R'dam rsm - 20130314

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R'dam rsm - 20130314

  1. 1. Have  you  no*ced  this  ad  for  …  
  2. 2. …or  did  you  arrive  at  this  search-­‐page  without  having  ever  seen  the  ad?  
  3. 3. A  few  clicks  later  you  have  arrived  here  to  choose  what  to  buy,  where  and  at  what  price.  
  4. 4. But  the  day  a@er  you  are  surprised  by  a  similar  newspaper-­‐ad  of  another  brand.  How  confusing.  
  5. 5. But  confused  consumers  …  compare.    (Aren’t  we  all  confused  consumers?)  
  6. 6. Brands  themselves  confuse  consumers.   Deliberately.  http://bit.ly/ZBFHFK
  7. 7. That’s  how  they  do  it.  
  8. 8. Eventually  you  ask  some  car  lover-­‐friends  which  used  car  you  should  buy.  Aston  Mar*n  or  BMW.  
  9. 9. That’s  the  social  consumer:  he/she  buys  a  lot  -­‐  not  only  cars  -­‐  based  on  recommenda*ons.  
  10. 10. What’s  the  problem  with  adver*sing?  “Why  now?  You  interrupt  my  ac4vi4es”    “Not  for  me.  I  just  bought  my  stuff”  “Too  many  ads.  I  avoid  them”  “So  stupid”.  “Nice  ad,  but  so  what?  Not  relevant  for  me.”  “Haven’t  even  seen  it.”  “I  don’t  care.  Will  search  when  I  need  something.”  “Don’t  trust  it.  Nothing  but  lies.  I’ll  ask  my  friends  or  colleagues”  
  11. 11. Ad agency Ads Media you you youBrand
  12. 12. “We  are  not  the  customers  of  Facebook,  we  are  the  product.  Facebook  is  selling  us  to  adver*sers.”   Douglas Rushkoff Your data
  13. 13. Reviews  do  the  job!  
  14. 14. Yelp  (2008-­‐2012)  s*ll  loses  money.  
  15. 15. About  70%  of  Yelp’s  revenue  is  from  ads  (!!!)  by  local  businesses  listed  on  its  site.    
  16. 16. Prof.  Dr.  Gerard  Tellis  1980-­‐1990:Adver,sing  +10%  =  +2.2%  marketshare  2008:Adver,sing  +20%  =  +2.2%  marketshare   “  ….  the  authors  conduct  a  meta-­‐analysis  of  751  short-­‐term  and  402  long-­‐term   direct-­‐to-­‐consumer  brand  adver4sing  elas4ci4es  es4mated  in  56   studies  published  between  1960  and  2008.  the  study  finds  several  new   empirical  generaliza4ons  about  adver4sing  elas4city.  the  most  important   are  as  follows:  the  average  short-­‐term  adver4sing  elas4city  is  .12,  which   is  substan4ally  lower  than  the  prior  meta-­‐analy4c  mean  of  .22;  there  has  been  a   decline  in  the  adver4sing  elas4city  over  4me.”   Gerard  Tellis,  PhD  Michigan,  is  Professor  of  Marke,ng,  Management,  and  Organiza,on,  Neely  Chair  of  American  Enterprise,  and  Director  of   the  Center  for  Global  Innova,on,  at  the  USC  Marshall  School  of  Business.  He  is  Dis,nguished  Visitor  of  Marke,ng  Research,  Erasmus   University,  RoUerdam  and  has  been  Visi,ng  Chair  of  Marke,ng,  Strategy,  and  Innova,on  at  the  Judge  Business  School,  Cambridge  University,   UK.  Tellis  specializes  in  the  areas  of  innova,on,  adver,sing,  global  strategy,  market  entry,  new  product  growth,  promo,on,  and  pricing.  
  17. 17. One  of  many  brands’  issues:  “Adver*sing  is  too  expensive.  Grows  faster  than  the  economy!”     YOY-growth +7% +3,8% +3,8% +4,6% +5,2%
  18. 18. Recommenders  directly  influence  20-­‐50%  of  all  purchase  decisions.  
  19. 19. Offline!  Thé  method  of  recommenda*on.  
  20. 20. The  mo*ves  of  recommenders?  
  21. 21. Why  do  you  recommend?  And  why  not?  
  22. 22. The  difference  between  a  “recommended”  beer  and  a  marke*ng  beer.     http://www.ratebeer.com/
  23. 23. The  difference  in  family  fortune  between  a  “recommended”  beer  and  a  marke*ng  beer.     $11 billion € 270 million
  24. 24. “Friends  &  family”  -­‐  recommenda*ons  lead.  
  25. 25. “Friends  &  family”  are  the  trusted  source.  Adver*sing  …?  
  26. 26. Some  buy  a  lot  online  and  tell  it  to  a  lot  of  people  online  too.  
  27. 27. Who’s  influencing?    Is  all  that  buzzing  trustworthy?   “…  while  consumer  electronics  buyers  pay  more   aZen4on  to  other  consumers’  reviews  than  to   editorial  reviews  –  by  a  margin  of  more  than  three   to  one  (77  percent  vs.  23  percent)  –  a  majority  are   concerned  about  the  authen4city  of  consumer   reviews  (80  percent),  leading  them  to  conduct   considerable  analysis  before  making  their  decision.”  
  28. 28. POE:  Paid.  Owned.  Earned.  
  29. 29. Recommenda*on  measurement  started  with  Reichheld  in  2003  
  30. 30. Not  only  we  ask  clients  whether  they  will/will  not  recommend  a  brand…   8   8 8   NPS  
  31. 31. We  ask  non-­‐clients  too.  They  too  judge,  talk  and  influence.  That’s  why  we  ask  them.   NPS  
  32. 32. The  actual  Holaba  B2B-­‐dashboard  in  China  Net Promoter Score= % promoters (9-10) minus % detractors (0-6)among clients.Holaba Score = % promoters (9-10) minus % detractors (0-6) among recommenders
  33. 33. From  RFM  to  RRFM  to   decide  about  what  to  Recency,  frequency,  monetary  value  (RFM)  of   invest  where.  clients  are  decisive  for  investment  in   RFM  -­‐  axis  marke,ng  communica,on.  Therefore  lots  of  money  spent  (wasted)  in  this  group  of  heavy  and  recent  buyers    Light  and  non  frequent  buyers  are  o_en  “neglected”    
  34. 34. The  recommenda*on   power  of  clients   becomes  the  decisive   tool  to  decide  on   marcom-­‐investments   RFM  -­‐  axis   Does  not  mean  they  all  give  posi4ve  +RFM  &  -­‐  REC   +RFM  &  +  REC   recommenda4ons   Recommenda7on  axis   Frequency  and  intensity  of   recommenda*on.   -­‐  RFM  &  +  REC  -­‐  RFM  &  -­‐  REC  
  35. 35. To  influence  these  influencers,  iden*fy  them.  Con*nuously.    Everywhere.  
  36. 36. Jan  Van  den  Bergh  杨⽂文博  jevedebe@gmail.com  hFps://www.facebook.com/jevedebe  hFps://www.facebook.com/holaba  TwiFer:@holaba    Skype:jevedebechina  +86  136  2179  9450  (CH)  +32    475  427  882  (BEL)  A  :  上海市新闸路831号丽都新贵13层F室,  200041  13-F,  No  831  Xin  Zha  Road,  Shanghai,  200041  

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