3 Ways to Use Player Behavior Analytics to Increase Game Revenue

The ever increasing popularity of the freemium model in mobile gaming has created substantial demand for data analytics services in gaming. Many small development teams do not have the resources to hire a team of trained data scientists, yet the need for analytics is too great to ignore. According to VentureBeat, the global gaming market is expected to reach $218.7 billion in 2024. The collection and interpretation of player data is fundamental to understanding which users can be monetized,  identifying the underlying issues causing player churn, segmenting players into actionable groups and communicating KPI’s to stakeholders and investors.

Game makers often put in thousands of development hours before their games reach the masses. As seasoned developers know, this is usually only half of the battle. A large number of active users does not always translate to a higher ARPDAU (average revenue per daily active users). The ever popular freemium model encourages many mobile developers to offer a product for free now in exchange for potential future monetization of that product. Fortunately, the barriers to monetization can be significantly reduced with proper analytics. 

With segmentation and appropriate targeting, players can be grouped into tiers and marketing campaigns created based upon that segmentation. Thus, the players with the highest likelihood of converting to paying users can be more aggressively targeted. Furthermore, issues in the game that get players stuck and increase churn can be resolved or even turned into opportunities to monetize would be lost users.

Reducing Player Churn

Player retention is one of the key factors that investors and publishers alike are eager to explore. A small to medium size gaming company can be heavily rewarded for an aptitude to digest, improve upon and communicate this metric. As previously mentioned, the use of analytics to identify and reduce “sticky points” in the game is often the first place an astute developer will look to improve upon player retention.


Segmenting Players

With a monetization target in mind, game developers will look to carve out data driven segments of their active user base. This data will fuel marketing campaigns, user experience development, product development and product life cycle decisions. A segment of users may be more likely to get stuck in certain parts of the game, understanding which part of the user experience creates this obstacle can allow developers to retain and monetize users the otherwise would likely churn.

Key characteristics will define a group of users with the highest ARPDAU.  Marketing teams will not only target these users more aggressively with offers, but also look to attract more look-alike users with promotional materials.

Communicating With Data

While the use cases for analytics may vary widely between small and large game developers, the notion that professionalism can be communicated with that data holds as a constant across the board. Whether communicating KPI’s to stakeholders within the organization, or potential outside investors, an understanding of key metrics and the analytics that support them is critical. An investor in search of a solid ROI will want to see player retention and ARPDAU.

Teams within the same organization may disagree on where to allocate resources, and often a failed release will show evidence of misallocation. A unified team with a set of core metrics and data driven evidence to back them can focus resources on the most meaningful areas of development to ensure a higher likelihood of a successful initial release.