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

Pre se nte d b y:

Ple a se sta nd by. We bina r will be g in a t 1:00 p.m. E DT

T e c hnic a l Ove rvie w

Che c k vie w se tting s

 E

nsure the to p rig ht ic o ns a re hig hlig hte d b lue

Ask a q ue stio n

 At yo ur to p rig ht c o rne r, ma ke sure the “Q&A” b o x is b lue

(ie e na b le d). T he n a t yo ur b o tto m rig ht c o rne r, a sk “All Pa ne lists” a nd type / sub mit yo ur q ue stio n.

I f yo u’ re a tte nding via mo b ile pho ne

 Do ub le ta p the b o x sho wing o ur pa ne lists, a nd the y’ ll g o

full-sc re e n

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 .

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

• 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.

Pa ne lists

Da ta Sc ie nc e

Wha t is da ta sc ie nc e ?

Da ta

 Ope ra tio na l da ta wa re ho use s

 Custo me r Re la tio nship

Ma na g e me nt Da ta b a se s

 Re ve nue Ma na g e me nt

Da ta b a se s

 Custo me r sa tisfa c tio n surve ys

 Co mple me nta ry da ta so urc e 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 nc e

 Custo me r b e ha vio r pre dic tive

mo de ls

 A/ B T

e sting

 E

c o no me tric mo de ling o f c usto me r pric e se nsitivity

 E

xpe rime nta l o ptimiza tio n via c o ntro lle d te sting o n c usto me r sa mple s

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

Sc ie ntific Me tho d a s Wo rkflo w

12

F ra me Que stio n Co lle c t Da ta Pe rfo rm Sta tistic a l T e st De sc rib e Insig ht Re c o mme nd Ac tio n

13

F ra me Que stio n Co lle c t Da ta Pe rfo rm Sta tistic a l T e st De sc rib e Insig ht Re c o mme nd Ac tio n

T

• o muc h

unstruc ture d da ta

Sc ie ntific Me tho d a s Wo rkflo w

14

F ra me Que stio n Co lle c t Da ta Pe rfo rm Sta tistic a l T e st De sc rib e Insig ht Re c o mme nd Ac tio n

F a ilure to turn insig hts into a c tio ns

Sc ie ntific Me tho d a s Wo rkflo w

15

F ra me Que stio n Co lle c t Da ta Pe rfo rm Sta tistic a l T e st De sc rib e Insig ht Re c o mme nd Ac tio n

E xpe nsive I T & Skills

Sc ie ntific Me tho d a s Wo rkflo w

Ca se : Pro mo tio na l T e sting

$50

Revenue

$70

Revenue

$90

Revenue

$100

Profit

$20

Promo Expense

$120

Revenue

Ca se : Pro mo tio na l T e sting

Ca se : Pro mo tio na l T e sting

Se g me nt A B C

A B C

$50

Revenue

$70

Revenue

$90

Revenue

$180

Profit

$30

Promo Expense

$210

Revenue

$5

Promo Required

$10

Promo Required

$15

Promo Required

Ca se : Pro mo tio na l T e sting

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

the inno va tio ng ro up.c o m