Digital Data Tips Tuesday #1 - Tag Management: Tomas Salfischberger - Relay42

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#ddtt #1 Keynote by Tomas Salfischberger - the future of tag management - your data layer

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Digital Data Tips Tuesday #1 - Tag Management: Tomas Salfischberger - Relay42

  1. 1. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   1   Tag  Management:   The  Next  Steps   Why  Tag   Management?   site-­‐speed   markeEng   velocity   independence  
  2. 2. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   2   What  are  the   possibili9es?  manage  tags   assure   data-­‐quality   cookie   consent   The  Swiss  Knife  of   your  website   •  Manage  tags  (of  course)   •  Collect  Data   •  OpEmize   •  Personalize  
  3. 3. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   3   A/B-­‐tests  with  Tag   Management   •  Simple  A/B-­‐tests   •  Analyze  in  web-­‐analyEcs   •  Tests  based  on  random  groups   Missing  link?   Data!   •  Collect  data  through  the  TMS   •  Use  data  instead  of  staEc  content   (e.g.  “last  booked  10  seconds  ago”)   •  OpEmize  the  site  for  a  general  audience  
  4. 4. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   4   Case:   Vrij  Uit   •  Collect  booking  data   •  Display  persuasion  elements   •  Conversion  rate:  up  by  7%   Personaliza9on   Through  TMS   •  Next  step  aZer  opEmizaEon   •  Visitor  segmentaEon   •  Machine  learning  to  determine  the   right  content  for  each  visitor   (e.g.  “This  fits  your  taste”)  
  5. 5. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   5   Case:   Neckermann   •  Calculate  personalized   recommendaEons   •  Use  current  context  (product)  +   user  profile  (history)   Case:   CRM  Data  Sync   - Online behavior data - User identifiers - Owned products - Customer status Profile Time   Anonymous Visitor Identification (e.g. email link) CRM   System   +   Prospect   Message   Customer   Specific  
  6. 6. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   6   Case:   Offline  Data   Profile •  Views & Recommendations •  Channels used •  Feedback by agent Time   Visitor Online behavior data •  Personalized  recommendaEons   •  Combined  with  dynamic   opEmizaEon  elements   •  12%  increased  conversion  rate   Case:   Thomas  Cook  
  7. 7. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   7   Behind  The   Scences   Tag  Management   Data  Pla^orm   website   Raw   Data   Learning  Algorithms  IntegraEon  Center   User   Profiles   Others   Back-­‐end   Systems  
  8. 8. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   8   The  future  of   Tag  Management   •  A  Tag  Management  System  is   much  more  than  a  simple   container  for  tags   •  Valuable  data  can  be  at  your   fingerEps   •  Dynamic  opEmizaEon  and   personalizaEon  are  the  next   A/B-­‐tesEng   Key  takeaways   •  The  Tag  Management  System    is   a  mulE-­‐tool  for  the  website   •  TMS  performance  is  essenEal  for   personalizaEon   •  Work  towards  a  direct   integraEon  between  tags  and   data  
  9. 9. Tomas  Salfischberger  -­‐  #DDTT  Tag   Management   May  6th  2014   Digital  Data  Tips  Tuesday  -­‐  Amsterdam   hAp://digitaldata.Eps   9  

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