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ANZ Marketing Analytics
 

ANZ Marketing Analytics

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The presentation discusses the significance of data in marketing campaigns.

The presentation discusses the significance of data in marketing campaigns.

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    ANZ Marketing Analytics ANZ Marketing Analytics Presentation Transcript

    • >  Marke(ng  Analy(cs  <   Using  data  to  boost  return  on   marke1ng  investment  
    • >  Short  but  sharp  history  §  Datalicious  was  founded  in  late  2007  §  Strong  Omniture  web  analy1cs  history  §  1  of  4  preferred  Omniture  partners  globally  §  Now  360  data  agency  with  specialist  team  §  Combina1on  of  analysts  and  developers  §  Carefully  selected  best  of  breed  partners  §  Driving  industry  best  prac1ce  (ADMA)  §  Turning  data  into  ac1onable  insights  §  Execu1ng  smart  data  driven  campaigns      December  2011   ©  Datalicious  Pty  Ltd   2  
    • >  Smart  data  driven  marke(ng   “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  ROMI  December  2011   ©  Datalicious  Pty  Ltd   3  
    • 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Media  a<ribu(on  December  2011   ©  Datalicious  Pty  Ltd   4  
    • >  The  ideal  media  dashboard   Channel   Investment   ROMI   Return   Brand  equity   ($100)   n/a   $40   Baseline   Offline   $7   330%   $30   TV,  print,  outdoor,  etc   Direct   $1   400%   $5   Direct  mail,  email,  etc   Online   $2   1150%   $25   Search,  display,  social,  etc  December  2011   ©  Datalicious  Pty  Ltd   5  
    • >  Duplica(on  across  channels     Paid     Bid     Search   Mgmt   $   Banner     Ad     Ads   Server   $   Email     Email   Blast   PlaNorm   $   Organic   Google   Search   Analy(cs   $  December  2011   ©  Datalicious  Pty  Ltd   6  
    • >  Cookie  expira(on  impact   Paid     Bid     Search   Mgmt   $   Banner     Banner     Ad     Ad  Click   Ad  View   Server   $   Email     Email   Expira(on   Blast   PlaNorm   $   Organic   Google   Search   Analy(cs   $  December  2011   ©  Datalicious  Pty  Ltd   7  
    • >  De-­‐duplica(on  across  channels     Paid     Search   $   Banner     Ads   $   Central   Analy(cs   PlaNorm   Email     Blast   $   Organic   Search   $  December  2011   ©  Datalicious  Pty  Ltd   8  
    • >  Campaign  flows  are  complex   =  Paid  media   Organic     PR,  WOM,   search   events,  etc   =  Viral  elements   =  Sales  channels   YouTube,     Home  pages,   Paid     TV,  print,     blog,  etc   portals,  etc   search   radio,  etc   Direct  mail,     Landing  pages,   Display  ads,   email,  etc   offers,  etc   affiliates,  etc   CRM   Facebook   program   Twi<er,  etc   POS  kiosks,   Call  center,     loyalty  cards,  etc   retail  stores,  etc  December  2011   ©  Datalicious  Pty  Ltd   9  
    • >  Media  channels  feed  each  other   TV/Print/DM     audience   Banner   Search   audience   audience  December  2011   ©  Datalicious  Pty  Ltd   10  
    • >  Ad  server  exposure  test   Banner   TV/Print   Search   Impression   Response   Response   $   Banner   Search   Direct   Impression   Response   Response   $   Users  are   segmented   before  1st   ad  is  even   Exposed  group:  90%  of  users  get  branded  message   served     Control  group:  10%  of  users  get  non-­‐branded  message   Banner   Search   Direct   Impression   Response   Response   $  December  2011   ©  Datalicious  Pty  Ltd   11  
    • >  Indirect  display  impact    December  2011   ©  Datalicious  Pty  Ltd   12  
    • >  Indirect  display  impact    December  2011   ©  Datalicious  Pty  Ltd   13  
    • >  Indirect  display  impact    December  2011   ©  Datalicious  Pty  Ltd   14  
