Behavioral Profiling in Games: An overview

The game industry has access to detailed data about how players are interacting with games.  The data can come from a variety of channels are often high-dimensional, time-dependent and potentially very large. Profiling users has emerged across multiple data science application areas as a way of managing complex user data, and to discover underlying patterns in the…

Guns and Guardians: Playstyles in Destiny

Given a huge and varied game like Destiny, it is of interest to see if there are any patterns in how people play the game. There can be a variety of reasons for this – for developers the focus can be on monitoring the players and checking no group emerges that has issues progressing, gaining…

Introducing Clustering III: Challenges and Pitfalls

In the previous post of this series we introduced the theoretical foundations of cluster analysis and the various categories of algorithms. In this post we take a specific look at the challenges associated with running a cluster analysis on behavioral telemetry from games. Clustering behavioral data from games does not involve any unique challenges: the…

Introducing Clustering II: Clustering Algorithms

[This post was written in collaboration with Christian Bauckhage and Rafet Sifa.] Clustering is imminently useful for finding patterns in gameplay data. In this second post in the clustering series, we briefly outline several classes of algorithms and discuss the types of contexts they are useful in. Cluster algorithms can be categorized based on how the…

Visualizing Dynamic Behavior Flow

One of the most important challenges in game analytics is to take the power of quantitative analysis and place it into the hands of everyone, not just trained analysts. In this post we describe the process of developing a method for generating behavioral profiles of player, and visualize how they over time migrate between these…