Player Segment Analysis

Define Your Player Segments Using Empirical Data

Your game audience isn’t one homogeneous group. Identify the distinct personas underlying an audience to target them with specific game features and messaging. We apply cluster analysis on our large gamer data set to identify distinct player segments (and their frequency) within specific game titles, franchises, genres, or demographic groups.

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Frequently Asked Questions

Nick Yee and Nic Ducheneaut have over 40 peer-reviewed papers on gaming and virtual worlds. Our research on online gaming motivations research has been cited over 1,600 times. Our current Gamer Motivation Model was developed via factor analysis of survey data from more than 239,000 gamers.

We created a Gamer Motivation Profile where gamers could complete a 5-minute survey, get their personalized motivation profile, and share it online. About 80% of our traffic came from social media sharing.

Over 239,205 gamers have taken the Gamer Motivation Profile.

Usually between 3-8 segments emerge.
After executing the service agreement and statement of work, we can deliver the report within 5 business days.
  • An executive summary slide of all the player segments.
  • A descriptive sketch of each segment.
  • The demographic profile of each segment (including gender percentages, median age, casual/core/hardcore gamer type, and number of days per week with at least 30 minutes of gaming).
  • The motivation profile of each segment (i.e., percentile ranks on each of the 12 motivations in our model).
  • A ranked list of the games that are disproportionately popular in each segment.
  • Explore a sample report.
In our own research and work across multiple contexts and applied on either psychometric data or server-side log data, we’ve consistently found Archetype Analysis to out-perform density-based and centroid-based clustering (e.g., k-means). This is our preferred clustering method.
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