Why digital analytics?

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Why digital analytics?

  1. 1. WHY  DIGITAL  ANALYTICS? Raymond  Chau   Nov  2013 1
  2. 2. About  me • Building  web  site  for  10  years   • Working  in  isobar,  a  full  serviced  digital  agency  around  the  globe   • My  blog:  http://www.whymeasurethat.com 2
  3. 3. WHAT  IS  DIGITAL  ANALYTICS? 3
  4. 4. What  is  digital  analytics? “Collect  and  use  data  to  make  things  better” 4
  5. 5. How  do  we  collect  data? Data PRIVATE  Data logs   tracking   (e.g.  server  logs) (e.g.  Google  Analytics) survey   (e.g.  iPerception) PUBLIC  Data free   (e.g.  Google  Trends,  forums) paid   (e.g.  Hitwise,  Compete) 5
  6. 6. Example:  Google  Analytics Free  tool  offered  by  Google  to  monitor   user  activities  on  their  web  sites  or   mobile  apps 6
  7. 7. Example:  Facebook  Insight Allows  developers  and  Page  owners   to  see  how  their  app  /  page  perform 7
  8. 8. Example:  Google  Trends Public  available  data  that  allows  user  to  see  how  a   particular  search-­‐term  performs  over  a  time  period   on  different  regions 8
  9. 9. Example:  TripAdvisor Forum  is  one  of  the  best  (and  mostly  free)  source   of  qualitative  data  from  your  customers!  See  how   honest  are  they!! 9
  10. 10. WHAT  CAN  DIGITAL  ANALYTICS  DO? 10
  11. 11. Improve  advertising  spending  effectiveness ROI  can  be  calculated  and  see  which   channel  is  more  effective 11
  12. 12. Fix  the  entrance  of  the  site 75%  of  visitors  immediately  leave  the  site   after  seeing  the  page.  What’s  wrong? 12
  13. 13. Optimize  check  out  process Only  36%  people  checkout  after   adding  things  to  cart,  what’s   wrong? Where  do  people  go  if  they  quit   from  billing  page?  Are  they  looking   for  shipping  details? 13
  14. 14. Experimenting  (A/B  Testing) 14
  15. 15. Personalisation   • Movie:  Minority  Report  (2002) 15
  16. 16. Personalisation 
 e.g.  email  marketing  using  user  behaviour  data   16
  17. 17. Personalisation e.g.  recommendations  based  on  purchase  history  data 17
  18. 18. Personalisation e.g.  advertisement  based  on  facial  expression  data
 http://www.cenique.com/cenique/advertising_Platform.php 18
  19. 19. Recommendations Provide  recommendations  using  crowd-­‐sourced  data  (e.g.  Netflix,  Amazon) 19
  20. 20. Re-­‐marketing  /  re-­‐targeting 4.  visitor  goes  back  to   your  site  because  of  the   promo,  and  may  possibly   purchase 3.  visitor  goes  to  a  popular   site,  promotional  ad   targeted  to  the  product   the  visitor  just  read  is   displayed 1.  visitor  enters  your  site 2.  visitor  doesn’t  buy   anything  and  leaves,  but  you   know  he  has  seen  a   particular  product  and  put  it   into  the  cart 20
  21. 21. TRADITIONAL  MARKETING  V.S.  DIGITAL  MARKETING 21
  22. 22. Measurability Traditional   Digital   • Very  difficult  to  measure   • Can  be  very  expensive  to  measure   • Cannot  measure  how  viewers  engage   with  the  content • Very  easy  to  measure     • Almost  free  to  measure   • Can  measure  how  viewers  engage  or  even   interact  with  the  content ! ! 22
  23. 23. Message  Delivery Traditional   Digital   • Message  deliver  to  as  many  audiences   as  possible   • Have  no  knowledge  on  audiences   • Less  likely  to  respond • Message  deliver  only  to  your  target  audiences   • Know  who  the  audiences  exactly  are   • More  likely  to  respond  as  the  message  is   relevant   ! ! 23
  24. 24. Example:  Non-­‐target  ad  v.s.  target  ad Non-­‐target  Ad  -­‐  TV     Target  Ad  -­‐  Facebook   • Can’t  target  audiences  that  are  really   relevant  to  your  product   • For  example,  you  can’t  target  those   who  really  have  acne  problems   • Can  target  visitors  in  finest  level     • For  example,  you  can  target  based  on   country,  city,  gender,  age  range,  interests,   etc ! ! 24
  25. 25. Speed Traditional   Digital   • Data  takes  time  to  collect  and  analyse   • Cannot  respond  to  audience   immediately     • Marketers  spend  longer  time  +  more   money  to  get  insights  and  adapt • Data  are  collected  or  even  processed  at   real  time       • Can  respond  and  give  tailored  response   to  audience  real  time   • Allows  marketers  to  fail  cheap  and  fast ! ! 25
  26. 26. LATEST  TOPIC  ON  DIGITAL  ANALYTICS 26
  27. 27. BIG  DATA!!! Abacus
 (old  method) Calculator   (new  method) Calculation Excel
 (old  method) Big  Data
 (new  method) Data  Storage  &   Analysis 27
  28. 28. We’re  generating  more  and  more  data • Example:  facebook   • 699  million  people  login  Facebook  daily   • 300  million  photos  are  uploaded  daily   • Every  60  seconds   • 510  comments  are  posted   • 293,000  statuses  are  updated   • 136,000  photos  are  uploaded 28
  29. 29. Example:  Obama  2012  election  campaign • Collect  1  database  that  factors  80  pieces  of  information  about  voters:  
 (e.g.  age,  race,  sex  and  even  voting  history)   • Target  right  audience:  focus  on  voters  who  might  change  their  mind  based  on  voters’  ‘persuasive   score’   • Personalisation:  deliver  policy  messages  or  fund  raising  event  tailored  for  individual  voters 29
  30. 30. Example:  Disneyland 1.  Opt-­‐in  for  a  wireless   tracking  bracelet   ‘MagicBand’  which   links  to  the  system  My   Magic+ 3.  Mickey  Mouse  now   knows  a  lot  about  YOU!!! 2.  Visitors’  real  time   location,  riding  patterns  &   purchases  are  all  recorded 30
  31. 31. SUMMARY 31
  32. 32. Data:  to  use  or  not  to  use? TARGET  ad  reveals  teen’s  pregnancy   http://bit.ly/1b3u5k5   32
  33. 33. Want  to  know  more? Google  +  page   +RaymondChau facebook  fan  page
 WhyMeasureThat ME LinkedIn   linkedin.com/in/raymondchau blog   www.whymeasurethat.com   twitter   @raymondchau 33
  34. 34. THANK  YOU! 34

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