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 HOW	
  MEDIA	
  WILL	
  EVOLVE:	
  
  SEX,	
  DATA	
  AND	
  MEMES	
  
We	
  asked	
  ourselves	
  a	
  holy-­‐grail	
  ques<on:	
  
How	
  can	
  adver<sing	
  	
  
stop	
  being	
  invasive	
  
 announcements…	
  
…	
  and	
  evolve	
  into	
  	
  
meaningful	
  conversa<ons?	
  
AIerall,	
  
conversa<ons	
  have	
  
the	
  same	
  ingredient	
  
   that	
  makes	
  the	
  
  internet	
  unique:	
  	
  
     Interac<vity.	
  
Newsflash:	
  Tradi<onal	
  Media	
  lacks	
  interac<vity.	
  	
  
20th	
  century	
  rules	
  don’t	
  apply	
  to	
  21st	
  century	
  media.	
  
Now,	
  new	
  adver<sing	
  models	
  are	
  possible:	
  
 smartphones	
  +	
  social	
  media	
  hold	
  the	
  key	
  
  for	
  meaningful	
  interac<ve	
  adver<sing.	
  
FIRST,	
  MARKET	
  FUNDAMENTALS:	
  
GET	
  READY	
  FOR	
  SMART	
  &	
  SOCIAL	
  MOBILE.	
  
Grupo 42 - Sex, Data and Memes
#MEMES	
  
#MEMES	
  
Brazil	
  has	
  55	
  million	
  
smartphones,	
  20%	
  of	
  
         mobile	
  park.	
  
It’s	
  expected	
  to	
  reach	
  	
  
 130	
  million	
  by	
  2015.	
  
             Source:	
  
Argen<na	
  has	
  11	
  million	
  
 smartphones,	
  19%	
  of	
  
          mobile	
  park.	
  
 It’s	
  expected	
  to	
  reach	
  	
  
   35	
  million	
  by	
  2015.	
  
               Source:	
  
#MEMES	
  
#MEMES	
  
But	
  now,	
  Social	
  Media	
  
became	
  the	
  Killer	
  App	
  	
  
  of	
  smartphones.	
  




                                  #MEMES	
  
But	
  now,	
  Social	
  Media	
  
became	
  the	
  Killer	
  App	
  	
  
  of	
  smartphones.	
  
                         	
  
    (Killer	
  App:	
  what	
  Mario	
  Bros	
  	
  
        did	
  for	
  the	
  Game	
  Boy)	
  




                                                       #MEMES	
  
“Two	
  birds	
  with	
  one	
  stone”	
  
                                      #MEMES	
  
#MEMES	
  
#MEMES	
  
SOCIAL	
  &	
  MOBILE	
  BRANDING:	
  
  REALITY	
  IS	
  THE	
  NEW	
  AD	
  
Then,	
  don’t	
  focus	
  
  on	
  the	
  ends…	
  
…focus	
  on	
  the	
  #MEMES	
  
“A	
  meme	
  is	
  a	
  unit	
  of	
  
      human	
  cultural	
  	
  
evolu<on	
  analogous	
  to	
  the	
  
                gene	
  (…)	
  
   It’s	
  a	
  message	
  that’s	
  
  contagious	
  in	
  the	
  same	
  
  way	
  a	
  gene<c	
  virus	
  is.”	
  
                       	
  
             Sir	
  Richard	
  Dawkins,	
  1975	
  
Example:	
  Trending	
  Topics	
  are	
  
#memes	
  that	
  reached	
  <pping	
  point.	
  
Memes	
  have	
  Epidemic	
  Behaviours	
  like	
  genes	
  do.	
  
Memes	
  spread	
  like	
  viruses:	
  the	
  nodes	
  with	
  
more	
  connec<ons	
  –users	
  with	
  more	
  influence–	
  
         are	
  the	
  main	
  agents	
  of	
  a	
  message.	
  
Tradi<onal	
  Media	
  has	
  a	
  
 “one	
  to	
  many”	
  model.	
  	
  
Interrup?on	
  Adver?sing	
  	
  
  was	
  their	
  game:	
  “we	
  
    talk,	
  you	
  listen.”	
  
Gen	
  Y	
  does	
  not	
  want	
  to	
  
      be	
  Interrupted	
  
 anymore.	
  They	
  have	
  	
  
mul<-­‐tasking	
  afen<on.	
  
