Co-founder & COO at Braavo Capital. We use data, integrations and automation to provide funding for mobile growth.
There are a lot of apps floating around in the world, from pocket dictionaries to payment systems to games that use augmented reality. And while the vast majority of them have nowhere near the reach of the most popular apps, they still have access to a considerable amount of user data. For the most part, app developers have done little with this data except use it to address user complaints or to provide incremental improvements to the user experience. But given the explosive growth of the app market that’s projected over the next three years, app publishers should come up with new ways to use the data they already have to create immersive, personalized user experiences that will keep users in the app for as long as possible. Data should be used to inform decisions and support customer growth efforts, as long as publishers are careful about using a customer’s personal and proprietary data.
At the moment, many app publishers are moving to subscription-based models in order to create a steady revenue stream. But in order to be a successful subscription business, these apps have to be able to maintain their value. This is where many apps fail. Certain types of apps have a stronger potential for success using a subscription model than others. For example, dating, fitness and music apps are likely to have better success using a subscription model than a dictionary or weather app.
A game that uses augmented reality, on the other hand, is a different story. Unlike a mobile dictionary, a mobile game offers an immersive experience for the user that encourages them to spend more time in the app. And the more time they spend in the app, the more information that can be collected on that specific user. This information could be used for real-time level optimization, for instance, changing the difficulty of the level a user is playing depending on user achievements and progress. And considering that mobile games account for a large part of the market revenue for mobile apps, the possibilities are enormous.
There are myriad ways in which apps could use the information they collect in order to improve the user experience. For example, fitness apps could optimize a user’s workout based on their health conditions and any other data that has either been entered by the user or tracked by wearable devices. Or, they could use machine learning to generate customized workouts, as the Optimize Fitness app already does. By using data to tailor workouts to each individual user, these types of apps are better able to prove their worth to the consumer and ensure that they continue to use it. This doesn’t just work with fitness apps: Airbnb’s app offers users guidebooks and activity suggestions that are tailored to their upcoming stays.
Apps could also use data they’ve collected to push relevant content to users, whether it’s an ad for a product they think the user will like or a news story on a topic that the user has expressed interest in before. The Nike+ app is one example of this. In addition to notifying customers of events that might be of interest to them, the app also organizes the in-app shopping experience so that the products most relevant to the individual show up first.