Mobile attribution is the science of matching two data points, such as attributing ad spend to user engagement or installs based on certain variables. Attribution creates an understanding of what happens when a user interacts with a mobile ad.
Successful mobile app attribution covers the entirety of the conversion funnel. It identifies and reports whether a user reacts upon seeing an advertisement, whether a user installs an app after seeing an ad, and how a user behaves after installing the app. While mobile app tracking helps advertisers and marketers understand individual users, it can also help marketers identify relevant cohorts, identify groups that do (or don’t) respond to creatives, and determine how they behave in-app by tracking key events.
Attribution figures out the number of ad dollars spent on the number of conversions gained, and is important to determining the success of advertising campaigns. Without accurate attribution, advertisers, partners and app developers wouldn’t know how much has been spent per ad, and how much a successful conversion pays out.
Furthermore, mobile app attribution is essential for optimization of all kinds. By tracking user events, and understanding how users behave when faced with paid activity, you can change and improve almost every aspect of your app, your creatives, and your ad spend.
Attribution affects the entire mobile ad ecosystem, from determining how much ad space costs to how well a campaign has performed – another reason attribution is a fundamental component of mobile marketing.
Temporary attribution is a time-sensitive model used to give UA managers flexibility with how their data is presented. It can also be useful for implementing tests and campaign management.
To understand how this differs from regular attribution models, let’s take a look at an example:
You have a gaming app and want to run a campaign with a limited time offer. You also want to see how a new network, Network B, can drive in-app events within one week post-reattribution. But when the week is over, you also want to stop crediting Network B with future in-app events.
If you use a temporary attribution model, any attribution to Network B would move back to the previous source of attribution once that week is over. The network would still be paid for those reattributions, but the reattributed users’ ensuing session and event data would be reflected under the previous source, whether it be organic or another network source.
For this reason, temporary attribution can be useful for measuring the success of engagement and retargeting campaigns.
Attribution is central to everything Adjust does. We have developed an attribution system that is easy to integrate and set-up, so marketers can easily get started with mobile measurement. To find out more about how to configure Adjust’s attribution settings, take a look at our official documentation.
By working with Adjust, you can understand media performance across multiple channels. Adjust clients can track their marketing channels and aggregate conversion data for in-depth analysis – whether that’s via click or impression. You'll always know which ads delivered which users, along with useful contextual information such as which campaign creatives those users saw. Your incoming users are tracked and accurately sourced in real time.
Because Adjust has a fully dynamic partner setup, you don’t have to worry about partner-specific URLs and bulky network SDKs. This means you can add your campaigns directly into your dashboard and immediately begin tracking results across your networks. To learn more about the many partners we’re already working with, take a look at our full list of technology partners.
If you’d like to learn more about mobile app attribution, take a look at our beginner’s guide to the term, here. We also have a more in-depth look at attribution in this report, detailing everything from the challenges making mobile attribution more complicated than web attribution, to how attribution providers verify the user journey from first engagement to lifetime value (LTV).