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Blinktraffic E245 final presentation Blinktraffic E245 final presentation Presentation Transcript

  • Final Project ReportBlink Traffic: Stevia Angesty Stanford University Ian Christopher ENGR 245: The Lean Michael Feng Launchpad Richard Kidarsa Winter 2011
  • Ini$al  Product  Idea   Mobile  applica+on  providing  crowd-­‐ Shanghai Lahore sourced  real  +me  traffic  map  in   developing  countries   Bangkok Jakarta
  • Meet the Team Stevia AngestyMichael FengRichard KidarsaIan ChristopherBackground: Investment Banking and Private Engineering, BusinessBackground: Computer Science EngineeringEquity in AsiaExpertise: Indonesian connections, logisticsExpertise: Programming Indonesian connections Programming,experienceExpertise: Finance, MarketingRole: Technical framework, server-side Client application development, websiteRole: Financials, Strategy Liaising with customers and partners,developmentmarket research
  • Business  Canvas  1  
  • What  we  did  (part  1)  •  Interviewed  market  leader  in  traffic  informa+on   services  •  Interviewed  8  corporate  customers  in  Indonesia  
  • Inrix  Interview   Market  Leader  in  Traffic   Data  Services  Customer  Segments:   Public   Sector   Media   Automo$ve   Mobile  
  • Pass/Fail     Criteria  •  Companies  in  Indonesia  do  not  have  the  technology  to  detect  traffic    •  Large  companies  in  Indonesia  distribute  at  least  200  corporate  Blackberries  to   their  employees  •  At  least  2  companies  have  strong  interest  in  buying  traffic  applica+on  
  • Customer  Segment:  Corporate  Interviewed  8  poten$al  business  sector  customers:   “We  have  our  own  proprietary  traffic  system” “Traffic  is  driver’s  responsibility.  We  will  evaluate  the  fuel  usage” “We  only  give  out  limited  number  of  corporate  Blackberries  to  employees” “Tardiness  is  tolerable.  We  use  motorcycles  if  it  is  too  late” cTc
  • Customer  Segment:  Corporate   The Dispatchers: Customer   Sounds cool. It’d be Archetypes   more efficient than relying on drivers. Users
  • Customer  Segment:  Corporate   Customer   The Managers: Archetypes   We’d love to have the app if it works Users Influencers and Recommenders
  • Customer  Segment:  Corporate   Influencers and Customer   Recommenders The Procurement Dept: Our drivers know the Archetypes   the traffic better than you! Users Economic Buyers, Decision Makers
  • Customer  Segment:  Corporate   Influencers and Archetypes   Recommenders The Drivers: Are you questioning our expertise? International, local, large, and small companies Users Saboteurs Economic Buyers, Decision Makers
  • Pass/Fail     Criteria   FAIL•  Companies  in  Indonesia  do  not  have  the  technology  to  detect  traffic     •  Most  don’t  but  large,  sophis+cated  ones  do  •  Large  companies  in  Indonesia  distribute  at  least  200  corporate  BlackBerries  to   their  employees   •  Largest  mul+na+onal  bank  gives  out  approximately  10  •  At  least  2  companies  have  strong  interest  in  buying  traffic  applica+on   •  0  out  of  the  8  companies  we  surveyed  
  • Customer  Segment:  Corporate  Corporates are not our initial target market
  • Business  Canvas  2  
  • What  we  did  (part  2)  •  Interviewed  market  leader  in  consumer  traffic   applica+ons  (Waze)  •  Interviewed  2  Indonesian  web  startups  •  Surveyed  98  Indonesian  commuters  
  • Waze  Interview   100% crowdsourced traffic targeting consumers 2,500,000 2,000,000 Recently raised $25 Users 1,500,000 1,000,000 million Series B 500,000 round 0 2009 (est) 2010 2011 •  How did they grow? Social and gaming features •  What markets are they focusing on? North America •  What are the key challenges? Data costs, cultural differences •  How do they make money? They don’t…yet
