This blog was posted on IDGConnectMay 31 2016on
The following is a contributed article by Prabhjot Singh, co-founder and president of a new mobile business intelligence startup Pyze.
Mobile app experts predict revenue from in-app purchases and advertising to exceed $99 billion by 2019. And yet, the large majority of app publishers today make less than $500 a month. The top grossing apps earn millions of dollars per day, while the rest make next to nothing in comparison. Much like the US economy, the mobile app world has its own wealth gap. The root cause of this disparity lies in the failure of mobile analytics technology to keep up with the rapidly maturing mobile app market.
Unsurprisingly, the few big players dominating the app stores are the ones with the deep pockets required to collect, process and utilize data at an extremely sophisticated level. They have the resources to collect massive amounts of user behaviour data, and hire the best talent to analyze and create targeted action plans around it. Product managers working at one of the biggest mobile gaming companies spend an average of three hours every day just analysing the data, and usually with the help of a data scientist.
For the overwhelming majority of smaller app publishers, this approach is not a viable option. The mobile analytics tools available at their price point can indicate where users are clicking in the app, but they don’t provide nearly enough insight into who the users are or how to best engage with them. This begs the question: where’s the real business value in a technology inaccessible to the majority of those it’s supposed to benefit?
The death of mobile analytics is inevitable. The technology as we know it has reached the end of its rope, for three main reasons:
1. Inability to Scale
Traditional analytics tools are based on segmentation and require data analysts to manually define the segments of users they wish to analyse before they can run reports on metrics such as app installs, retention, engagement and so on.
By today’s standards, successful apps are those that attract literally millions of users. As an app’s user base reaches even just the hundreds of thousands range, it becomes impossible to define all the segments of interest – let alone analyse them.
2. Much Pain for Little Gain
Mobile analytics requires a lot of effort and know-how to actually get anything out of it. Every data point collected requires manual instrumentation, a very labour-intensive and tedious process.
There are some mobile analytics solutions out there that provide back-end access to data, allowing publishers to bypass this process, but these cost thousands of dollars a month for a pretty measly advantage over free solutions. And for marketing capabilities – like push notifications or in-app messaging – they charge double. For the app publishers making less than $500 a month… yeah, not happening.
Even if you surpass the hurdle of analysing the data, it’s just as difficult to glean actionable insights from it. Manual segmentation involves a lot of grunt work for app publishers to address even the most basic questions, like which users are at risk of attrition, which are under-monetised or which actions best predict buying behaviour. Answering these questions generally requires offline analysis. And this is just for one user segment – implementing a strategy for engaging with different sets of users is next to impossible.
The Way Forward
The blistering pace at which the mobile app market continues to grow and change has made conventional mobile analytics irrelevant, to the detriment of most app publishers. Who knows what amazing app may never see the light of day simply because a smaller publisher didn’t have access to the necessary analytics tools? Ultimately, this stifles innovation and hurts the entire industry.
App publishers need solutions that allow them to model user behaviour in real-time, develop custom engagement plans and automatically execute on them, at a price that’s affordable for two guys operating out of a garage. The ability to strategically target millions of users based on each one’s individual behaviour will drive a level of growth that the dominant app publishers will have no choice but to reckon with.
With these solutions beginning to emerge, the mobile app wealth gap’s days are numbered.