The global market for mobile apps is set to reach the $100 billion mark by 2020 as more developers seek ways of monetising their products – but this will only be possible with the help of effective big data analytics.

Prabhjot Singh, co-founder and president of business intelligence service Pyze, told TechCrunch that even though there are millions of entrepreneurs around the world building apps and offering them to the public via Apple's App Store and Android's Google Play, very few of these are financially successful.

Although the world's leading apps can rake in upwards of a million dollars a day, the vast majority have difficulty generating any revenue, with less than 50 per cent of developers making more than $500 a month.

However, this could be changed through effective use of big data analytics. One major reason for the failure of many apps to monetise at the moment is a lack of data and business intelligence that can help developers improve their decision-making and identify better prospects.

But as the technology for evaluating data and turning it into useful information becomes cheaper and more widely available, this presents a great opportunity for smaller app developers to improve their results.

"Companies that can build big data and analytics pipelines to learn about how their apps are being used and who uses them are in the best position to build a community of 'sticky users' who will continually use their apps," said Mr Singh.

He added these players are better able to link into media outlets and social services such as Facebook and LinkedIn to retarget their users and deliver the most relevant, interesting experience. This is something that could not be achieved by the majority of app developers, who may be made up of just one or two people.

Until now, the problem with mobile analytics has been that the solutions that were available did not scale particularly well to provide developers with the type of answers they needed. The tools struggled to effectively analyse millions of data points and then draw out the key information that could give an insight into user behaviour and desires.

Dickey Singh, co-founder and CEO of Pyze, explained that this problem could be solved by using machine learning tools that can automatically cluster groups of users into segments, making it easier to offer more personalised services.

This can enable developers to better monitor usage habits to identify different patterns of app use. 

"From here, an app can begin to develop personalized messages for given users based upon how they use the app," TechCrunch noted. "Nonprofit and for-profit uses of the app can be identified; this enables app developers to more clearly see who is using their apps in a premium, pay-for mode, and where they should be investing their efforts to further monetise their products."

In a study of 12 companies using such tools conducted by Pyze, customer engagement has increased by an average of 35 per cent, while revenue has gone up by 20 per cent.

Prabhjot Singh noted this can help level playing fields between independent designers and large app companies, while also improving rates of engagement for large enterprises that are not primarily in the app business, but that want to use such tools to improve relationships with customers.