When your soft launch data is clear and you have a high degree of confidence in it, things are easy. But there are many factors that can make it difficult to have a clear reading of the performance of your game. This post discusses ways to deal with fuzzy soft launch data.
Even though there is an intention behind every feature you design, once it’s live on the store users will reappropriate your game and play it the way they like. Sometimes that means users won’t play the game you want them to play it. Having a user-centric, game-as-service approach means your goal should not be to make users play your game a certain way. Rather, you should leverage data to identify your users’ preferences, and find ways to help them engage with your game on their own terms as much as possible.
Engagement is key to develop a game that will be successful in the market. But engagement alone is not enough to build a successful title. Looking at how spending and engagement go hand in hand can help highlight some key dynamics of mobile monetization, and rethink what the most effective monetization strategy might look like.
This week I suggest ways to leverage data to get better insights into what is driving your user behavior. In order to build the best games, you need to understand what your users’ motivations are. A hypothesis-driven use of data is the way to go for that.
Ben Reiter’s book on the Houston Astros depicts the culture of data that helped win the 2017 World Series. The Astros are a great example of an organization that knew when to rely on data, and when (and why) to trust their gut. “Astroball” is a great book that provides some interesting insights for baseball fans – and also for anyone wrestling with how and when to use data in their decision process.
Game as service is not just about adding content. It’s about serving the needs of users. And that has implications for the way you design and monetize your game.