Promotion without analytics is like driving with eyes shut. Will you go far? The same is with mobile apps. Even an experienced marketing specialist shouldn’t rely on professional intuition. Today we’ll speak about some aspects of mobile analytics, traffic tracking while promoting apps, to be exact.
It’s important to conduct analytics of all the necessary metrics while promoting a mobile app. A marketing specialist should know the result of all the actions made during an advertising campaign. That’s the only way you can make right decisions.
Analytics tasks may be divided into 2 types: user behavior before and after app installation. In the first case, it’s important for a marketing specialist to know where does traffic come from, which sources are the most efficient, and so on. In the second case — how do users interact with an app.
There are special systems of install tracking for solving tasks of the first type. Systems of user behavior analysis will help with the tasks of the second type. There’s a simple example of how useful they are. Let’s assume that you use several traffic sources at once, both of them give the same conversion coefficient. But users from the first one use your app more actively and make more purchases. It’s evident that this platform is more beneficial and it’s better to switch to it.
It’s important for a marketing specialist to know a user way from a click on a banner to app installation. But here’s a big difficulty: it’s easy to track a click on the web but all the connection with a user is lost while transfer to a store as there are no such means there.
There’s a way out: building in of SDK into an app. It helps to “see” a click on the web and compare it to installation from an app. But it’s not that easy: if you work on this scheme, you’ll have to build in SDK of all the advertising networks you get traffic from.
That’s why there’s an advanced decision — special tracking systems. They work like this: redirection of a system is launched after a click which helps to get information about it. A user “fingerprint” is created on this stage. It’s a combination of different technical data about a device. Further on, an installation is marked from the app. And the comparison of the click and an install happens by this fingerprint.
Everything could be ideal but, unfortunately, the majority of trackers lack data (browser version, IP, device type, platform, etc) for a more precise click comparison.
Besides it often happens that a user downloads an app from one IP and launches it on another one. The connection between a click and an installation is lost in this case. There are other technical problems that decrease the accuracy of a tracker. As a result, the average level of mistakes increases to 25%.
The time of a click is another parameter that should add to a user virtual profile (fingerprint). I.e. tracking systems gives a temporary identifier to a user at the time of making a click. Then, a match of an image is checked during an app launch and a link of a click to installation is made. But if a user has installed or deleted other apps on his/her device between a click and an app launch, the system loses data about the necessary install. An average level of mistakes with a temporary identifier is 25% as well.
Trackers with advertisements on Facebook work by a similar scheme. The level of mistakes is only 5% there as a user’s social profile is used as a fingerprint. Besides, there’s a possibility to form reports on tracking on Facebook.
If a tracker you use is a partner of the social network, installs are calculated quite correctly, as Facebook itself forms the reports. If a network isn’t a Facebook partner, a level of mistakes may increase significantly. For example, if a user clicks on Google banner but makes an installation from Facebook, the tracker will count it to Google.
There are many systems on the market but each of them has both pros and cons. We’ll tell you about the most popular ones.
Tracking systems is an obligatory step for mobile analytics. They help to track user history from a click to the launch of an app. Statistics that you get while analyzing traffic sources, allows building an advertising campaign wisely, and significantly decrease your budget.