data driven targeting - behavioural targeting

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[ Data driven marke.ng ] Reducing waste and increasing relevance through targe3ng

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The presentation discusses the significance of data in marketing through targeting.

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Page 1: Data Driven Targeting - Behavioural Targeting

[  Data  driven  marke.ng  ]  Reducing  waste  and  increasing  relevance  through  targe3ng  

Page 2: Data Driven Targeting - Behavioural Targeting

[  Using  data  to  reduce  waste  ]  

August  2010   ©  Datalicious  Pty  Ltd   2  

Media  a8ribu.on  

Op.mising  channel  mix  

Tes.ng  Improving  usability  

$$$  

Targe.ng    Increasing  relevance  

Page 3: Data Driven Targeting - Behavioural Targeting

[  Increase  revenue  by  10-­‐20%  ]  

August  2010   ©  Datalicious  Pty  Ltd   3  

By  coordina.ng  the  consumer’s  end-­‐to-­‐end  experience,  companies  could  enjoy  revenue  increases  of  10-­‐20%.  

Google:  “get  more  value  from  digital  marke.ng”    or  h8p://bit.ly/cAtSUN  

Source:  McKinsey  Quarterly,  2010  

Page 4: Data Driven Targeting - Behavioural Targeting

[  The  consumer  data  journey  ]  

August  2010   ©  Datalicious  Pty  Ltd   4  

To  reten.on  messages  To  transac.onal  data  

From  suspect  to   To  customer  

From  behavioural  data   From  awareness  messages  

Time  Time  prospect  

Page 5: Data Driven Targeting - Behavioural Targeting

[  Coordina.on  across  channels  ]      

August  2010   ©  Datalicious  Pty  Ltd   5  

Off-­‐site  targe.ng  

On-­‐site  targe.ng  

Profile    targe.ng  

Genera.ng  awareness  

Crea.ng  engagement  

Maximising  revenue  

TV,  radio,  print,  outdoor,  search  marke3ng,  display  ads,  performance  networks,  affiliates,  social  media,  etc  

Retail  stores,  call  centers,  brochures,  websites,  landing  pages,  mobile  apps,  online  chat,  etc  

Outbound  calls,  direct  mail,  emails,  SMS,  etc  

Page 6: Data Driven Targeting - Behavioural Targeting

Off-­‐site  targe3ng  

On-­‐site  targe3ng  

Profile  targe3ng  

[  Combining  targe.ng  plaZorms  ]  

August  2010   ©  Datalicious  Pty  Ltd   6  

Page 7: Data Driven Targeting - Behavioural Targeting

[  Targe.ng  plaZorms  ]  

§  Off-­‐site  targe3ng  –  Ad  networks:  Google,  Yahoo,  ValueClick,  etc  –  Ad  servers:  DoubleClick,  Eyeblaster,  Atlas,  etc  

§  On-­‐site  targe3ng  –  Paid:  Omniture  Test&Target  (Offerma3ca,  TouchClarity),  Memetrics  (Accenture),  Op3most  (Autonomy),  Ke[a  (Acxiom),  AudienceScience,  Maxymiser,  Amadesa,  etc  

–  Free:  BTBuckets,  Google  Analy3cs,  etc  §  Profile  targe3ng  –  Email  pla^orms:  Inxmail,  Trac3on,  Returnity,  etc  – Marke3ng  automa3on:  Aprimo,  Unica,  Eloqua,  etc  

August  2010   ©  Datalicious  Pty  Ltd   7  

Page 8: Data Driven Targeting - Behavioural Targeting

On-­‐site    segments  

Off-­‐site  segments  

[  Combining  technology  plaZorms  ]  

August  2010   ©  Datalicious  Pty  Ltd   8  

On  and  off-­‐site  targe.ng  plaZorms  should  use    iden.cal  triggers  to  sort  visitors  into  segments  

Page 9: Data Driven Targeting - Behavioural Targeting

August  2010   ©  Datalicious  Pty  Ltd   9  

Page 10: Data Driven Targeting - Behavioural Targeting

August  2010   ©  Datalicious  Pty  Ltd   10  

Page 11: Data Driven Targeting - Behavioural Targeting

Customer  data  

[  Combining  data  sets  ]  

August  2010   ©  Datalicious  Pty  Ltd   11  

3rd  party  data  

+   The  whole  is  greater    than  the  sum  of  its  parts  

Web  analy.cs  data  

Page 12: Data Driven Targeting - Behavioural Targeting

[  Behaviours  plus  transac.ons  ]  