Social	
  Media	
  is	
  the	
  first	
  
 “many	
  to	
  many”	
  kind	
  
of	
  media.	
  Everyone	
  has	
  
  their	
  share	
  of	
  voice.	
  
And	
  it’s	
  good	
  listeners	
  	
  
what	
  make	
  a	
  Conversa?on.	
  	
  
Being	
  compe<<ve,	
  means	
  
 detec<ng	
  memes	
  in	
  real-­‐
    <me	
  and	
  act	
  fast.	
  
#SusanGlenn	
  Axe	
  Campaign:	
  Memes	
  +	
  TV	
  
Meme<cs	
  is	
  about	
  Disrup?ve	
  Adver?sing	
  
Interrup<on	
  models	
  need	
  you	
  to	
  pay	
  
afen<on,	
  you	
  must	
  adapt	
  to	
  the	
  content…	
  
…while	
  disrup<on	
  models	
  aim	
  to	
  hack	
  your	
  
  afen<on,	
  the	
  content	
  adapts	
  to	
  you.	
  
HOW	
  WE	
  DO	
  IT?	
  
SOCIAL	
  MEDIA	
  DATA	
  MINING	
  
The	
  average	
  person	
  
 today	
  processes	
  more	
  
data	
  in	
  a	
  single	
  day	
  than	
  
 a	
  person	
  in	
  the	
  1950’s	
  
      did	
  in	
  its	
  life<me.	
  	
  
Data	
  Mining	
  is	
  applying	
  
computer	
  algorithms	
  to	
  
  detect	
  meaningful	
  
        behaviours.	
  	
  
Zenzey	
  finds	
  the	
  memes	
  that	
  mafer.	
  
Filter	
  social	
  media	
  streams	
  with	
  Keywords	
  and	
  Demographics	
  
Explore	
  conversa<on	
  Insights	
  and	
  iden<fy	
  key	
  memes.	
  
Trigger	
  automated	
  ac<ons	
  to	
  enhance	
  Conversa<ons.	
  
Measure	
  every	
  single	
  aspect	
  of	
  each	
  Campaign	
  
Iden<fy	
  the	
  real	
  Key	
  Opinion	
  Formers.	
  
CASE	
  A:	
  
MEME	
  MARKETING	
  
We	
  detected	
  in	
  Real-­‐Time	
  
conversa<ons	
  in	
  Twifer	
  from	
  
  women	
  about	
  their	
  hair,	
  
 fashion	
  and	
  related	
  topics.	
  
We	
  get	
  over	
  60.000	
  relevant	
  conversa<on	
  	
  
 opportuni<es	
  per	
  month	
  in	
  Argen<na.	
  
Our	
  Agent	
  Accounts	
  tweet	
  about	
  fashion	
  and	
  hairstyling,	
  
and	
  reply	
  to	
  tweets	
  that	
  meet	
  Sedal’s	
  criteria	
  on	
  Zenzey.	
  
93%	
  of	
  the	
  replies	
  to	
  our	
  Agents	
  are	
  posi<ve	
  or	
  neutral.	
  
             35%	
  of	
  the	
  tweets	
  with	
  links,	
  get	
  clicked.	
  
And	
  we	
  get	
  Insights	
  revealing	
  the	
  keys	
  to	
  drive	
  the	
  
conversa<on.	
  For	
  Afro	
  and	
  Curly	
  Hair,	
  it	
  was	
  #Rock	
  
So	
  we	
  generate	
  content	
  accordingly,	
  even	
  working	
  with	
  
       the	
  Key	
  Opinion	
  Formers	
  that	
  Zenzey	
  detected.	
  
The	
  quan<ty	
  of	
  users	
  sent	
  by	
  Zenzey	
  to	
  Sedal’s	
  blog	
  
  averaged	
  the	
  same	
  number	
  than	
  other	
  sources.	
  
Users	
  that	
  visited	
  the	
  Sedal	
  Blog	
  detected	
  by	
  Zenzey	
  on	
  
    Twifer	
  spent	
  4X	
  more	
  <me	
  with	
  the	
  content.	
  
CASE	
  B:	
  
MARKET	
  RESEARCH	
  DATA	
  MINING	
  
For	
  a	
  new	
  fragance,	
  they	
  asked	
  
  us:	
  How	
  are	
  people	
  talking	
  
 about	
  love	
  around	
  the	
  globe?	
  
