How to Harvest the Gold in your Game Sales Database Nick Berry,
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How to Harvest the Gold in your Game Sales Database Nick Berry, M.Eng, ARAeS, CIPP President, DataGenetics All logos and trademarks in this presentation are property of their respective owners.
Biography 1988 1994 2008 2010
Agenda 1) What is Social Gaming? 2) Why is it so popular? 3) How to find out more about download customers 4) Examples
What is a Social Game? “But they’re not social!” (After all, “Casual Games” are not casual either!) P P “A game played on a Social Network” So what is a game? Not Work! “Any non-obligatory activity that is performed for fun!”
A Social Game is any non-obligatory activity that is performed, for fun, on a Social Network.
Players broadcast their indulgences, performances and achievements (both actively and passively). Facebook has exposed people to copious quantities of non-essential activities and provided easy channels to announce participation in these entertainments to others. Why are Social Games so Popular? In no more than a couple of clicks, exposed users can be having fun, and jumping on the latest bandwagon of distraction. Discoverability Curiosity, Invitation, Peer Pressure, Challenge. Accessibility Camaraderie Whilst social could be considered a poor adjective to describe games when many games are solo activities, these activities do earn it the moniker social because they offer a shared experience. Albeit asynchronously, all the people who have enjoyed the same activity have been down the same path.
What do you know about your existing customers?
Age 18 Age 49 Age 23 Age 38 Age 27 Age 17 Age 58 Age 16 Social Game Developers have it “easy”
What do you know about your Deluxe Download customers?
Sales Database Sales Date Sales Value Credit card Name Credit card Number 2/3/2001 2/3/2001 2/3/2001 2/3/2001 6.95 2/3/2001 6.95 2/3/2001 6.95 6.95 2/3/2001 2/3/2001 Nicholas Berry 6.95 Nicholas Berry 6.95 Nicholas Berry Nicholas Berry 6.95 6.95 3713 xxxx xxxx 9980 Nicholas Berry 3713 xxxx xxxx 9980 Nicholas Berry 3713 xxxx xxxx 9980 3713 xxxx xxxx 9980 Nicholas Berry Nicholas Berry 3713 3713 xxxx xxxx xxxx xxxx 9980 9980 3713 3713 xxxx xxxx xxxx xxxx 9980 9980
What’s in a name? (Gender) Taylor Jessica Nicholas What about androgynous names?
US Social Security Administration NAME Database of all registered names in USA since 1880 complete with gender. Year Frequency Mary Susan F F 1967 1967 25,320 22,259 Karen Angela Melissa F 1967 21,544 F F 1967 1967 19,537 18,370 Patricia Amy Elizabeth F F F 1967 1967 1967 17,745 16,130 16,110 Christine Laura Julie F F F 1967 1967 1967 15,992 15,820 15,541 Cynthia Donna F F 1967 1967 15,336 14,789 Tina F 1967 14,154 Deborah F 1967 14,004
History of Male Names
History of Female Names:
Scrabble Score Score Letters 1 A,E,I,O,U,L,N,R,S,T 2 D,G 3 B,C,M,P 4 F,H,V,W,Y 5 K 8 J,X 10 Q,Z Creative spelling: Izzabellah (33 points) instead of Issabella Kristyn (14 points) instead of Kristin Z replacing S Y replacing I (11 points) (11 points)
Trivia – Highest scoring name in the 86,987 distinct names in the SSA database is: Jazzmyne (scoring 38 points)
Returning to Androgynous names 2009 Data
Taylor over the years
Nobody lives forever Male % Female % Number of male Taylors born in 2012 (still alive) Number of male Taylors born in 2011 (still alive) Number of male Number of male Taylors born in 1940 (still alive) Number of female Taylors born in 2012 (still alive) Number of female Taylors born in 2011 (still alive) Number of female Number of female Taylors born in 1940 (still alive) Males named Taylor who are still alive Females named Taylor who are still alive
Life (Death) tables 1901 Life Tables CDC/NCHS – Center for Disease Control and Prevention/National Center for Health Statistics
Life (Death) Percentage chance of reaching a specified age. 65 92.1% 88.7% 82.4% 67.9% 39.1%
Percentage Chance of Reaching Specified Age 100% 0% Gender Differences
Gender Differences – Age at Death Male 1930 Female Age at Death (per 100,000) 1980
Multiply
Taylor Probability density function
Who names their child “Ethel” these days? Probability Density Functions
Facebook demographics
13 Male AGE 65 FaceBook Demographics Female
Many users of college age In USA large number of members over 65 FaceBook Demographics
Bejeweled
Jay Leno vs. Conan
38.41% correlation Comparing Demographic “Genes”
80.89% correlation
Bejeweled Blitz Affinity
What are fans of glee on facebook interested in?
