet in the world
- IP address: A specific address that devices use to communicate with one another via the internet
- User agent: A line of text that identifies a user’s browser and operating system
- Timestamp: The time the user clicked on the link
- First install: When the app was first opened
With this information, the attribution provider can determine whether the user is new or existing. If the user is new, the attribution provider will attempt to match the user’s install to their engagement on a particular ad. This exchange of information can happen in several ways, but the most common is for the app to integrate the attribution provider’s SDK.
A software development kit (SDK) allows apps to communicate with Adjust’s servers. App developers integrate the SDK into their app’s code, much like if they had a car and a manufacturer gave them a new part for a bit of an upgrade. This creates a line of communication between the app and Adjust, through which we can provide attribution data in real-time.
Adjust’s SDK is open-source. It is freely available, transparent code that app developers can edit, modify, or improve to meet their app’s needs. For more information, take a look at our SDK on Github.
App install attribution with windows and waterfalls
Once a user’s install has been confirmed, an attribution provider begins to look at the user’s other previous ad engagements and attempts to make a match. This match is the attribution. However, Adjust won't look at every past engagement–only the ones that fall within the attribution window.
An attribution window is the period of time in which a publisher can claim that a click or a view led to an install. Attribution windows are an essential tool for helping advertisers and publishers understand when a conversion takes place. Often there’s a gap between the exposure to an advertisement and the install. During this gap a number of engagements with ads can take place, making the matching process critical for accurate attribution. In this case, the process is known as multi-touch attribution.
Adjust works backwards, looking for the data point within the attribution window with the most robust information, before heading down the attribution waterfall to confirm a match. The waterfall looks like this:
- Device ID match: First, we look to see if we have any past clicks matching the same advertising ID. On iOS, the advertising ID is called an identifier for advertisers (IDFA). The Android equivalent is called an Android Advertising (AAID).
- Android referrer: For Android phones, we’ll also check for a match via Play Store referrer, which will contain a unique value our backend assigns to a specific click. These IDs are not volatile and are as accurate as advertising ID matches.
- Click fingerprint match: If the above data is unavailable, we will look to see if we have any past click engagements that came through with the same IP address. We will then create a scorecard for each click, taking into account information such as the type of device, device name, operating system and version, and language. The click that has the most common parameters with the install information will get the attribution. This can be tricky as IP addresses can be dynamic and change rapidly, especially if the user is on the go. So for these types of data points we use a much shorter attribution window.
- Impression device match: If the above data is unavailable, we will look to see if we have any past impressions that came through the same advertising ID.
- Impression with fingerprinting: If the above data is unavailable, we will check for past impressions that have the same IP address as the install’s IP address. When we find a match we create a scorecard taking into account the device type and name, operating system and version, and language. The impression with the most parameters in common with the install information will get the attribution.
- No match: If Adjust goes through all of the above checks and has not found a single match, the user is attributed as organic.
For example, a user sees an ad for a game on Facebook while commuting to work in the morning, seemingly forgets about it, but then sees the ad again later in the week on Instagram and clicks on the CTA. They again do not make an install, until they remember to download the app on the way home from work in the evening. They play the game on their journey home.
In this example, the click engagement would be matched to the install, making Instagram the attributed channel. Meanwhile, Facebook may be considered an assisted conversion.
Of course, iOS 14.5+ has hugely changed how attribution works on iOS. With user consent to access the IDFA via the App Tracking Transparency (ATT) opt-in, attribution can be carried out in the same way as before the iOS 14.5 rollout. Otherwise, marketers must work with SKAdNetwork (SKAN) to attribute and measure non-consented users. We cover these differences and how to work with SKAN and its conversion values in detail in our guide, iOS 14.5+: From day one until now.
What can you learn from attribution reports?
Once this process has been completed by the attribution provider, the app marketer or developer will be able to view this data in an attribution report. Depending on your app’s needs you can choose to work with aggregated reports or raw data reports. Attribution reports will show you:
- The journey users took to install your app within the attribution window
- What actions the user took after installing your app
Adjust’s attribution solution provides a single, streamlined dashboard you can utilize for in-depth analysis without having to collate or wrangle data from your media partners. Adjust then goes beyond attribution reports, giving you the power of verified purchases and fraud protection to make sure your data stays clean and reliable.
Why is mobile attribution challenging?
Despite its many benefits, it’s important to acknowledge that there are real challenges with mobile attribution. A lack of industry-wide standards (rules for dropping data points), competing mobile app attribution models (disagreements about which data points count), user journeys that touch multiple platforms, and the issue of widespread fraud all complicate the process of app attribution tracking. That’s why Adjust is here to simplify the process and walk through your marketing journey as a partner in measurement.
Those are the basics of how Adjust goes about attributing data points. Now you know how essential it is to incorporate an attribution provider that follows the user from first engagement to their very last in-app purchase, as well as what kind of data you can gather from attribution reports. Learn more about mobile attribution with Adjust, and Adjust’s all-in-one data hub, Datascape.
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