Zenzey	
  processed	
  over	
  	
  
 1	
  Million	
  tweets	
  with	
  public	
  
displays	
  of	
  love,	
  from	
  the	
  UK,	
  
  USA,	
  Brazil	
  and	
  Argen<na.	
  
In	
  1	
  month,	
  we	
  delivered	
  over	
  
           125	
  different	
  insights.	
  
Including	
  key	
  movies,	
  tv	
  series,	
  
  songs,	
  and	
  of	
  course	
  #memes	
  
             for	
  every	
  market.	
  
TEXTING	
  on	
  their	
  daily	
  rou4ne	
  
   It´s	
  extremely	
  important	
  to	
  receive	
  a	
  text	
  message	
  before	
  sending	
  it	
  to	
  the	
  
   other	
  person.	
  The	
  wow	
  factor	
  is	
  very	
  effec4ve.	
  	
  
   Text	
  messages	
  are	
  an	
  essen4al	
  part	
  of	
  a	
  couple	
  daily	
  rou4ne.	
  They	
  need	
  to	
  
   receive	
  “good	
  night”	
  and	
  “good	
  morning”,	
  otherwise	
  they	
  will	
  feel	
  sad.	
  


                                                                             "That	
  amazing	
  feeling	
  
                                                                             when	
  your	
  crush	
  texts	
  
                                                                                      you	
  first"	
  	
  



                                                                                "I	
  get	
  NO	
  good	
  
                                                                              morning/night	
  calls/
                                                                                        texts"	
  

Insight	
  Example	
  #1	
  
#WHEN	
  as	
  a	
  descrip4ve	
  vehicle:	
  
When	
  girls	
  start	
  their	
  tweets	
  using	
  the	
  hashtag	
  #When	
  it	
  means	
  that	
  they	
  are	
  about	
  to	
  describe	
  a	
  
specific	
  and	
  unique	
  moment	
  that	
  makes	
  them	
  feel	
  happy.	
  It´s	
  a	
  great	
  vehicle	
  to	
  understand,	
  
promote	
  or	
  just	
  iden4fy	
  “Romance”	
  moments.	
  




 "When	
  they	
  shut	
  you	
  
  up	
  by	
  kissing	
  you"	
  



  "When	
  you	
  take	
  forever	
  to	
  
   say	
  goodnight	
  cause	
  you	
  
  don't	
  want	
  to	
  stop	
  talking	
  
           to	
  each	
  other"	
  

                                                                                                      Insight	
  Example	
  #2	
  
The	
  First	
  Time:	
  
They	
  refer	
  to	
  First	
  Time	
  in	
  two	
  ways:	
  
-­‐	
  Like	
  a	
  nice	
  memory:	
  LOVE	
  AT	
  FIRST	
  SIGHT	
  is	
  a	
  common	
  topic	
  among	
  girls.	
  They	
  mainly	
  talk	
  about	
  
first	
  kisses,	
  first	
  4me	
  they	
  met	
  their	
  boyfriends,	
  first	
  4me	
  they	
  saw	
  a	
  boy,	
  etc.	
  
-­‐	
  Like	
  a	
  sexy	
  experience:	
  “Kiss	
  me	
  like	
  I	
  was	
  your	
  first	
  4me”.	
  


  "#MeFirstKiss	
  was	
  in	
  the	
  snow.	
  He	
  was	
  
   walking	
  me	
  home	
  at	
  night	
  and	
  spun	
  
   me	
  around	
  and	
  kissed	
  me.	
  It	
  was	
  by	
  
     far	
  the	
  most	
  roman4c	
  first	
  kiss"	
  
                             	
  




     "I	
  never	
  believed	
  in	
  
      love	
  at	
  first	
  sight…	
  
     un4l	
  I	
  first	
  saw	
  you”	
  

                                                                                                         Insight	
  Example	
  #3	
  
Love	
  &	
  Rain	
  
Rain	
  seems	
  to	
  make	
  everything	
  more	
  roman4c.	
  Also,	
  being	
  tucked	
  in	
  bed	
  when	
  
it’s	
  raining	
  seems	
  to	
  be	
  a	
  generalized	
  sense	
  of	
  well	
  being.	
  


