How app stores will change by 2015

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How app stores will change by 2015

  1. 1. App  Store  In  The  Year  2015       Marcin  Rudolf,  CTO,        
  2. 2. Future-­‐Shaping  Problems  That  App  Stores   Face  1.  Open  or  closed  app  distribu<on  model?  2.  App  Stores  do  not  enable  users  to  find  apps  they   want.  3.  App  Stores  are  not  aware  of  user’s  situa<onal   and  social  context.  
  3. 3. From  Desktops  To  Gadgets   •  Handheld  hardware   created  handheld   soJware.   •  A  shiJ  from  consuming   informa<on  to  using   func<ons.  
  4. 4. „Apps  In  The  Browser”  Not  Likely  To   Succeed   •  For  most  people   there  is  no  return   to  the  desktop.   •  We  need  „open   hardware”  first!  
  5. 5. App  Discovery  Is  Unsolved   Less  than  0.1%  of  Apps  Generates  More  Than   50%  of  Monthly  Downloads  in  Jun  2012   5,000,000   Downloads  in  February   4,500,000   4,000,000   2013  Downloads  in  Jun  2012   3,500,000     3,000,000   Android  2,2  bln   2,500,000   2,000,000   Google  Play   iOS  1,87  bln   Apple  Appstore   1,500,000   1,000,000   500,000   0   0   2000   4000   6000   8000   10000   PosiCon  in  Monthly  Top  List  
  6. 6. A  Long  Tail  Of  Apps  That  Are  Never  Found   How  it  really  looks  like   State  of  the  art   5,000,000   4,500,000     4,000,000   1.  Most  apps  are  never  Downloads  in  Jun  2012   3,500,000   downloaded   3,000,000   2,500,000   2,000,000   2.  People  are  not  finding   1,500,000   what  they  want.   1,000,000     500,000   3.  SoluCon  to  this   0   0   50000   100000  150000  200000  250000  300000  350000  400000  450000  500000   problem  will  shape  the   PosiCon  in  Monthly  Top  List   future  app  store.    
  7. 7. Content  Discovery  –  Books  &  Papers  •  Fundamentally  books  &   papers  are  informa<on.  •  We  have  thousands  of  years   of  experience  in  books   discovery;>  •  Classifica<on  is  becoming   more  automa<c.  
  8. 8. Content  Discovery  -­‐  Music  •  Hundreds  of  self-­‐ proclaimed  music  genres   exist.  •  Music  is  very  social  and   self-­‐organising  which  is   leveraged  by  last.fm  and   similar  services.   hap://slycoder.files.wordpress.com/2010/01/meow.pdf  
  9. 9. Intelligent  App  Store  •  App  is  a  new  type  of  content   –  An  app  is  a  piece  of  soJware  that  carries  on  a  very   specific  ac<on  in  a  short  <me.   –  An  app  is  defined  by  what  it  does.  •  App  Store  must  learn  what  apps  can  do  for   humans  and  how  apps  can  be  linked  together.  •  With  close  to  2  mln.  apps  exis<ng  and  85  000  new   apps  each  month  this  process  must  be  automa<c.  
  10. 10. Finding  What  Apps  Can  Do   Machine  learning   algorithms  will:   •  Find  all  possible  app   func<ons.   •  Automa<cally  assign   each  app  to  one  or   more  func<on.  
  11. 11. Showing  What’s  Out  There  •  What’s  out  there  in  music?  
  12. 12. Search  Box  Is  Too  Hard  For  Average  User  How  People  Search  For  Apps?   The  Implica<ons   Specific  AcCon  Queries   “Inspire  Me”  Queries      “crop  photos”,  “block  calls”,   “games”,  “fun”,  “free”   “view  movies”   Most  users  look  for  general  app  categories     5%   15%   Some  users  want  to  be  inspired:  to  find  a  cool   app  or  a  new  game     A  small  minority  look  for  a  specific  func<on   80%   General  Category  Queries     “music”,  “movies”,  “chat”   Source:  2  years  of  XYO’s  query  log   data  
  13. 13. A  Rich  User  Context  Is  Available  •  The  device  you  are  using  knows  what  you  do  and   where  you  are.  •  Social  services  know  who  you  are  and  what  and   whom  you  like.  •  You  are  typically  giving  this  informa<on  away,   disregarding  any  privacy  concerns.  
  14. 14. Facebook  Graph  Search:  An  Early  Example   Of  Social  Content  Discovery  
  15. 15. User  As  A  Query   What  if  we  map  what  you  and  your   friends  like  to  what  apps  in  app  store  can   do  for  you?  
  16. 16. App  Store  2015  •  A  mul<tude  of  „Walled  Gardens”  •  With  deep  understanding  what  humans  can  do   with  apps.  •  With  intelligent  algorithms  which  make  long  tail   apps  available.  •  With  deep  knowledge  of  user’s  situa<onal  and   social  context  that  delivers  apps  seamlessly.  
  17. 17. Thank  You!  …and  see  all  the  above  in  ac<on  hap://next.xyo.net/betasignup  

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