    • >  Success  a<ribu(on  models     Banner     Paid     Organic   Success   Last  channel   Search   Ad   Search   $100   $100   gets  all  credit   Banner     Paid     Email     Success   First  channel   Ad   $100   Search   Blast   $100   gets  all  credit   Paid     Banner     Affiliate     Success   All  channels  get   Search   Ad   Referral   $100   $100   $100   $100   equal  credit   Print     Social     Paid     Success   All  channels  get   Ad   Media   Search   $33   $33   $33   $100   par(al  credit  December  2011   ©  Datalicious  Pty  Ltd   15  
    • >  First  and  last  click  a<ribu(on     Chart  shows   percentage  of   channel  touch   points  that  lead   Paid/Organic  Search   to  a  conversion.   Neither  first     Emails/Shopping  Engines   nor  last-­‐click   measurement   would  provide   true  picture    December  2011   ©  Datalicious  Pty  Ltd   16  
    • >  Full  purchase  path  tracking   Introducer   Influencer   Influencer   Closer   $   Paid     Display     Social   Direct     Online   search   ad  clicks   referrals   site  visits   sales   Display     Affiliate   Social     Retail     Offline   ad  views   clicks   buzz   store  visits   sales   TV/print     Organic   Website   Direct  mail,   Life(me   ad  views   search   events   emails   profit  December  2011   ©  Datalicious  Pty  Ltd   17  
    • >  Search  call  to  ac(on  for  offline    December  2011   ©  Datalicious  Pty  Ltd   18  
    • >  Personalised  URLs  for  direct  mail   VickyCarroll.myspaday.com  >  redirect  to  >  myspaday.com?     CampaignID=DM:123&   Demographics=F|35&   CustomerSegment=A1&   CustomerValue=High&   CustomerSince=2001&   ProductHistory=P1|P2&   NextBestOffer=P3&   ChurnRisk=Low   [...]  December  2011   ©  Datalicious  Pty  Ltd   21  
    • >  Offline  sales  driven  by  online   Adver(sing     Phone   Credit  check,   campaign   order   fulfilment   Retail   Confirma(on   order   email,  1st  login   Website   Online   Online  order   Virtual  order   research   order   confirma(on   confirma(on   Cookie  December  2011   ©  Datalicious  Pty  Ltd   22  
    • >  Event  ROI  extrapola(on   Product   Applica(on   Applica(on   Offline   Campaign   view   start   complete   conversion   @   @   Campaign   $10   $30   $60   $100   Campaign   $10   $30   $100   Campaign   $10   $100  December  2011   ©  Datalicious  Pty  Ltd   23  
    • >  Single  source  of  truth  repor(ng   Insights   Repor(ng  December  2011   ©  Datalicious  Pty  Ltd   24  
    • >  Where  to  collect  the  data     Ad  Server   Web  Analy(cs   Banner  impressions   Referral  visits   Banner  clicks   Social  media  visits   +   Organic  search  visits   Paid  search  clicks   Paid  search  visits   Email  visits,  etc   Lacking  organic  visits   Lacking  ad  impressions   More  granular  &  complex   Less  granular  &  complex  December  2011   ©  Datalicious  Pty  Ltd   25  
    • >  Raw  a<ribu(on  data  Web  Analy(cs  data  sample  (AD  IMPRESSION  >)  AFFILIATE  >  SEARCH  >  $$$  SEARCH  >  SOCIAL  >  EMAIL  >  DIRECT  >  $$$    Ad  Server  data  sample  01/01/2011  12:00  AD  IMPRESSION  01/01/2011  12:05  PAID  SEARCH  07/01/2011  17:00  EMAIL  08/01/2011  15:00  $$$    December  2011   ©  Datalicious  Pty  Ltd   26  
    • >  Purchase  path  for  each  cookie   Mobile   Home   Work   Tablet   Media   Etc  December  2011   ©  Datalicious  Pty  Ltd   27  
    • >  Understanding  channel  mix  December  2011   ©  Datalicious  Pty  Ltd   28  
