Mobiquity recently contributed to research titled, “Modelling and Predicting User Engagement in Mobile Applications,” in the Data Science Journal, a publication that offers scientific data, covering everything from data creation, mining, discovery, curation, modeling, processing, and management to analysis, prediction, visualization, user interaction, communication, sharing, and re-use.
We know there is no denying that today’s mobile application landscape is growing at an unbelievable pace, creating an extremely crowded market and fierce competition among app developers. And we also know that keeping users engaged is essential – but it’s not easy. With so many reasons for app failure, such as lack of personalization, inability to integrate with other apps or technologies, and competing apps, it’s difficult to stand out and maintain success.
In collaboration with IBM and the Department of Computer Science at Vrije Universiteit Amsterdam, Mobiquity helped to conduct research that proves it can be easy to predict when mobile app users are disengaged by gathering data detailing user interactions with the app. And we can use this data throughout the lifespan of an app to ensure its success by applying these predictions to support updates, new features, and better user experiences.
So what’s the secret equation for successful user engagement?
The leaders from Mobiquity, IBM, and Vrije Universiteit Amsterdam conducted a study to uncover the right factors to make predictions not only possible, but easy and effortless.
In this research paper, the team proposes, applies, and evaluates a framework to model and predict user engagement in mobile applications via different numerical models. The proposed framework is empirically validated by means of a year-long observational dataset collected from a real deployment of a waste recycling app.
Results revealed that user engagement predictability can be done. Ready to see the research with your own eyes? Click here to learn more.
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