August  2010   ©  Datalicious  Pty  Ltd   12  

one-­‐off  collec3on  of  demographical  data    age,  gender,  address,  etc  customer  lifecycle  metrics  and  key  dates  profitability,  expira.on,  etc  predic3ve  models  based  on  data  mining  

propensity  to  buy,  churn,  etc  historical  data  from  previous  transac3ons  

average  order  value,  points,  etc  

CRM  Profile  

UPDATED  OCCASIONALLY  

+  tracking  of  purchase  funnel  stage  

browsing,  checkout,  etc  tracking  of  content  preferences  

products,  brands,  features,  etc  tracking  of  external  campaign  responses  

search  terms,  referrers,  etc  tracking  of  internal  promo3on  responses  

emails,  internal  search,  etc  

Site  Behaviour  

UPDATED  CONTINUOUSLY  

Page 13: Data Driven Targeting - Behavioural Targeting

The  study  examined  data    from  two  of  the  UK’s  busiest    ecommerce  websites,  ASDA  and  William  Hill.    Given  that  more  than  half    of  all  page  impressions  on    these  sites  are  from  logged-­‐in    users,  they  provided  a  robust    sample  to  compare  IP-­‐based  and  cookie-­‐based  analysis  against.  The  results  were  staggering,  for  example  an  IP-­‐based  approach  overes3mated  visitors  by  up  to  7.6  3mes  whilst  a  cookie-­‐based  approach  overes.mated  visitors  by  up  to  2.3  .mes.    Google:  ”red  eye  cookie  report  pdf”  or  h8p://bit.ly/cszp2o      

[  Overes.ma.ng  unique  visitors  ]  

Source:  White  Paper,  RedEye,  2007  

Page 14: Data Driven Targeting - Behavioural Targeting

[  Maximise  iden.fica.on  points  ]  

20%  

40%  

60%  

80%  

100%  

120%  

140%  

160%  

0   4   8   12   16   20   24   28   32   36   40   44   48  

Weeks  

−−−  Probability  of  iden3fica3on  through  Cookies  

Page 15: Data Driven Targeting - Behavioural Targeting

August  2010   ©  Datalicious  Pty  Ltd   15  

Datalicious  SuperCookie  Persistent  Flash  cookie  that  cannot  be  deleted  

Page 16: Data Driven Targeting - Behavioural Targeting

August  2010   ©  Datalicious  Pty  Ltd   16  

Page 17: Data Driven Targeting - Behavioural Targeting

[  Sample  site  visitor  composi.on  ]  

August  2010   ©  Datalicious  Pty  Ltd   17  

30%  exis.ng  customers  with  extensive  profile  including  transac3onal  history  of  which  maybe  50%  can  actually  be  iden3fied  as  individuals    

30%  new  visitors  with  no  previous  website  history  aside  from  campaign  or  referrer  data  of  which  maybe  50%  is  useful  

10%  serious  prospects  with  limited  profile  data  

30%  repeat  visitors  with  referral  data  and  some  website  history  allowing  50%  to  be  segmented  by  content  affinity  

Page 18: Data Driven Targeting - Behavioural Targeting

Phase   Segment  A   Segment  B   Channels  

Awareness  

Considera.on  

Purchase  Intent  

Up/Cross-­‐Sell  

[  Developing  a  targe.ng  matrix  ]  

Page 19: Data Driven Targeting - Behavioural Targeting

Phase   Segment  A   Segment  B   Channels  

Awareness   Seen  this?   Social,  display,  search,  etc  

Considera.on   Great  feature!   Social,  search,  website,  etc  

Purchase  Intent   Great  value!   Search,  site,  emails,  etc  

Up/Cross-­‐Sell   Add  this!   Direct  mail,  emails,  etc  

[  Developing  a  targe.ng  matrix  ]  

Page 20: Data Driven Targeting - Behavioural Targeting

Avinash  Kaushik:  “The  principle  of  garbage  in,  garbage  out  applies  here.  […]  what  makes  a  behaviour  targe<ng  pla=orm  <ck,  and  produce  results,  is  not  its  intelligence,  it  is  your  ability  to  actually  feed  it  the  right  content  which  it  can  then  target  […].  You  feed  your  BT  system  crap  and  it  will  quickly  and  efficiently  target  crap  to  your  customers.  Faster  then  you  could  ever  have  yourself.”  

[  Quality  content  is  key  ]  

Page 21: Data Driven Targeting - Behavioural Targeting

1.  Define  success  metrics  2.  Define  and  validate  segments  3.  Develop  targe3ng  and  message  matrix    4.  Transform  matrix  into  business  rules  5.  Develop  and  test  content  6.  Start  targe3ng  and  automate  7.  Keep  tes3ng  and  refining  8.  Communicate  results  

[  Keys  to  effec.ve  targe.ng  ]  

August  2010   ©  Datalicious  Pty  Ltd   21  

Page 22: Data Driven Targeting - Behavioural Targeting

Google:  “change  one  word  double  conversion”    or  h8p://bit.ly/bpyqFp  

[  ClickTale  tes.ng  case  study  ]  

August  2010   ©  Datalicious  Pty  Ltd   22  

Page 23: Data Driven Targeting - Behavioural Targeting

August  2010   ©  Datalicious  Pty  Ltd   23  

ADMA  short  course  “Analyse  to  op.mise”    

In  Melbourne  &  Sydney  October/November  

By  Datalicious  

Page 24: Data Driven Targeting - Behavioural Targeting

August  2010   ©  Datalicious  Pty  Ltd   24  

Email  me  [email protected]  

 Talk  to  us  

ADMA  Forum  Stand  347    

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