At Playnomics, we have a simple mission: to enable 1-1 targeting of players for connected games. We make this happen through the use of predictive data mining, which allows us to dynamically profile players and predict player value across games.
We started Playnomics in 2009 because we saw a fundamental shift in how games were developed, published, and iterated. Games are now connected, persistent, and played anywhere on multiple platforms. Every interaction between the publisher and the player is an opportunity for publishers to have players do more, interact more with the game, and ultimately spend more.
Our belief is that if publishers can understand player value and quantify player behavior, publishers can acquire the right type of player for their games and then retain and monetize them better. Doing this with millions of players in real-time is not easy, and the answer lies in data. We are pioneering the application of predictive data mining to games on a massive scale. By processing terabytes of in-game player actions, and applying cutting edge machine learning algorithms to that data we can dynamically create profiles of each player, and then target that player in a personalized way. This technology has been applied in a other industries like finance, information security, and e-commerce, and we are the pioneers of applying it to games.
