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Big data analytics for video, mobile,

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Big Data Analytics for Video,
Mobile, and Social Game
Monetization
By Kimbely Chulis
Published july 17 2012
Presented by
Ma Khin Nwe Oo, Ma Cing Gel Vung
Game Industry Changes and Trends
• The sheer size of the global game industry is staggering.
• According to ABI Research, web-based games will be parallel to
continued growth in video games played on the computer and to
explosive growth in mobile games.
• This translates into big opportunity for analytics providers.
Game Analytics
• Game developers are starting to adopt advanced analytics to support game
development, product design, targeted marketing efforts, and in-game
monetization.
• Many of off-the-shelf products adequately provide the expected standard list of
metrics for social games, including:
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Daily active users (DAU)
Monthly active users (MAU)
A combined DAU/MAU ratio
Engagement, which measures time spent playing a game
K-factor, which is an infection rate of the core and casual player
Average revenue per user (ARPU)
Lifetime value (LTV)
Game Monetization
• Now there is more of a convergence of business monetization approaches
between game types.
• Video Game, social and mobile games make money (monetize) in a few
ways.
Video Game
 Pay-to-play is where players must
pay a monthly subscription fee.
 Free-to-play usually involves an
upfront software cost but no
additional payments.
 Freemium allows players to
access game content and play for
free but offers options to pay for
additional content and access.
Social and mobile games
 Charge an initial purchase
subscription fee
 Freemium model
 Use actual money or Facebook Credits
to purchase in-game virtual goods
 In-game advertising
Cont'd
• Gamification is one of the hottest enterprise trends for 2012
• Use game mechanics and design to motivate people and drive specific
behaviors
• In a consumer behavior sense, it involves the introduction of game
elements such as leaderboards, badges, trophies, points, virtual
currency and credits
• NoSQL technology is used to manage the rapidly changing data
volume, sources as an input for analytics solutions.
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