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Making Data Sexy

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Datalicious
Datalicious

The presentation discusses the four main data categories in correlation with marketing and analytics strategies.

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>  Making  data  sexy  <   Turning  raw  data  into     ac.onable  insights  
>  The  datalicious  elevator  pitch   “Using  data  to  widen  the  funnel”   Media  A:ribu<on  &  Modeling   Op<mise  channel  mix,  predict  sales   Targeted  Direct  Marke<ng     Increase  relevance,  reduce  churn   Tes<ng  &  Op<misa<on   Remove  barriers,  drive  sales   Boos<ng  ROI  
Make  data  sexy   by  turning  it  into     ac<onable  insights   August  2011   ©  Datalicious  Pty  Ltd   3  
Standardise  metrics   August  2011   ©  Datalicious  Pty  Ltd   4  
August  2011   ©  Datalicious  Pty  Ltd   5  
Break  down  data  silos   August  2011   ©  Datalicious  Pty  Ltd   6  
>  Establish  a  single  source  of  truth   Insights   Repor<ng   August  2011   ©  Datalicious  Pty  Ltd   7  
>  Combine  profile  data  sources   CRM  Profile   Site  Behaviour   one-­‐off  collec.on  of  demographical  data     tracking  of  purchase  funnel  stage   +   age,  gender,  address,  etc   browsing,  checkout,  etc   customer  lifecycle  metrics  and  key  dates   tracking  of  content  preferences   profitability,  expira<on,  etc   products,  brands,  features,  etc   predic.ve  models  based  on  data  mining   tracking  of  external  campaign  responses   propensity  to  buy,  churn,  etc   search  terms,  referrers,  etc   historical  data  from  previous  transac.ons   tracking  of  internal  promo.on  responses   average  order  value,  points,  etc   emails,  internal  search,  etc   Updated  Occasionally   Updated  Con<nuously   August  2011   ©  Datalicious  Pty  Ltd   8  
>  3rd  party  data  enhancements   Customer  profile  data   Geo-­‐demographic  data   +   The  whole  is  greater     than  the  sum  of  its  parts   3rd  party  data   August  2011   ©  Datalicious  Pty  Ltd   9  
Visualise  your  data   August  2011   ©  Datalicious  Pty  Ltd   10  
What  trends  can  you  iden<fy  in  5  seconds     by  looking  at  the  raw  data  only?   August  2011   ©  Datalicious  Pty  Ltd   11  
August  2011   ©  Datalicious  Pty  Ltd   12  
August  2011   ©  Datalicious  Pty  Ltd   13  
August  2011   ©  Datalicious  Pty  Ltd   14  
August  2011   ©  Datalicious  Pty  Ltd   15  
RED  =  No  single  men   August  2011   ©  Datalicious  Pty  Ltd   16  
Allocate  a  data  budget   August  2011   ©  Datalicious  Pty  Ltd   17  
Combine  data  &  crea<vity   August  2011   ©  Datalicious  Pty  Ltd   18  
August  2011   ©  Datalicious  Pty  Ltd   19  
Contact  us   insights@datalicious.com     Learn  more   blog.datalicious.com     Follow  me   twi:er.com/datalicious     August  2011   ©  Datalicious  Pty  Ltd   20  
Data  >  Insights  >  Ac<on   August  2011   ©  Datalicious  Pty  Ltd   21  

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