Mobile gaming gives people shared experiences, plus, these games happen in a virtual world and every aspect of the game is measurable. So, Big Data and gaming go well together. Big Data along with AI-powered analytics can help measure certain key KPIs that are essential for understanding the performance of the mobile game. Some of these KPIs include a number of active users, where they come from, the number of new sign-ups, daily Active users, monthly active users, and customer lifetime value, etc. Event-based analytics can also be set to reveal opportunities by showing more about what users are doing on an app. The ability to gather data and the ability to analyze it creates new opportunities in the Mobile Gaming industry.
So, what can analytics do?
Analyzing millions of hours of data can provide greater insights into which parts of the games are popular and companies can use this information to increase user interaction. Through analytics, companies can also analyze when exactly the users abandon the game and strategize for improvements. Analytics can also be used to identify bottlenecks and issues within the game. Further, if there were any major changes like moving from a free version to a paid version of the game, analytics can provide insights into customer engagement and behavior.
Data and AI powered analytics
Data by itself is of no value, unless it is converted into actionable intelligence via analytics. Especially in the gaming world where millions of interactions happen at any given time, any anomaly can have a huge impact. AI-powered analytics can discover issues in real-time and alerts can be sent out – enabling the teams to take quick decisions to fix things. These kinds of analytics can provide unique insights and the teams can quickly review critical metrics by breaking down crashes by specific areas like the app, the platform, and the engineering team can deploy appropriate fixes before they impact the business in terms of downtime and in turn money.
Companies no longer have to depend on reactive solutions like relying on crash reports, customer support case details or wait until a further disaster occurs. AI could give you enough insights to work on – more effectively and more efficiently.