    • >  Website  entry  survey     De-­‐duped  Campaign  Report   Greatest  Influencer  on  Branded  Search  /  STS   }   Channel   %  of  Conversions   Channel   %  of  Influence   Straight  to  Site   27%   Word  of  Mouth   32%   SEO  Branded   15%   Blogging  &  Social  Media   24%   SEM  Branded   9%   Newspaper  Adver1sing   9%   SEO  Generic   7%   Display  Adver1sing   14%   SEM  Generic   14%   Email  Marke1ng   7%   Display  Adver1sing   7%   Retail  Promo1ons   14%   Affiliate  Marke1ng   9%   Referrals   5%   Conversions  aoributed  to  search  terms   Email  Marke1ng   7%   that  contain  brand  keywords  and  direct   website  visits  are  most  likely  not  the   origina1ng  channel  that  generated  the   awareness  and  as  such  conversion   credits  should  be  re-­‐allocated.    December  2011   ©  Datalicious  Pty  Ltd   30  
    • >  Adjus(ng  for  offline  impact   -­‐5   -­‐15   -­‐10   +5   +15   +10  December  2011   ©  Datalicious  Pty  Ltd   31  
    • >  Custom  a<ribu(on  models     Introducer   Influencer   Influencer   Closer   $   Even     25%   25%   25%   25%   A<rib.   Exclusion   33%   33%   33%   0%   A<rib.   ?   ?   ?   ?   Custom   A<rib.  December  2011   ©  Datalicious  Pty  Ltd   32  
    • >  Path  across  different  segments   Introducer   Influencer   Influencer   Closer   $   Product     Channel  1   Channel  2   Channel  3   Channel  4   A  vs.  B   New   Channel  1   Channel  2   Channel  3   Channel  4   prospects   Exis(ng   Channel  1   Channel  2   Channel  3   Product  4   customers  December  2011   ©  Datalicious  Pty  Ltd   33  
    • 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Experience  op(misa(on  December  2011   ©  Datalicious  Pty  Ltd   34  
    • >  Increase  revenue  by  10-­‐20%     Capture  internet  traffic   Capture  50-­‐100%  of  fair  market  share  of  traffic   Increase  consumer  engagement   Exceed  50%  of  best  compe1tor’s  engagement  rate     Capture  qualified  leads  and  sell   Convert  10-­‐15%  to  leads  and  of  that  20%  to  sales   Building  consumer  loyalty   Build  60%  loyalty  rate  and  40%  sales  conversion   Increase  online  revenue   Earn  10-­‐20%  incremental  revenue  online  December  2011   ©  Datalicious  Pty  Ltd   35  
    • >  New  consumer  decision  journey   The  consumer  decision  process  is  changing  from  linear  to  circular.  December  2011   ©  Datalicious  Pty  Ltd   36  
    • >  New  consumer  decision  journey   The  consumer  decision  process  is  changing  from  linear  to  circular.   Online  research     Change  increases   the  importance  of   experience  during   research  phase.  December  2011   ©  Datalicious  Pty  Ltd   37  
    • December  2011   ©  Datalicious  Pty  Ltd   38  
    • December  2011   ©  Datalicious  Pty  Ltd   39  
    • 40  December  2011   ©  Datalicious  Pty  Ltd  
    • December  2011   ©  Datalicious  Pty  Ltd   41  
    • >  Seamless  research  experience   TV,  print,     Display     direct  mail,  etc   ads   Ad  Server  /  SuperTag   Organic,  paid   Display  ad     search   re-­‐targe(ng   AdWords   Ad  Server  /  SuperTag   Test&Target  /  SuperTag   Customised   landing  pages   Test&Target  /  SuperTag   ANZ.com     Applica(on   re-­‐targe(ng   process   Fall-­‐out  email   follow-­‐up  December  2011   ©  Datalicious  Pty  Ltd   42  
    • >  Network  wide  re-­‐targe(ng   Frequent  Flyer  campaign   Access  Advantage  campaign   Home  Loans  campaign   Card   Access   Loan   prospect   prospect   prospect   Card   Access   Loan   customer   customer   customer   Loan   Loan   Access   prospect   prospect   prospect  December  2011   ©  Datalicious  Pty  Ltd   43  
    • >  Network  wide  re-­‐targe(ng   Group  wide  campaign  with  approximate  impression  targets  by  product  rather  than  hard  budget  limita(ons   Card   Access   Loan   prospect   prospect   prospect   Card   Access   Loan   customer   customer   customer   Loan   Loan   Access   prospect   prospect   prospect  December  2011   ©  Datalicious  Pty  Ltd   44  
    • Targe(ng  before  tes(ng  December  2011   ©  Datalicious  Pty  Ltd   45  
