CVPR2010: Learnings from founding a computer vision startup: Chapter 7: Business models: how to make money?
- 2. Learnings from founding a Computer Vision Startup Flickr:dystopos How are you gonna create value?
- 3. Learnings from founding a Computer Vision Startup Innovation happens also in business models (not only technology)
- 4. Learnings from founding a Computer Vision Startup Lots of business models possible Auction business model ■ Bricks and clicks business model ■ Collective business models ■ Component business model ■ Cutting out the middleman model ■ Direct sales model ■ Distribution business models, various ■ Fee in, free out ■ Franchise http://en.wikipedia.org/wiki/Business_model ■ Freemium business model ■ Industrialization of services business model ■ Low-cost carrier business model ■ Loyalty business models ■ Monopolistic business model ■ Multi-level marketing business model ■ Network effects business model ■ Online auction business model ■ Online content business model ■ Premium business model ■ Professional open-source model ■ Pyramid scheme business model ■ Razor and blades business model (bait and hook) ■ Servitization of products business model ■ Subscription business model
- 5. Learnings from founding a Computer Vision Startup One of the key decisions B2C vs B2B Flickr:jamesjustin / dexxus
- 6. Learnings from founding a Computer Vision Startup New Markets vs Existing Markets New Market Finding a working business model at all Existing Market Finding a better business model Flickr:Aube insanité http://en.wikipedia.org/wiki/Blue_Ocean_Strategy
- 7. Learnings from founding a Computer Vision Startup Good Business Models are Scalable Create once - sell often Scalable: licenses, subscriptions, services Not so scalable: project business, consulting Flickr:brandondoran
- 8. Learnings from founding a Computer Vision Startup “Free” as a business model Chris Anderson, Wired http://www.wired.com/techbiz/it/magazine/16-03/ff_free Free: the future of a radical price. Chris Anderson, 2009 http://www.amazon.com/Free-Future-Radical-Chris-Anderson/dp/1401322905
- 9. Learnings from founding a Computer Vision Startup Twitter has many appealing opportunities for generating revenue but we are holding off on implementation for now because we don’t want to distract ourselves from the more important work at hand which is to create a compelling service and great user experience for millions of people around the world. While our business model is in a research phase, we spend more money than we make. From the twitter website (“About twitter” (2009))
- 10. Learnings from founding a Computer Vision Startup “Free” as a business model - maybe not? David Heinemeier Hansson The secret of making money online http://www.youtube.com/watch?v=0CDXJ6bMkMY
- 11. Learnings from founding a Computer Vision Startup Free often doesn’t mean free for everybody Two-sided markets One side finances the other. Often with advertising. Examples: Any newspaper, Google, Acrobat Reader, Games. Platforms are often two-sided markets Examples: Nintendo, PC, iPhone, Acrobat. Freemium Basic Service Free, Pro costs (Flickr, Dropbox, Evernote and many other online services) The paying minority finances the free majority. (But digital services are cheap, so no big deal) Typical conversion is 2-3%. These users pay for everyone else.
- 12. Learnings from founding a Computer Vision Startup Examples of two sided markets Geoffrey Parker and Marshall Van Alstyne (2005). “Two-Sided Network Effects: A Theory of Information Product Design.” Management Science, Vol. 51, No. 1
- 13. Learnings from founding a Computer Vision Startup Why does Google work? Advertising targeted - really targeted! Basic advantage: people are searching for something. (They are not on facebook, NYT ...) Economic part of ad auction business is crucial (more crucial than PageRank) E.g. they hired Hal Varian as Chief Economist (formerly professor Economics at Stanford) Secret of Googlenomics: Data-Fueled Recipe Brews Profitability (Wired Oct 2009) http://www.wired.com/culture/culturereviews/magazine/17-06/nep_googlenomics?currentPage=all
- 14. Learnings from founding a Computer Vision Startup Digital Business Model Trends Advertising Must be targeted as just seen. Examples: Google adwords, many websites, iAd (!!) Saas (Software as a Service) Run Software in cloud/browser. Subscriptions (!). Example: Salesforce, 37signals. Freemium Basic service free, extended costs. “Drug dealers get it right” (ReWork) Examples: Flickr, Google apps, Evernote! “Apps” Apple App store is huge success. (1 billion paid out). But note: not recurring for developer -> iAd Virtual goods Mainly gaming. In game purchase of weapons, levels etc. Facebook virtual goods ($75 million* in 09(?)). * http://www.businessinsider.com/breaking-down-facebooks-revenues-2009-7
- 15. What is special about Vision? In Terms of Business Model
- 16. Learnings from founding a Computer Vision Startup Special challenges for Vision Startups B2B partly well established Industrial Vision, face recognition, ... B2C no models established yet Investors often point to the many image retrieval (by similarity) companies as failures although counter examples exist (Riya, ...) BUT: new opportunities come around these days New generation of technology (local features etc.) Mobile phones with integrated camera (in general increasing amount of visual data on Web) New distribution platforms for services (app stores!)
- 17. Learnings from founding a Computer Vision Startup Case: Riya - like.com Tried to do a Flickr competitor with face recognition but too little traction/adoption. Switched to visual comparison for shopping and now cash flow positive with shopping referral model. Advertising to get traffic.
- 18. How we did it
- 19. Learnings from founding a Computer Vision Startup How we did it Experimented a lot Were now able to turn from project business into recurring models Still experimenting with joy This year is gonna be interesting! Lots of opportunities to innovate. We are making revenue ;) We have been making revenue from the beginning. No black numbers yet, but hopefully soon.
- 20. Learnings from founding a Computer Vision Startup How we did it Experimented a lot First, we tried to do a “Google” (tagging across the web, better search results for people search) Then we tried B2C (consumer service where users collectively tag people in their social graph) Now we do B2B (licensing for mobile, desktop and cloud) Not there yet but B2B seems to be the right model.
- 21. Q&A
- 22. Learnings from founding a Computer Vision Startup Resources Wikipedia on Business Models http://en.wikipedia.org/wiki/Business_model Book: Blue Ocean Strategy http://en.wikipedia.org/wiki/Blue_Ocean_Strategy Free (Wired Article) http://www.wired.com/techbiz/it/magazine/16-03/ff_free http://www.amazon.com/Free-Future-Radical-Chris-Anderson/ Free (Book) dp/1401322905 David Heinemeier Hansson http://www.youtube.com/watch?v=0CDXJ6bMkMY The secret of making money online Geoffrey Parker and Marshall Van Alstyne (2005). “Two-Sided Network Effects: A Theory of Information Product Design.” Management Science, Vol. 51, No. 1 http://www.wired.com/culture/culturereviews/magazine/17-06/ Wired Article Googlenomics nep_googlenomics?currentPage=all