Interpret Gaming Data
One of many things I am liking about Gamestar Mechanic is that it gives you various pieces of data around the games that you create and publish within its community. The other day, I created my first multi-level game — Deep Drop Dream – and over the last three days, a few players have given it a try. As a Premium member, I have access to various stats (see above) which indicate to me not only how many people have played it, but also, whether they were able to finish the game or if there was a level that was abandoned consistently.
Why is this important?
If a game is too hard, then the player gets frustrated. If it is too easy, they get bored. The key to game development is to find that middle ground where there is challenge for the player but no insurmountable challenge. They have to be able to succeed, although it may mean they have to work at it. This data chart shows where those kinks in the game might be, and for the developer, you don’t always get that sense. It’s like writing a novel — sure, it reads great to me, the writer, but an impartial reader can give valuable critical advice for places where the story doesn’t work.
Here, I notice that 15 players started the game but only four finished. A few dropped out at different levels, and according to the guidelines, the funnel’s data shape is fine. It’s OK to lose some players. But if everyone is gone — if the funnel has a sharp tip at the end because no one made it there — then you know you have trouble and need to revamp the game. If the funnel is a vertical rectangle, meaning every player won every time, then the game is too easy.
This is a great analysis tool for kids, don’t you think?