CVPR2010: Learnings from founding a computer vision startup: Chapter 10: Competition and positioning: OMG, Google is doing the same thing!

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  • 1. 10. Competition and positioning OMG, Google is doing the same thing
  • 2. No competition, no market
  • 3. Learnings from founding a Computer Vision Startup Basic competition check (again) www.crunchbase.com
  • 4. DifferentiationLearnings from founding a Computer Vision Startup How are you different from your competition? (performance, features, geographic, price, business model, ...)
  • 5. Learnings from founding a Computer Vision Startup How to handle competition? Be aware of who competitors are and what they do (you need to be able to answer when people ask) But... Focus on your own ideas and on making your product great Be inspired if competition does something good but don’t copy or follow blindly - copying lacks understanding, better think for yourself Competitors might have a different agenda and goals And... Don’t worry - a reasonable amount of competition is good for all
  • 6. Learnings from founding a Computer Vision Startup OMG, what happens if Google is doing “the same”? - they never really do the exact same thing - they most likely have a different goal - they most certainly have a different business model - they have competitors who might want partners (you)
  • 7. Learnings from founding a Computer Vision Startup Polar Rose: How we did it Case 1: Picasa & iPhoto Google Picasa added face recognition for people tagging in fall 2008 Apple’s iPhoto added the same in January 2009 At the same time we were doing people tagging at polarrose.com (Flickr/Facebook) End result: Picasa and iPhoto drive competitors to feature parity
  • 8. Learnings from founding a Computer Vision Startup Polar Rose: How we did it Case 2: Goggles Google Goggles launched late fall 2009 with supposed face recognition feature disabled At the same time we had the Augmented ID / Recognizr app End result: still unclear, but large players are more careful, small startups can take risks and provoke. Again a drive for feature parity elsewhere is emerging.
  • 9. Learnings from founding a Computer Vision Startup “Traction” first iPhone MMS campaign with easyjet first version visual search iPhone SDK Worlds first iPhone app $$ Seed for visual search > 1 million items in DB Amazon acquires snaptell kooaba Tech Talk @ Google(USA) $$ Angel > 10 million items in DBQ2/07 Q3/07 Q4/07 Q1/08 Q2/08 Q3/08 Q4/08 Q1/09 Q2/09 Q3/09 Q4/09 Q1/10 A brief history of visual search and kooaba
  • 10. Learnings from founding a Computer Vision Startup Books: ReWork (again) References
  • 11. Round up
  • 12. Learnings from founding a Computer Vision Startup Things we didn’t cover Some boring parts: IP & patents How to handle admin stuff (bank, bookkeeping, legal,...) Office & finding a good place to work B2B licensing alternatives and structures How to do consultancy work Deeper into certain topics we presented today. We could tell you next CVPR if you want ;)
  • 13. Learnings from founding a Computer Vision Startup Take home messages Starting out is cheaper and easier than you think Focus on core functionality and engage customers early Vision is about to enter consumer market, timing is good Lots of the things we learned and told you today turn out to be “just” (advanced) common sense.
  • 14. Learnings from founding a Computer Vision Startup Vision specific lessons Vision is magic to many, explanations often needed Complex technology (you will need funding / quality in product development) Business models in B2C often unclear (innovation is needed here, too) But huge opportunities for you as an expert, if you’re not a total techie ;)
  • 15. Feedback?
  • 16. The EndTill Quack Jan Erik Solemquack@kooaba.com www.polarrose.comwww.kooaba.com janerik@polarrose.com@tmdq @jesolemwww.quack.ch www.janeriksolem.net Slides will be online! http://www.vision.ee.ethz.ch/tquack/cvpr10-tutorial.html