Segmenting Gamers Through Clustering Gameplay Behaviors...Huge number of gameplay records (yy...

Segmenting Gamers

Through Clustering Gameplay Behaviors

Peter Liu & Laura Higgins

Sony PlayStation & JMP/SAS

Outline

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● Business background

● Segmenting gamers

Source data

Processes, tools, and methods

Business application

● Takeaways

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Serious gaming is a

BIG bu$ine$$.

PlayStation was at a critical moment…

● Behind the market leader

High hurdle to jump

● An opportunity to regain #1 position

Once in a decade

● The future was on the line

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A Resounding Successful Launch

● Gamers cherished PS4

1 Million PS4 sold on the 1st Day

#1 top-selling US next-gen console

● Regained #1 Market Leadership

#1 next-gen market share

Overall market share jumped

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The biggest launch ever in the history of game consoles.

“The beast has arrived! PS4 time”

Drivers behind PS4 Launch

Insights of/from Gamers

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Consoles for Gamers – Focus on gamers

Targeted Marketing – Core PS gamers

Effective Pricing

Listened to Gamers

Mining gameplay Followed Gamers

Segment Gamers

● Source Data

● Processes, tools, and methods

● Business applications

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Listened to Gamers

Followed Gamers

Mining gameplay

Source Data

● Large number of PS gamers (xx millions)

● Huge number of gameplay records (yy billions)

Game title, genre, party type, Downloadable Contents (DLCs)

Device platform (PS3, PSVita, etc.)

Media types (disc games, digital games, videos)

Gameplay history (# of plays, play minutes, first play, last play, etc.)

● Transactions

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Processes, Tools, and Methods

● Data preparation, explorations, transformations, etc.

● JMP Pro, SAS, SQL

● PCA/Clusters

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Business Applications

● Marketing DLCs for A Disc Game

● Forecasting New Disc Game

● Predicting PS4 Purchasers

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Business Applications

● Marketing DLCs for A Disc Game

● Forecasting New Disc Game

● Predicting PS4 Purchasers

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Marketing DLCs for A Disc Game

● Gamers love disc games

● DLCs – DownLoad Contents (digital)

New weapons, missions, characters, games

Other add-ons downloaded online

● DLCs enrich and extend gaming experiences

● Segment gamers

Who are most likely to buy DLCs?

How many DLCs can be sold?

How shall we approach gamers?

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DLCs for Disc Game (cont’d)

Clustering gamers by gameplay

● Data Set

A random sample of 59k (5%)

25 variables

● Analysis process

Distribution analysis

Multivariate analysis

One-way analysis

PCA Analysis

K-means clustering

One-way analysis with cluster

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DLCs for Disc Game (cont’d)

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DLCs for Disc Game (cont’d)

● Clustering results

4 effective clusters

● Implications

Heavy gamers with passion variations (1 & 4)

Gaming concentration

Casual gamers – followers (2 & 3)

Timing

Gameplay intensity

Price conscious

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DLCs for Disc Game (cont’d)

● Actions

Targeted approach to each of 4 segments

Messaging/relevance/timing/value propositions

● Impact

DLC sales significantly higher than expectation

Optimized marketing spending

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Clustering/Segmenting Gamers - Business

Applications

● Marketing DLCs for Disc Game

● Forecasting New Disc Game Sales

● Predicting PS4 Purchasers

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Forecasting New Disc Game Sales

● Old & aggregated forecast approach didn’t work

● Built forecasts based on gamer clusters

● Cluster gamers for a game from a franchise

Gamers (2 million)

Gameplay behaviors

Gamer attributes

● Impact

More reliable sales forecast

Increased understanding of gamers

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Franchises

Clustering/Segmenting Gamers - Business

Applications

● Marketing DLCs for Disc Game

● Forecasting New Disc Game Sales

● Predicting PS4 Purchasers

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Predicting PS4 Purchasers

● Clustered PS3 gamers

XX Million gamers: Gaming behaviors, gamer attributes

● Refined targeted audience

● Impact

Enhanced marketing strategies

1 million PS4 consoles sold – 1st day

10 million PS4 sold globally (as of end of July 2014)

#1 market position

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Takeaways

● Analytics works - No short cut (an iterated process)

● Domain knowledge is critical

● JMP/SAS – Powerful enabling tools

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Thanks! 22

QUESTIONS?

Acknowledge

● Much appreciation is extended to Jianfeng Ding, Senior Research Statistician

Developer at SAS/JMP, for her valuable advice and consulting in conducting

clustering analysis.

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