Mobile app attribution tracking overview
Mobile app attribution tracking is the process of attributing successful app events including downloads, purchases, sign-ups, and more back to the marketing efforts that drove them, such as digital ads. Unlike web attribution, where there are clear standards, mobile app attribution lacks conventions and can be exceedingly difficult without the right tools.
Why is mobile app attribution vital?
Today, app marketing is all about results. Marketers and product designers must show that their ad campaigns and feature tweaks have a positive impact on revenue. Yet without insights into how their actions impact, persuade, and drive users, these teams can’t demonstrate that connection.
With mobile app attribution, product teams get direct feedback. This reporting allows them to tweak, test, and optimize everything from onboarding sequences down to button colors and menu placement. It helps them build products people love.
To attribute their marketing, app creators must know:
- The external events that led to in-app actions (Ad clicks, reviews, social shares, etc.)
- The behavior of users within the app (Downloads, purchases, etc.)
This requires product teams to collect detailed, user-level data from three sources:
- Referring sources (Advertisements, web pages, other apps)
- App stores (PLAY, iTunes, Amazon AppStore)
- The app itself
User journeys, however, are circuitous and difficult to track. Few, if any, follow a predetermined ‘golden path’ to conversion. Some users who are referred to an app store don’t download the app. Some may go to the app store for another reason and suddenly convert on a search result. Some may go directly from ad to purchase while others will go dark and then mysteriously purchase one year later.
Collecting all this data can be challenging and making sense of it even more so.
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Why is mobile attribution so difficult?
The mobile app ecosystem is highly fractured and doesn’t make things easy for product teams. App creators often have data streaming in from many operating systems, devices, app stores, advertising platforms, and various versions of their app, with users moving erratically between them. Matching all this data can be challenging, especially when different platforms have different tracking conventions and taxonomies.
And unlike web attribution, with which most product teams and marketers are familiar, mobile attribution has no industry accepted standards. On the web, advertising networks and brands have long leveraged a combination of:
- Custom URLs: Tracking the origin of each visitor by appending data to the end of the URL.
- Pixel tags: Prompting users’ browsers to download a pixel upon ad-click and another upon event completion to match the two.
- Cookies: Depositing snippets of code onto users’ browsers to track behavior.
Yet all the methods above rely on a web browser. They don’t work on mobile where the most critical part of the user journey – the decision stage – takes place within app stores such as PLAY for Android and iTunes for iOS. These app stores may allow users to explore apps and see ads just like a browser, but unlike the web, they aren’t open to developers. Each mobile app store operator can choose whether to share user information with brands. Some do and some do not.
Android does. Advertisers on PLAY can pull user data through SDKs and can easily access referrer URL parameters for download links in the PLAY store. That is, advertisers get feedback on what led app store visitors to download the app. App creators can sync this information to analytics platforms for attribution.
Apple, on the other hand, does not expose information to brands. The iTunes app store is effectively an attribution black box. There are workarounds to help with this, such as rerouting traffic to additional pages before and after the app store, but they are complex and difficult to maintain.
To attribute ads, app creators must take what data they can glean from app stores and combine it with data from referring sources and their app itself. For teams who lack product analytics, this can involve manually matching data in excel spreadsheets at the end of the month, which is time-consuming and prone to error. Luckily, analytics platforms exist to make this easier.
Mobile operating system market share
While iOS makes up almost half of the U.S. smartphone market, Android dominates internationally. – Statista
For easy attribution, use product analytics
Product analytics can help product teams consolidate their data to analyze it all in one place. These platforms integrate into all the most common data sources such as advertising platforms, websites, apps, and app stores to:
- Consolidate platforms
- Automate the tracking process
- Resolve cross-platform inconsistencies
- Optimize marketing and advertising
With a product analytics platform, marketers and product people can view complete user journeys from beginning to end, from ad-click to in-app purchase. It pulls data from the PLAY store, automates tracking around the iTunes store, and marries this with detailed, user-level data from within the app itself.
With product analytics, product teams can answer questions like:
- Which sources produce the most valuable users?
- What referring sources have the greatest ROI?
- Which ads are most successful?
- Which ad variants are best for which personas?
- Which campaigns led to users with the highest lifetime value (LTV)?
From there, product teams can optimize their marketing activities to align them with long-term mobile app success.
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