Blog Understanding and analyzing the effects of deeplinking

Understanding and analyzing the effects of deeplinking

Over the last two weeks, we’ve discussed how to implement deep link magic in your app - how to best redirect users right into your app, instead of the App Store, and how the finer points of these mechanisms help you bring the most value to your users.

An important part of understanding how you are improving your app will always be proper measurement. So given that you’ve implemented your deep link backup plan, and deferring them until after the install, how can we analyze user behavior after having been treated this way?

When you reach out to a user and send them over a deep link, this constitues a distinct event, and you’ll want to look at their behaviour as a group after that event has happened. Let’s regard this as a “re-engagement”, and segment users out who were re-engaged in this way a a certain time.

We’ll want to record the new “re-engagement”, stating which deep link they came over, what sort of creatives we used to drive them to the deep link, what time and so on. In effect, we’ll be attributing their new activity to this re-engagement effort - what’s called a “reattribution”. When you’ve reattributed a user onto a re-engagement campaign, you can sum up the activities of all activity that is attributed as such, and compare that to your baseline.


Having done this, we can associate each re-engagement technique with specific results down the line - increased purchases, higher engagement, or whatever other goals you may be pursuing.

In order to be able to analyze the effects that a re-engagement has on users in aggregate, it’s best to regard the re-engagement as an attribute of the user, and not as a distinct event in the past. Usually, we may store older attributions as distinct events, but remember the latest attribution. Once you’ve recorded this as an attribute, you’re good to do any analysis further on.

What we do in the adjust SDK is that we take a look at whether a user either has been sent over a deep link - by flagging the methods that handle the deep link - and send a message to our servers that records that particular event. This is automatic in our open-source SDK, but you can also implement this as a user attribute in a tool like Mixpanel (or let us send that data to Mixpanel.)

Want to get real neat? Then record exactly how the user arrived into your app. By recording whether or not the deep link was triggered when the user entered the app - whether it was deferred or not. Knowing the proportion of re-engaged users that come over the deep link gives you a serious hint whether you are managing to stay on the device or not. While we won’t know the exact number (for the lack of total population proportion and respective conversion rates), optimizing on the ratio between users who had to re-download and users who could just hop back into your app can be a great boon.

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