Analytics cultures in Europe (Web Analytics Congress de Utrecht 13-14 marzo 2013)


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Presentación en inglés de Aurélie Pols en el Web Analytics Congress celebrado en Utrecht el 13-14 de marzo de 2013.

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Analytics cultures in Europe (Web Analytics Congress de Utrecht 13-14 marzo 2013)

  1. 1. Analytics cultures in EuropeMarch 2013 – Web Analytics Congres – Aurélie Pols
  2. 2. Who am I? @aureliepols
  3. 3. Women’s  dayBecause women always analyze everything,we know how to optimize (our time & work!)
  4. 4. ¿Mind Your Group? Empresas de nicho volcadas en ayudar a sacar el máximo partido al canal online
  5. 5. Sponsored  by  
  6. 6. Data-informed vs. data-driven
  7. 7. STAGES  OF  ANALYTICAL  COMPETITION   Use  Internal  +   StaGsGcal  Analysis  &   External  Data   Analy4c   PredicGve  Modeling   Compe4tors   High  Quality  Data  /   Company  Wide  Culture   Analy4c  Companies   Not  CompeGng   Have  BI  Tools   Isolated   No  Easy  Access   Analy4c  Aspira4ons   FuncGons   Mostly  ReporGng   Business   Localized  Analy4cs   as  Usual  Poor  Quality  /   Missing  Data   Analy4cally  Impaired   Lack  Skill  
  8. 8. Modelo de madurez en Analítica Digital Basado  en  el  modelo  de  madurez  de  analí/ca  web  de  Stéphane  Hamel  
  9. 9. Un plan estratégico Diseño  de  Scorecards   Analí4ca  Prescrip4va   12 Elaboración  Plan  Estratégico   meses Integración  datos  offline   Iden4ficación  de  Oportunidades   Analí4ca  Predic4va   9 Análisis  Ciclo  de  Vida  del  Cliente   meses 6 Desarrollo  Dashboards  Automa4zados   Personalización  Contenido   Generación  Modelos  Estadís4cos   Perfiles  y  Modelos  de  Personas   meses 3 E4quetado  de  Campañas   Creación  Embudos  Conversión   infraestructura   Análisis  UX   Análisis  Arquitectura  Información   Preparación  Test  A/B   Estudio  de  la  competencia   Análisis  Cualita4vo   meses Implementación  Básica  Herramienta   Personalización  Herramienta   Ges4ón  de  Calidad  de  los  Datos  tác4ca   Análisis  del  Tráfico   Análisis  Conversión   1 Establecimiento  de  Obje4vos   Generación  KPIs   Definición  Segmentos  de  Negocio   mes estrategia  
  10. 10. The key to success, not newTechnology   People   Process  
  11. 11. 7 steps for beautiful DDDM# 7  Go  for  the  boOom-­‐line  (outcomes)  # 6  ReporGng  is  not  analysis  # 5  Depersonalize  decision  making  # 4  ProacGve,  not  reacGve  insights  # 3  Empower  your  analysts  # 2  Solve  for  the  Trinity  # 1  Got  Process?   Avinash Kaushik
  12. 12. # 7 Bottom-line Product  innovaGon   PRICE   STRATEGIES   Product  Quality   DifferenGated  MarkeGng   MARGIN   Process  InnovaGon   COST   STRATEGIES   FuncGonal  Efficiencies   DiscreGonary  spending  NET  INCOME   IntegraGon   MARKET  SHARE   STRTEGIES   MarkeGng  SegmentaGon   Customer  Value  Chain   RelaGve  Spending/Effort   VOLUME   MARKET  SIZE   STRATEGIES   “Related”  New  Products   “Related”  New  Markets   More  usage  occasions  
  13. 13. # 6 Analysis, not Reporting Comparing Roles Analytics Analytics Consultant PractitionerJune Dershewitz 1.  A  pracGGoner  has  an  open-­‐ended  statement  of  work   2.  What’s  the  hold-­‐up?   3.  MeeGngs  upon  meeGngs  upon  meeGngs   4.  Longer  projects,  lasGng  impact   5.  Fear  of  losing  touch   6.  From  center  of  the  universe  to  subject  maOer   7.  The  role  of  the  consultant  is  to  make  the  client  look  good  
  14. 14. Outsource the boring stuff! 20%   How  does   your  day   look  like?  Source:  The  Next-­‐Genera4on  Privacy  Professional  -­‐  IAPP  
  15. 15. WEB  ANALYTICS  2.0   Tráfico  y   1.  Qué   Conversión   Datos  Offline   2.  Cuánto   TesGng   3.  Por  Qué   Voz  Cliente   CompeGdores   4.  Qué  más   Insights  
  17. 17. Statement  #1:    Companies  &  sectors  are  not  equal  
  18. 18. 2005: Google Analytics = free “Staffing for a free product is an issue in Germany”  Oliver Schiffers Matt Cutler Jason Burby
  19. 19. Google Analytics market share Source: en/blog/203-infographic-ireland-who-is- using-google-analytics.html
  20. 20. Europe’s economic fiber: SMEs
  21. 21. Europe’s economic fiber: SMEs kroes/coalition-digital-jobs/
  22. 22. In 2007…and still today     Action vs. findings     “What is the most difficult aspect of analytics for your company?” Pulling together the data 24% Forming the hypothesis 9% Developing the analytical models 12% Interpreting the results 3% Acting on the findings 53% Source: Forrester Research
  23. 23. Cruise ship vs. speed boat
  24. 24. Statement  #2:    Job  descrip4ons  are  not  always  what  they  seem  
  25. 25. Analytics rockstar What are you willing to sacrifice? to outsource?  
  26. 26. Long term vision Dylan Lewis Wonder about data, analytics & Hadoop? Read this: Page
  27. 27. Life stages
  28. 28. Journey companion
  29. 29. Consultancy or company? Outsourcing or near sourcing?  
  30. 30. The Spanish ConnectionBe demanding: evolve or change!
  31. 31. Statement  #3:    There  is  no  truth,    only  points  of  views  
  32. 32. Is attribution dead?Distribuciónde fuentesDe tráfico
  33. 33. From web analytics to digitalSource:  hOp://­‐to-­‐build-­‐a-­‐beOer-­‐inbound-­‐markeGng-­‐machine    
  34. 34. How can you… Reach  more   people,   more   efficiently,   at  lower   costs?  
  35. 35. Specializations#CRO#UX, #LEANUX#SEM, #SEO#MEASURE#ANALITICAWEB#MOBILE#RWD…#AUDIT#PRIVACY uploads/2013/01/weboptimeez-analytics- roadmap-2013.jpg
  36. 36. Los datos son el nuevo oro negroPage    43  
  37. 37. Our Blood Type is Data +
  38. 38. What did we learn today?# Best  prac4ces  exist  about  data   driven/informed  cultures  # Despite  differences,  pockets  of   excellence  also  exist  # Create  win-­‐win  situaGon  for  you   and  your  company  # If  not,  move  on:  in  the  Netherlands,   in  Europe  or  in  the  world  
  39. 39. Don’t Crash & Burn! Informed Uninformed 2 Pessimism Optimism 1 5 Informed Optimism Crisis of 3 Meaning 4 Crash & BurnTransition Curve
  40. 40. Ask yourself this Where  do  YOU   want  to  be   In whichcountry/region? in  10  years?   Loner or part of a team? Life balance: Doing what? Expert or Professional Responsible generalist? vs. Private for what?
  41. 41. El futuro pertenecerá a los que realmente hagan buenas preguntas Gracias   Aurélie Pols@aureliepols