     #ThingsThatILove	
  the	
  sound	
  of	
  
       rain	
  piger-­‐pahng	
  on	
  your	
  
        window	
  when	
  you're	
  all	
  
           snuggled	
  up	
  in	
  bed	
  	
  




      Boy:	
  "Make	
  me	
  food."	
  Girl:	
  
      "Be	
  more	
  roman4c.”	
  Boy:	
  
     "Make	
  me	
  food	
  in	
  the	
  rain."	
  	
  


                                                                               Insight	
  Example	
  #4	
  
The	
  best	
  part?	
  Not	
  even	
  
 Don	
  Draper	
  can	
  write	
  
tweets	
  with	
  such	
  quality	
  
  and	
  in	
  that	
  quan<ty.	
  
CASE	
  C:	
  
SOCIAL	
  LENS	
  
On	
  November	
  8	
  (#8N),	
  
Argen<na	
  had	
  its	
  biggest	
  
protest	
  in	
  years.	
  People	
  
organized	
  it	
  using	
  mostly	
  
        social	
  media.	
  
We	
  analyzed	
  1	
  Million	
  
tweets	
  to	
  iden<fy	
  the	
  most	
  
  ac<ve	
  users	
  during	
  that	
  
  day	
  using	
  the	
  hash	
  #8N	
  
Our	
  clustering	
  algorithm	
  
automa<cally	
  detected	
  a	
  
  big	
  presence	
  of	
  bots	
  
And	
  it	
  wasn’t	
  just	
  any	
  kind	
  
of	
  bot.	
  In	
  a	
  very	
  literal	
  way,	
  
  the	
  most	
  effec<ve	
  ones	
  
         where	
  Fembots.	
  
This	
  is	
  how	
  they	
  look.	
  
Design,	
  copywri<ng	
  and	
  
avatar	
  have	
  all	
  a	
  realis<c	
  
    feeling	
  to	
  them.	
  
Our	
  bot	
  detec<on	
  
technology	
  reduces	
  the	
  
noise	
  and	
  enhances	
  the	
  
 signal	
  when	
  looking	
  at	
  
     Social	
  Media.	
  
Being	
  digital,	
  is	
  being	
  interac<ve.	
  And	
  being	
  
interac<ve	
  is	
  about	
  being	
  able	
  to	
  talk	
  AND	
  listen.	
  
    AIerall,	
  it’s	
  all	
  just	
  basic	
  communica<on.	
  	
  
Learn	
  more	
  on	
  how	
  leading	
  brands	
  use	
  Zenzey	
  




       San<ago	
  Siri	
                             Manolo	
  Chada	
                         Marco	
  Gomes	
  
   	
  	
  	
  @SANTISIRI	
      	
  	
  	
  	
  	
  @MANOLOCHADA	
        	
  	
  	
  	
  	
  @MARCOGOMES	
  
san<@popego.com	
  	
           mchada@thinky.com.ar	
  	
                 marco@boo-­‐box.com	
  	
  
                  	
                                                                                	
  

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Grupo 42 - Sex, Data and Memes