  • Jagoan  Interview   *  Indonesian  Social  App   *  Partnered  with  Retail   Companies   User  friendly  interface  while   SLOW   User     looks  savvy   connec$on   Loyalty  
  • Disdus  Interview   *  Indonesian  Groupon   *  Poten$al  partnership         for  adver$sing   Troublesome   Hard  to   payment   mone$ze  before   method   cri$cal  mass  
  • B2C  Customer  Feedback   98   2½h   1h   $8   web  and  phone   spent  in  heavy   surveys  in   spent  in  car  per   traffic  (<6mph)   on  gasoline  per   Indonesia     day   per  day   day  
  • B2C  Customer  Feedback  20%  of  reduc,on  in  heavy  traffic  would  save  a  person1:   Blink  Subscrip$on:   50h   $42   saved  per  year     gasoline  costs  per   year2   $1 /month1.  Assumes  5  working  days  per  week  and  50  workweeks  per  year  2.  Assumes  gasoline  usage  is  30%  of  normal  usage  during  heavy  traffic  
  • B2C  Customer  Feedback   120   52%   Plenty  of  $me  to  use   mobile  devices  while   web  and  phone   surveys  in   USE  DRIVERS     commu$ng   Indonesia     46%   1.  Mo$vated  by  3-­‐person   HOV  lanes   2.  Alterna$ve:    pay  “carpool   CARPOOL   jockeys”  $2.50  per  trip  
  • B2C  Customer  feedback1   Blackberry  leads  usage  but  iPhone/iPads  important   Conclusion: Focus on Blackberry first and iPhone/Pad second What mobile device do you use in the car? 45% 40% 40% 35% 30% 28% 25% 20% 20% 15% 10% 8% 4% 5% 0% Blackberry iPhone iPad other None smartphones 1. Data obtained from web and phone surveys of 120 potential customers
  • B2C  Customer  feedback1   What do you do with your Never   Rarely   Sometimes   Often   Always   >= Sometimes   smartphones in the car?   Work   39   17   33   6   17   50%   Gather traffic information   66   28   17   6   0   20%   Read news   39   22   22   28   0   46%   Browse internet   28   17   11   33   28   62%   Community and game mechanics are Socialize with friends   Play games   11   33   6   17   28   39   28   11   44   17   86%   58%   critical to driving usage and viralityHow often would you use these Never   Rarely   Sometimes   Often   Always   >= Sometimes  features of our application?  Report incidents   22   28   22   33   17   60%  Join a chat   33   28   44   17   0   50%  Play mini-games   44   28   28   22   0   41%  Ask and respond to questions   39   39   28   17   0   37%  Find your friends and followers   22   39   22   28   6   48%  Earn points for driving more   33   39   22   22   11   44%  1. Data obtained from web and phone surveys of 120 potential customers
  • Business  Canvas  3  
  • What  we  did  (part  3)  •  Assessed  market  size  •  Tested  demand  crea+on  via  website  
  • How  Big  is  the  Market?   1.  Located  outside  the  U.S.,  Western  Europe,  and  Australia   2.  Mobile  penetra+on  rate  *  popula+on  >=  4  million   3.  Popula+on  density  >=  2500  per  sq  km   4.  GDP  growth  rate  >=  5%   China: Beijing, Shanghai, Shenzhen Total cities: 24 Mediterranean: Istanbul North Asia ex-China: Taipei, Hong Kong, Total mobile users: 203.7 million Seoul Latin America: Mexico City Africa: Cairo, Lagos South Asia: SE Asia: Mumbai, Delhi, Jakarta, Surabaya, South America: Kolkata Bangkok, Singapore, Rio de Janeiro, Sao Kuala Lumpur, Manila Paulo, Bella Horizonte, Lima, Santiago. Buenos Aires
  • Market  Growth  Plan   Rest of World Rest of Asia • Brazil (Rio de • India (Mumbai, Janeiro, Belo Kolkata, Delhi) Horizonte • China (Bejing, • Buenos Aires Southeast Shanghai, • Cairo Asia: Shenzhen) • Istanbul • Surabaya • Hong Kong • Lagos • Bangkok • Taipei • Lima Jakarta • Singapore • Seoul • Mexico City • Bangkok • Santiago • Kuala Lumpur • ManilaMarket 1 2 3 4Cumulative number 1 6 15 25of citiesCumulative mobile 10.4 36.9 109.6 203.7users (millions) Detailed income statement and assumptions in Appendix
