This sponsored post is produced by Personagraph. 

Being relatively young within the digital landscape, analytics for mobile apps have come a long way in a short time. Developers and marketers can describe exactly how users use the app and the steps taken towards generating revenue. However, when it comes to learning more about their mobile users, particularly those who don’t use Facebook, developers rely on guesswork, surveys, and trial and error.

A half-blind approach towards user understanding is extremely costly. Studies show that 50% of downloaded apps are used no more than 5 times, and that 80% of apps in the App and Play stores are zombies. App advertising dollars are spent to generate as many downloads as possible, but often these pushes are not targeted towards individuals who are likely to become loyal users.

For example, advertising efforts are wasted on metrics such as number of downloads, because we know that so many people behind the downloads end up deleting the app after launching it only a handful of times. This translates to horrible retention rates, and as a result, it is easy to see why 64% of Android developers and 50% of their iOS counterparts are below the app poverty line, meaning that they make less than $500 per month.

The trick is to learn something about your most valuable users, so that you can focus your resources acquiring more users like them. So for example, instead of blindly acquiring users, why learn the characteristics of your most satisfied or most valuable users, and then focus your resources to acquire more users like them.  The benefits of acquiring users like them trickle up to improving downloads and retention.  Similar techniques can also help with engagement and monetization.

Easy, right?  There is a wrinkle, though: user understanding in mobile is particularly difficult as the relatively nascent mobile ecosystem is still a Wild West, similar to the desktop software industry around 10-15 years ago. Without more information, mobile users are seen as homogeneous, and treated as such.  The most established mobile tools, such as Flurry (Yahoo) and Google Analytics are really good at telling you how users are using mobile apps — which versions, operating systems, how long a user engages with them, which buttons are being pressed — but do give you little understanding into the wants and needs of the people using your mobile apps.

But how can you improve your app processes if you don’t have the tools to know your most valuable users? New mobile analytics companies are trying to fill this gap. Personagraph is a user insights platform for mobile that allows developers to understand their audience in ways not possible with traditional analytics tools.  By using machine learning against a number of contextual and device signals, it creates robust user profiles that contain much of the information about users that mobile app developers miss today: demographics, interests, descriptive analytics such as popular locations and popular app categories, and competitive analyses that provide what competitive apps are used and how often users access them.

As the mobile app industry matures, competitive advantage is no longer a matter of who can build the best app but rather who can market it best. Luckily, the mobile analytics space is maturing as well and is supporting developers in their quest to reach valuable users.

Irfan Mohammed is a co-founder of Personagraph, a user insights platform for mobile apps. Personagraph tells app makers who users are, what they do outside the app and how they interact with other apps.

Follow Personagraph on Twitter at @personagraph.

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