Da ta Sc ie nc e in Ga ming Ple a se sta nd by. We bina r will - PowerPoint PPT Presentation

Da ta Sc ie nc e in Ga ming Ple a se sta nd by. We bina r will be g in a t 1:00 p.m. E DT Pre se nte d b y:

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Da ta Sc ie nc e in Ga ming

Ab o ut I nno va tio n Ana lytic s I nno va tio n Ana lytic s is the da ta a na lysis a nd ne w te c hno lo g ie s a rm o f T he I nno va tio n Gro up. L e ve ra g ing the Co mpa ny’ s e xpe rie nc e wo rking with industry o pe ra to rs, te c hno lo g y de ve lo pe rs a nd inve sto rs, I nno va tio n Ana lytic s use s q ua ntita tive me tho ds a s the ke y to unlo c king b usine ss insig hts in ma na g e me nt, stra te g y, a nd ma rke ting .

Pa ne lists Anthony “A.J.” Ma son – Princ ipa l, I nno vatio n Analytic s Ba se d o ut o f Winte r Pa rk, F lo rida , A.J.’ s c o ntrib utio ns inc lude da ta b a se de c isio n a na lysis, dig ita l inte ra c tive g a p a na lysis, prima ry c usto me r re se a rc h, so c ia l/ inte ra c tive g a ming pla tfo rm, a nd o n-site mo b ile c usto me r da ta c a pture . He pro vide s e xpe rtise in dire c t ma rke ting , CRM, c a mpa ig n a nd pro mo tio na l de sig n, lo ya lty pro g ra ms, e -c o mme rc e , me dia pla nning , b usine ss inte llig e nc e , c o nsume rinsig hts, sta tistic a l mo de ling , pa rtne rships, a nd b ra nding . A.J. ha s wo rke d a s a multi-c ha nne l ma rke ting e xe c utive in the inte rna tio na l, re g io na l, a nd trib a l g a ming a nd ho spita lity industry fo r L a s Ve g a s Sa nds Co rpo ra tio n, Ame rista r Ca sino s Inc ., a nd F o xwo o ds Re so rt Ca sino . His fo c us ha s b e e n o n de ve lo ping fully inte g ra te d ma rke ting stra te g ie s b y q ua ntifying the e c o no mic impa c t o f pro mo tio na l a nd a dve rtising spe nd. A.J. ho lds se ve ra l e c o no mic s de g re e s, a Ba c he lo r o f Arts de g re e fro m India na Unive rsity, a nd a Ma ste r o f Arts de g re e fro m the Unive rsity o f Ne va da , L a s Ve g a s. Ma tt Konopka – Princ ipa l, I nno vatio n Analytic s Ma tt is b a se d o ut o f Sa n F ra nc isc o a nd ha s e xpe rtise in q ua ntita tive a na lysis a nd sta tistic a l pro g ra mming fo r a dive rse a rra y o f a pplic a tio ns. He ha s c o nsulte d a s a le a d sta tistic a l a na lyst o n pro je c ts fo r fe de ra l g o ve rnme nt c lie nts inc luding the E nviro nme nta l Pro te c tio n Ag e nc y, the Na tio na l Oc e a nic a nd Atmo sphe ric Administra tio n, a nd the De pa rtme nt o f Justic e . Pro je c ts a nd c a se s inc lude e c o no mic da ma g e c a lc ula tio n fo r the De e pwa te r Ho rizo n o il spill, pro c e dura l a sse ssme nts o f the Ame ric a n Re c o ve ry a nd Re inve stme nt Ac t o f 2009, a nd E PA fina nc ia l a ssura nc e rule ma king e va lua tio ns fo r e xtra c tive industrie s. Ma tt g ra dua te d fro m Unive rsity o f Ca lifo rnia , Sa n Die g o 's Sc ho o l o f Inte rna tio na l Re la tio ns a nd Pa c ific Studie s with a Ma ste ro f Pa c ific a nd Inte rna tio na l Affa irs. He ho lds a B.A. fro m Ame ric a n Unive rsity in Inte rna tio na l Studie s.

Da ta Sc ie nc e

Wha t is da ta sc ie nc e ? An inte rdisc iplina ry fie ld tha t turns ra w da ta into insig hts b y le ve ra g ing sta tistic s, e c o no mic s, a nd a na lytic s Da ta Sc ie nc e  Custo me r b e ha vio r pre dic tive  Ope ra tio na l da ta wa re ho use s mo de ls  Custo me r Re la tio nship  A/ B T Ma na g e me nt Da ta b a se s e sting  Re ve nue Ma na g e me nt  E c o no me tric mo de ling o f Da ta b a se s c usto me r pric e se nsitivity  Custo me r sa tisfa c tio n surve ys  E xpe rime nta l o ptimiza tio n via  Co mple me nta ry da ta so urc e s c o ntro lle d te sting o n c usto me r sa mple s  Ge o g ra phic a l I nfo rma tio n Syste ms  De mo g ra phic da ta (Ce nsus, e tc .)

Sc ie ntific Me tho d a s Wo rkflo w 12 F ra me Que stio n Re c o mme nd Co lle c t Da ta Ac tio n De sc rib e Pe rfo rm Insig ht Sta tistic a l T e st

Sc ie ntific Me tho d a s Wo rkflo w F ra me Que stio n Re c o mme nd Co lle c t Da ta Ac tio n T o o muc h unstruc ture d De sc rib e Pe rfo rm da ta Insig ht Sta tistic a l T e st 13

Sc ie ntific Me tho d a s Wo rkflo w F ra me Que stio n Re c o mme nd Co lle c t Da ta Ac tio n F a ilure to turn insig hts into a c tio ns De sc rib e Pe rfo rm Insig ht Sta tistic a l T e st 14

Sc ie ntific Me tho d a s Wo rkflo w F ra me Que stio n Re c o mme nd Co lle c t Da ta Ac tio n E xpe nsive I T & Skills De sc rib e Pe rfo rm Insig ht Sta tistic a l T e st 15

Ca se : Pro mo tio na l T e sting

Ca se : Pro mo tio na l T e sting $20 Promo Expense $120 $100 Revenue Profit $50 $70 $90 Revenue Revenue Revenue

Ca se : Pro mo tio na l T e sting Se g me nt A B C

Ca se : Pro mo tio na l T e sting $30 Promo Expense A B C $5 $10 $15 $210 Promo Promo Promo $180 Revenue Required Required Required Profit $50 $70 $90 Revenue Revenue Revenue

Ca se : Pro mo tio na l T e sting

Pa ne list Que stio ns

Ho w do yo u de sc rib e da ta sc ie nc e ? Wha t is the ro le o f da ta sc ie nc e in the g a ming industry?

Wha t hurdle s a re the re to instituting pro c e sse s info rme d b y da ta sc ie nc e ? Ho w c a n we de c re a se the impa c t o f the se hurdle s?

Wha t a re so me pra c tic a l a pplic a tio ns fo r da ta sc ie nc e in g a ming ? Whic h o pe ra tio na l a re a s a re mo st b e ne fitte d b y da ta sc ie nc e ?

Audie nc e Q&A

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