  • Success  Depends  on  Virality  >  Churn   Ra+o  of  early  stage  virality  rate  to  churn  rate  =  2.00x  
  • Success  Depends  on  Virality  >  Churn   Ra+o  of  early  stage  virality  rate  to  churn  rate  =  1.50x  
  • Success  Depends  on  Virality  >  Churn   Ra+o  of  early  stage  virality  rate  to  churn  rate  =  1.0x  
  • Demand  crea$on  via  website   1   2   3   “Not  a  landing  page”   Doesn’t  show  the   No  Indonesian  version   product  
  • Demand  crea$on  via  website  -­‐  results   Clicks CTR 100 74 2.00% 1.56% 68 1.25% 50 22 1.00% 0.59% 0 0.00% 1 2 3 1 2 3 People need to use the product CPC us to maximize learning click for Conversions per 1.5 1.34 6.00% 4.05% 1 0.62 4.00% 2.94% 0.54 0.5 2.00% 0.00% 0 0.00% 1 2 3 1 2 3
  • Business  Canvas  4  
  • What  we  did  (part  4)  •  Developed  server  backbone  integrated  with  OSM   and  Hadoop  •  Built  a  working  Blackberry  applica+on  •  Iterated  based  on  user  feedback  •  Talked  to  poten+al  partners  
  • Server  Backbone  with  OSM  and  Hadoop   OSM  DATA   BLINK  DATA   MAP  MANAGER   TRAFFIC   USER/EVENT   DATA   MANAGER   Front  End   AGGREGATION   Client  
  • Blackberry  applica$on  tes$ng  •  Iterate  through  different  versions   Ver1 Ver2 Ver3
  • First  release  issues   Device  cannot   Different   connect  to   provider  semng   internet   for  Indonesia   Downloading   Fix  website,   problems   Provide   instruc$ons   People  don’t   Pop  up  window   want  to  leave   to  force  people   feedback   to  give  feedback  
  • Second  release  issues   Bad  GPS   Use  data-­‐assisted   signal   GPS   Show   Users  dislike   instruc$ons  and   Pop-­‐ups   pop-­‐up  once   Users  have  old   Support  older  OS   Blackberry  OS  
  • Second  release  feedback  result   User  wants  to   So  far  50   Want  traffic  data   see  their  friends     downloads  
  • Third  release   Implemented   User  can  locate   20  downloads   chamng     others  on  map   since  release  3   days  ago   5  new  users   introduced  via   sharing   Feedback on 3rd release: Privacy   Baoery  life   Implement   Adjust  server   privacy  toggle   ping  rate  
  • Key  Partners   AGM Market  share:  44%  mobile   Interested  in  partnering  if   phone  service  &  18%   Disdus  will  adver+se  Blink   Blink  can  provide  them  free   Large companies are hard to negotiate. Blink will internet  mobile  phone   service   traffic  informa+on   in  their  website   focus more on partnering with other Startups Currently  looking  for   mobile  applica+on  to   AGM  owns  trucking  fleet   Blink  will  adver+se  Disdus   partner  to  increase  internet   (>100  trips/week)  in  Java   in  the  Blackberry   service  usage.  Telkomsel   region  which  can  help  Blink   applica+on   wants  a  large  number  of   in  genera+ng  traffic  data   users  before  partnering  
  • Final  Business  Canvas    