  • 1. In  collabora4on  with     HOW  MEDIA  WILL  EVOLVE:   SEX,  DATA  AND  MEMES  
  • 2. We  asked  ourselves  a  holy-­‐grail  ques<on:  
  • 3. How  can  adver<sing     stop  being  invasive   announcements…  
  • 4. …  and  evolve  into     meaningful  conversa<ons?  
  • 5. AIerall,   conversa<ons  have   the  same  ingredient   that  makes  the   internet  unique:     Interac<vity.  
  • 6. Newsflash:  Tradi<onal  Media  lacks  interac<vity.     20th  century  rules  don’t  apply  to  21st  century  media.  
  • 7. Now,  new  adver<sing  models  are  possible:   smartphones  +  social  media  hold  the  key   for  meaningful  interac<ve  adver<sing.  
  • 8. FIRST,  MARKET  FUNDAMENTALS:   GET  READY  FOR  SMART  &  SOCIAL  MOBILE.  
  • 12. Brazil  has  55  million   smartphones,  20%  of   mobile  park.   It’s  expected  to  reach     130  million  by  2015.   Source:  
  • 13. Argen<na  has  11  million   smartphones,  19%  of   mobile  park.   It’s  expected  to  reach     35  million  by  2015.   Source:  
  • 16. But  now,  Social  Media   became  the  Killer  App     of  smartphones.   #MEMES  
  • 17. But  now,  Social  Media   became  the  Killer  App     of  smartphones.     (Killer  App:  what  Mario  Bros     did  for  the  Game  Boy)   #MEMES  
  • 18. “Two  birds  with  one  stone”   #MEMES  
  • 21. SOCIAL  &  MOBILE  BRANDING:   REALITY  IS  THE  NEW  AD  
  • 22. Then,  don’t  focus   on  the  ends…  
  • 23. …focus  on  the  #MEMES  
  • 24. “A  meme  is  a  unit  of   human  cultural     evolu<on  analogous  to  the   gene  (…)   It’s  a  message  that’s   contagious  in  the  same   way  a  gene<c  virus  is.”     Sir  Richard  Dawkins,  1975  
  • 25. Example:  Trending  Topics  are   #memes  that  reached  <pping  point.  
  • 26. Memes  have  Epidemic  Behaviours  like  genes  do.  
  • 27. Memes  spread  like  viruses:  the  nodes  with   more  connec<ons  –users  with  more  influence–   are  the  main  agents  of  a  message.  
  • 28. Tradi<onal  Media  has  a   “one  to  many”  model.     Interrup?on  Adver?sing     was  their  game:  “we   talk,  you  listen.”  
  • 29. Gen  Y  does  not  want  to   be  Interrupted   anymore.  They  have     mul<-­‐tasking  afen<on.  
  • 30. Social  Media  is  the  first   “many  to  many”  kind   of  media.  Everyone  has   their  share  of  voice.  
  • 31. And  it’s  good  listeners     what  make  a  Conversa?on.     Being  compe<<ve,  means   detec<ng  memes  in  real-­‐ <me  and  act  fast.  
  • 32. #SusanGlenn  Axe  Campaign:  Memes  +  TV  
  • 33. Meme<cs  is  about  Disrup?ve  Adver?sing  
  • 34. Interrup<on  models  need  you  to  pay   afen<on,  you  must  adapt  to  the  content…  
  • 35. …while  disrup<on  models  aim  to  hack  your   afen<on,  the  content  adapts  to  you.  
  • 36. HOW  WE  DO  IT?   SOCIAL  MEDIA  DATA  MINING  
  • 37. The  average  person   today  processes  more   data  in  a  single  day  than   a  person  in  the  1950’s   did  in  its  life<me.    
  • 38. Data  Mining  is  applying   computer  algorithms  to   detect  meaningful   behaviours.    
  • 39. Zenzey  finds  the  memes  that  mafer.  
  • 40. Filter  social  media  streams  with  Keywords  and  Demographics  
  • 41. Explore  conversa<on  Insights  and  iden<fy  key  memes.  
  • 42. Trigger  automated  ac<ons  to  enhance  Conversa<ons.  
  • 43. Measure  every  single  aspect  of  each  Campaign  
  • 44. Iden<fy  the  real  Key  Opinion  Formers.  
  • 45. CASE  A:   MEME  MARKETING  
  • 46. We  detected  in  Real-­‐Time   conversa<ons  in  Twifer  from   women  about  their  hair,   fashion  and  related  topics.  
  • 47. We  get  over  60.000  relevant  conversa<on     opportuni<es  per  month  in  Argen<na.  
  • 48. Our  Agent  Accounts  tweet  about  fashion  and  hairstyling,   and  reply  to  tweets  that  meet  Sedal’s  criteria  on  Zenzey.  
  • 49. 93%  of  the  replies  to  our  Agents  are  posi<ve  or  neutral.   35%  of  the  tweets  with  links,  get  clicked.  
  • 50. And  we  get  Insights  revealing  the  keys  to  drive  the   conversa<on.  For  Afro  and  Curly  Hair,  it  was  #Rock  