100% Affinity for Games 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Si m s Pe tS ty ie c o i tr Te s W C ii n ou y tr or St G y u r ita Su H pe er r o ar M io B ro s P vi et ll e oo D dl e m Ju p C iv il i tio za n Z oo W or ld Pi ll o w g Fi ht W ii t Fi Te Tw xt t is C r s s e n ft ta an ge bl ke ar ar ra A et ow b at o c W W d T P C B ra ar tle e en n fia m of ir Sc W rm V as a e p s f a ar C d r M F o B 2 ol le am d s H tt V rl e s o er S t a W s x ob Te M v ity ill e ud dy PS 3 W a r to rs m
Howard Stern Battlestar Galactica Top Gear Oprah Winfrey Show Medium Martha Stewart Star Trek Biggest Loser Jay Leno South Park 80% Ellen Degenerous 90% Conan oBrien Law and Order Colbert Criminal Minds Two and a Half Men Big Bang Theory Mythbusters Sex and the City Ghost Whisperer NCIS Desperate Housewives Simpsons The Bachelor CSI Dr Who Ugly Betty Family Guy Heroes The Office Lost How I met your Mother Scrubs Saturday Night Live Americas Next Top Model SpongeBob MTV American Idol Jersey Shore 100% TV Shows 70% 60% 50% 40% 30% 20% 10% 0%
100% Music 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% y Ta w rS o l if t dy a L a ag G ty Ka y rr e P ey ir tn B s ar e Sp i ak h S ra in st Ju r be e Bi ri Av e gn i av lL na n ha Ri k ac l B ed Ey as Pe l ae h ic M n so k c Ja k an r F a tr a n Si d Re i li h C ot H s er p p Pe v El is y rr a B w il o n a M
80% 80% 70% 70% 60% 30% 20% 10% 20% 0% 10% 0% Crocs 90% Adidas 90% Reebok 90% Nike 100% Puma 100% Converse Pizza Hut Dunkin D. 30% Dairy Q. 40% Taco Bell 50% McDonalds 60% Starbucks Red Bull Coca-. Pepsi 100% 80% 70% 60% 50% 50% 40% 40% 30% 20% 10% 0%
90% 80% 80% 80% 70% 70% 70% 60% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% Cigars 90% Investing 90% Foursq. 100% Twitter 100% iTunes Dogs Cats Horses Gardening NASCAR Golf Martial Arts Knitting Scuba Diving Yoga Fishing Jogging Baking Skiing Snowboarding Soccer Fashion Makeup 100% 50% 40% 30% 20% 10% 0%
Example #1 GreatPokerHands Texas Hold’em Poker Strategy cards sold at retail.
GreatPokerHands sales Database
GreatPokerHands Age/Gender Profile Children under 18 do not have credit cards
45.63% 34.81% 25.72% GreatPokerHand Sales Correlations
Results:
Example CPC Prices: Texas Holdem 1.73 Golf (74.77%) 0.88 Texas Holdem 2.05 - 3.06 Scuba Diving (65.93%) 0.79 - 1.16 NASCAR (65.56%) 0.41 - 0.56
White House Visitor Logs
Every visitor to White House recorded, but no gender or age information 1.95 million 1.95 records available
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