  • Epilogue:  What  we  learned  •  MVP  has  to  iinclude  virality,  not  just  traffic   to   nclude  virality,  not  just  traffic  •  Legal-­‐ese  is  difficult  to  handle.  It  took  us  a  long  +me  to  understand  this  •  Users  need  to  test  the  product  in  order  to  maximize  learning  •  We  need  to  assume  tthat  users  are  ttechnically  lliterate   ssume   hat  users  are   echnically  i illiterate  •  Simplicity  is  everything  from  the  user’s  perspec+ve  •  Users  who  like  our  idea  are  not  the  same  as  early  adopters  /  promoters  •  Need  to  balance  tech  planning  and  implementa+on  •  Difficult  learning  curve  to  master  technologies  like  EC2  and  Apache  •  Blackberry  is  not  developer-­‐friendly  and  it  spreads  to  the  server  •  Gelng  user  feedback  is  a  lot  harder  than  we  originally  thought  •  Difficult  to  approach  customers  large  and  small  the  second  +me  around  •  From  mindsets  to  trends  to  technical  literacy,  the  tech  landscape  is  different  in  parts  of  the  world.  •  We  cannot  spend  too  much  +me  thinking  off  /  wri+ng  an  elegant  solu+on,  but  you  also  cannot   write  garbage  •  Code  organiza+on  really  starts  to  become  more  and  more  important  as  you  LOC  grows.  By  5,000   LOC  it  will  be  crucial  to  have  a  well  organized  code  base.  •  User  mindsets  and  ttechnological  environment  ddiffer  remendously  from  mmarket  to  market   indsets  and   echnological  environment   iffer  t tremendously  from   arket  to  market  
  • Epilogue:  •  Is  this  a  viable  business?   –  Poten+al  to  solve  a  hair-­‐on-­‐fire  problem  for  a  huge  and  growing  market   –  Small  capital  investment  needed  to  validate  business  model   –  High  ROI  •  Will  we  pursue  it  aqer  the  class?   –  YES!   “You gotta be in front of the wave to catch it”
  • Business  Canvas  Change  Progress     1  
  • Business  Canvas  Change  Progress     2  
  • Business  Canvas  Change  Progress     3  
  • Business  Canvas  Change  Progress     4  
  • Business  Canvas  Change  Progress     5  
  • Business  Canvas  Change  Progress     6  
  • Business  Canvas  Change  Progress     7  
  • Business  Canvas  Change  Progress     FINAL
  • THANK YOU!
  • Appendix:  Key  Assump$ons   Growth stages Early Mid Late Plateau Market penetration rate 0.0% 3.0% 10.0% 15.0% Churn rate 50% 50% 20% 10% Virality coefficient 0.75 0.60 0.20 0.10 Promotion % increase 10% 3% 2% Population growth Employees per city 5 10 20 30 Rent per city 1,000 2,000 5,000 10,000 Revenues   Costs   Ad revenues start when users per city Monthly salary per employee   $1000   exceed   10,000   Setup costs per city   $100,000   Views per month per active user   67.75   Technology costs per 1000 us Advertising eCPM   1.00   ers   $20   Fixed promotion costs per city   $10,000   Premium revenues start when users pe Annual promotion costs per a r city exceed   200,000   ctive user   $1   Premium percentage of regular users   17%   Tax rate   25%   Premium pevenue per user per month   1.00  
  • Appendix:  Markets   Rank Land area   Density   GDP   GDP   Mobile phones   Market   (Global City / Urban area   Country   Population   Density)   (in sqKm) (per sqKm) per capita growth rate per capita size 1   Mumbai   India   14,350,000   484   29,650   3,400   8.30%   63.22%   9,072,070   2   Kolkata   India   12,700,000   531   23,900   3,400   8.30%   63.22%   8,028,940   4   Lagos   Nigeria   13,400,000   738   18,150   2,400   6.80%   50.30%   6,740,200   5   Shenzhen   China   8,000,000   466   17,150   7,400   10.10%   62.80%   5,024,000   6   Seoul/Incheon   South Korea   17,500,000   1,049   16,700   30,200   6.10%   97.20%   17,010,000   7   Taipei   Taiwan   5,700,000   376   15,200   35,100   8.30%   100.00%   5,700,000   10   Shanghai   China   10,000,000   746   13,400   7,400   10.10%   62.80%   6,280,000   11   Lima   Peru   7,000,000   596   11,750   9,200   7.80%   95.50%   6,685,000   12   Beijing   China   8,614,000   748   11,500   7,400   10.10%   62.80%   5,409,592   13   Delhi   India   14,300,000   1,295   11,050   3,400   8.30%   63.22%   9,040,460   15   Manila   Philippines   14,750,000   1,399   10,550   3,500   