  • 51. So  we  generate  content  accordingly,  even  working  with   the  Key  Opinion  Formers  that  Zenzey  detected.  
  • 52. The  quan<ty  of  users  sent  by  Zenzey  to  Sedal’s  blog   averaged  the  same  number  than  other  sources.  
  • 53. Users  that  visited  the  Sedal  Blog  detected  by  Zenzey  on   Twifer  spent  4X  more  <me  with  the  content.  
  • 54. CASE  B:   MARKET  RESEARCH  DATA  MINING  
  • 55. For  a  new  fragance,  they  asked   us:  How  are  people  talking   about  love  around  the  globe?  
  • 56. Zenzey  processed  over     1  Million  tweets  with  public   displays  of  love,  from  the  UK,   USA,  Brazil  and  Argen<na.  
  • 57. In  1  month,  we  delivered  over   125  different  insights.   Including  key  movies,  tv  series,   songs,  and  of  course  #memes   for  every  market.  
  • 58. TEXTING  on  their  daily  rou4ne   It´s  extremely  important  to  receive  a  text  message  before  sending  it  to  the   other  person.  The  wow  factor  is  very  effec4ve.     Text  messages  are  an  essen4al  part  of  a  couple  daily  rou4ne.  They  need  to   receive  “good  night”  and  “good  morning”,  otherwise  they  will  feel  sad.   "That  amazing  feeling   when  your  crush  texts   you  first"     "I  get  NO  good   morning/night  calls/ texts"   Insight  Example  #1  
  • 59. #WHEN  as  a  descrip4ve  vehicle:   When  girls  start  their  tweets  using  the  hashtag  #When  it  means  that  they  are  about  to  describe  a   specific  and  unique  moment  that  makes  them  feel  happy.  It´s  a  great  vehicle  to  understand,   promote  or  just  iden4fy  “Romance”  moments.   "When  they  shut  you   up  by  kissing  you"   "When  you  take  forever  to   say  goodnight  cause  you   don't  want  to  stop  talking   to  each  other"   Insight  Example  #2  
  • 60. The  First  Time:   They  refer  to  First  Time  in  two  ways:   -­‐  Like  a  nice  memory:  LOVE  AT  FIRST  SIGHT  is  a  common  topic  among  girls.  They  mainly  talk  about   first  kisses,  first  4me  they  met  their  boyfriends,  first  4me  they  saw  a  boy,  etc.   -­‐  Like  a  sexy  experience:  “Kiss  me  like  I  was  your  first  4me”.   "#MeFirstKiss  was  in  the  snow.  He  was   walking  me  home  at  night  and  spun   me  around  and  kissed  me.  It  was  by   far  the  most  roman4c  first  kiss"     "I  never  believed  in   love  at  first  sight…   un4l  I  first  saw  you”   Insight  Example  #3  
  • 61. Love  &  Rain   Rain  seems  to  make  everything  more  roman4c.  Also,  being  tucked  in  bed  when   it’s  raining  seems  to  be  a  generalized  sense  of  well  being.   #ThingsThatILove  the  sound  of   rain  piger-­‐pahng  on  your   window  when  you're  all   snuggled  up  in  bed     Boy:  "Make  me  food."  Girl:   "Be  more  roman4c.”  Boy:   "Make  me  food  in  the  rain."     Insight  Example  #4  
  • 62. The  best  part?  Not  even   Don  Draper  can  write   tweets  with  such  quality   and  in  that  quan<ty.  
  • 63. CASE  C:   SOCIAL  LENS  
  • 64. On  November  8  (#8N),   Argen<na  had  its  biggest   protest  in  years.  People   organized  it  using  mostly   social  media.  
  • 65. We  analyzed  1  Million   tweets  to  iden<fy  the  most   ac<ve  users  during  that   day  using  the  hash  #8N  
  • 66. Our  clustering  algorithm   automa<cally  detected  a   big  presence  of  bots  
  • 67. And  it  wasn’t  just  any  kind   of  bot.  In  a  very  literal  way,   the  most  effec<ve  ones   where  Fembots.  
  • 68. This  is  how  they  look.   Design,  copywri<ng  and   avatar  have  all  a  realis<c   feeling  to  them.  
  • 69. Our  bot  detec<on   technology  reduces  the   noise  and  enhances  the   signal  when  looking  at   Social  Media.  
  • 70. Being  digital,  is  being  interac<ve.  And  being   interac<ve  is  about  being  able  to  talk  AND  listen.   AIerall,  it’s  all  just  basic  communica<on.    
  • 71. Learn  more  on  how  leading  brands  use  Zenzey   San<ago  Siri   Manolo  Chada   Marco  Gomes        @SANTISIRI            @MANOLOCHADA            @MARCOGOMES   san<@popego.com     mchada@thinky.com.ar     marco@boo-­‐box.com