    • >  Developing  a  targe(ng  matrix   Segmenta(on  based  on:  Search  keywords,   display  ad  clicks  and  website  behaviour   Purchase   Data     Cycle   Points   Access   Frequent   Etc   Advantage   Flyers   Research,   Acquisi(on   Acquisi(on   Acquisi(on   Ad  clicks,   considera(on   message  #A1   message  #A3   message  #A5   prod  views   Conversion   Acquisi(on   Acquisi(on   Acquisi(on   Applica(on   intent   message  #A2   message  #A4   message  #A6   starts   Reten(on,   Reten(on   Reten(on   Reten(on   Email  clicks,   cross-­‐sell   message  #R1   message  #R2   message  #R3   logins,  etc  December  2011   ©  Datalicious  Pty  Ltd   46  
    • >  Combining  data  sources   Website  behavioural  data   Campaign  response  data   +   The  whole  is  greater     than  the  sum  of  its  parts   Customer  profile  data  December  2011   ©  Datalicious  Pty  Ltd   47  
    • >  Transac(ons  plus  behaviours   CRM  Profile   Site  Behaviour   one-­‐off  collec1on  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   predic1ve  models  based  on  data  mining   tracking  of  external  campaign  responses   propensity  to  buy,  churn,  etc   search  terms,  referrers,  etc   historical  data  from  previous  transac1ons   tracking  of  internal  promo1on  responses   average  order  value,  points,  etc   emails,  internal  search,  etc   Updated  Occasionally   Updated  Con(nuously  December  2011   ©  Datalicious  Pty  Ltd   48  
    • >  Maximise  iden(fica(on  points    160%  140%  120%  100%   80%   60%   −−−  Probability  of  iden1fica1on  through  Cookies   40%   20%   0   4   8   12   16   20   24   28   32   36   40   44   48   Weeks  December  2011   ©  Datalicious  Pty  Ltd   49  
    • >  Developing  a  tes(ng  matrix   Test   Segment   Content   Success   Difficulty   Poten(al   New   Acquisi(on   Clicks,     Test  #1A     prospects   offer  A   orders,  etc   Low   $50k   New   Acquisi(on   Clicks,     Test  #1B   prospects   offer  B   orders,  etc   Exis(ng   Up-­‐sell   Clicks,     Test  #2A   customers   offer  A   orders,  etc   High   $75k   Exis(ng   Up-­‐sell   Clicks,     Test  #2B   customers   offer  B   orders,  etc  December  2011   ©  Datalicious  Pty  Ltd   50  
    • >  The  holy  trinity  of  tes(ng  1.  The  headline   –  Have  a  headline!   –  Headline  should  be  concrete   –  Headline  should  be  first  thing  visitors  look  at  2.  Call  to  ac(on   –  Don’t  have  too  many  calls  to  ac1on   –  Have  an  ac1onable  call  to  ac1on   –  Have  a  big,  prominent,  visible  call  to  ac1on  3.  Social  proof   –  Logos,  number  of  users,  tes1monials,     case  studies,  media  coverage,  etc  December  2011   ©  Datalicious  Pty  Ltd   51  
    • >  Best  prac(ce  tes(ng  roadmap  §  Phase  #1:  A/B  test   –  Test  the  same  landing   Element  #1:  Prominent  headline   page  content  in   completely  different   layouts  §  Phase  #2:  MV  test   Suppor1ng     Element  #2:     –  Then  test  different   content   Call  to  ac1on   content  element   combina1ons  within  the   winning  layout   Element  #3:  Social  proof  /  trust  §  Phase  #3:  Challenge   –  Con1nue  tes1ng  and   introducing  layout  and   Terms  and  condi1ons   content  challengers  December  2011   ©  Datalicious  Pty  Ltd   52  
    • >  Use  unique  phone  numbers   2  out  of  3  callers   hang  up  as  they   cannot  get  their     informa1on  fast   enough.     Unique  phone   numbers  can   help  improve   call  experience.  December  2011   ©  Datalicious  Pty  Ltd   53  
    • December  2011   ©  Datalicious  Pty  Ltd   54  
    • Contact  me   cbartens@datalicious.com     Learn  more   blog.datalicious.com     Follow  me   twi<er.com/datalicious    December  2011   ©  Datalicious  Pty  Ltd   55  
    • Data  >  Insights  >  Ac(on  December  2011   ©  Datalicious  Pty  Ltd   56