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Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
Crystal Ball for your Internet Startup
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Crystal Ball for your Internet Startup

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This presentation outlines a method of modeling a Freemium internet startup to predict it's ultimate business value.

This presentation outlines a method of modeling a Freemium internet startup to predict it's ultimate business value.

Published in: Business, Technology
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  • 1. A Crystal Ball for your Internet Startup August 30, 2009 Mike Koss – StartPad.org StartupWeekend – BizSpark/Redmond
  • 2. Your Site = Social Experiment
  • 3. Predictions
    • How many unique visitors will you eventually have?
    • What will be your maximum revenue?
    • What is the life-time value of a new customer?
    • How much is your business worth?
    • How can you improve the above?
  • 4. A Simple Model Active User Base New Users Leave Stay % (Attrition)
  • 5. A Simple Example Max User Base = New Users/Attrition_rate (1,000)
  • 6. What Can Change?
    • # of New Users:
      • Search Engine Optimization (SEO)
      • Paid Ads
      • PR or “Events”
    • The user type :
      • May have different expectations or be more or less inclined to join
    • Attrition rate (through site improvements or active engagement, e.g. email)
  • 7. StartPad.org
  • 8. Example (cont) 958 Unique (Last Month) 836 New Leave 89 Returns 91% (Attrition) Prediction: User Base Peak = 836/91% = 919
  • 9. A “Freemium” Model Organic New Users Paid Viral Free Trial Users % Conversion Rates % % $$$ Subscription Users Referrals % Leave % Leave %
  • 10. Data Collection
    • Customization of Google Analytics Needed
    • User Defined variable can be used to tag each user as “Paid”, “Referral”, “Trial”, or “Subscriber”
    • “Cohort Analysis”
      • Track individual users by month they first visited your site (or signed up for an account)
      • Track each cohort monthly to see % returning
  • 11. Summary
    • Understanding your web site dynamics you can predict:
      • Peak User Base (Trials and Subscribers)
      • Expected Lifetime of each user class
      • Lifetime value of each new user
      • Peak Revenue
      • Current Enterprise Value
      • Download Spreadsheet from
      • http://startpad.org/crystal-ball
  • 12. Photo Credits
    • http://www.flickr.com/photos/plasticbystander/

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