6.70%   73.60%   10,856,000   17   Jakarta   Indonesia   14,250,000   1,360   10,500   4,300   6.00%   73.10%   10,416,750   21   Cairo   Egypt   12,200,000   1295   9,400   6,200   5.30%   76.80%   9,369,600   25   Sao Paulo   Brazil   17,700,000   1968   9,000   10,900   7.50%   100.00%   17,700,000   27   Mexico City   Mexico   17,400,000   2072   8,400   13,800   5.00%   79.80%   13,885,200   28   Santiago   Chile   5,425,000   648   8,400   15,500   5.30%   100.00%   5,425,000   29   Singapore   Singapore   4,000,000   479   8,350   62,200   14.60%   100.00%   4,000,000   32   Istanbul   Turkey   9,000,000   1166   7,700   12,300   7.30%   92.20%   8,298,000   35   Rio de Janeiro   Brazil   10,800,000   1580   6,850   10,900   7.50%   100.00%   10,800,000   37   Hong Kong   Hong Kong   7,100,000   1100   6,455   45,600   5.70%   100.00%   7,100,000   38   Bangkok   Thailand   6,500,000   1010   6,450   8,700   7.60%   81.00%   5,265,000   47   Buenos Aires   Argentina   11,200,000   2266   4,950   15,000   7.80%   100.00%   11,200,000   52   Belo Horizonte   Brazil   4,000,000   868   4,600   10,900   7.50%   100.00%   4,000,000   90   Kuala Lumpur   Malaysia   4,400,000   1606   2,750   14,700   7.10%   100.00%   4,400,000   Total  mobile  users:  203.7  million  
  • Appendix:  Base  Case  Income  Statement  Year   0   1   2   3   4   5   6   7   8   9   10  Active users   200   7,329   268,559   1,535,297   2,980,314   6,056,792   13,783,296   21,013,877   33,175,710   36,705,798   39,698,300  % of market   0.0%   0.1%   1.9%   3.2%   2.0%   4.0%   5.1%   7.7%   12.1%   13.3%   14.2%   45,65Premium users   -   -   5   252,455   503,865   927,475   2,332,870   3,572,359   5,639,871   6,239,986   6,748,711  Basic users   200   7,329   222,904   1,282,842   2,476,449   5,129,317   11,450,427   17,441,518   27,535,839   30,465,812   32,949,589  Revenues  Advertising   -   64,502   614,266   1,445,797   3,180,516   6,551,758   12,404,549   18,487,439   23,697,673   25,988,931  Premium   -   45,655   1,846,731   3,819,142   9,198,477   19,113,580   36,267,426   55,890,537   71,641,922   78,568,768  Total Revenues   -   110,157   2,460,997   5,264,939   12,378,993   25,665,338   48,671,976   74,377,976   95,339,594   104,557,698  Costs  Market Entry Costs   100,000   -   500,000   900,000   -   1,000,000   -   -   -   -  Employee Salaries   60,971   62,800   399,824   756,995   1,809,328   3,008,931   4,821,172   6,152,098   8,395,482   9,511,708  Technology   550   20,152   220,947   503,758   1,127,276   2,320,268   4,388,843   6,575,357   8,428,461   9,243,384  Rent   12,000   12,000   75,000   148,000   348,000   582,000   959,000   1,210,000   1,760,000   2,085,000  Promotion   121,697   182,198   1,435,261   2,879,322   6,240,609   11,424,743   20,684,296   29,383,836   37,824,415   41,264,727  Total Costs   295,218   277,150   2,631,032   5,188,075   9,525,213   18,335,942   30,853,311   43,321,292   56,408,358   62,104,819  Operating cashflow   (295,218)   (166,993)   (170,034)   76,865   2,853,780   7,329,396   17,818,665   31,056,685   38,931,236   42,452,880  Taxes paid   -   5,626   290,449   514,985   1,176,461   2,465,737   4,946,514   7,764,171   9,732,809   10,613,220  Net income   (295,218)   (172,619)   (460,483)   (438,120)   1,677,319   4,863,659   12,872,151   23,292,514   29,198,427   31,839,660  Retained earnings   (295,218)   (467,836)   (928,320)   (1,366,440)   310,880   5,174,539   18,046,689   41,339,203   70,537,630   102,377,290  
  • Appendix:  Blink  Customer  Archetypes  Commuters in large developing market cities:-  Working professionals with cars-  Working professionals using public transport-  Students-  Stay-at-home partners (Tai-Tai’s)