Predictive analytics company Playnomics has announced the release of its new Churn Predictor, which aims to help developers more accurately predict the lifetime value (LTV) of their users. In doing so, developers are given a chance to market campaigns specifically to users that are most likely to stop playing, all in an effort to get them to stick around.
According to Playnomics, 70 percent of players of free-to-play games stop playing within the first 30 days. On the other hand, players who are brought back into a game within the first two days of downloading it play for 334 percent more overall. The longer a player plays, the more opportunity there is for the developer to turn them from a free player to a paying one.
By utilizing the Churn Predictor, developers will be able to predict when players are most likely to leave the app. The program offers a predictive score for each player’s likelihood of leaving the game and even the average number of days each player is expected to come back and play. If a large group of players is predicted to stop playing the game, developers can instantly target that group with a user engagement strategy to get them to keep coming back.
“Data and segmentation are changing the free-to-play gaming market, yet many developers aren’t leveraging data to understand and engage their players most effectively,” said Chethan Ramachandran, CEO of Playnomics, via a company release.
“This is why we provide our analytics suite for free, our aim is to democratize the access to the information and focus on taking action. By uncovering predictive churn for mobile games, our data science team is leading the industry to enable developers to maximize player engagement and lifetime value.”
All developers currently using Playnomics’ PlayRM platform now have access to the Churn Predictor’s features at no cost. The PlayRM system offers data on the gaming behaviors of over 200 million player profiles and helps developers monetize their users through targeted advertising campaigns.
Developers interested in learning more about PlayRM or the Churn Predictor are encouraged to visit Playnomics’ website.