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Predict your internet startup's future growth and revenue with a simple user model

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The document discusses using a simple model and data collection to predict key metrics for an internet startup, including the maximum user base, lifetime value of customers, and peak revenue. It provides an example of how to calculate the predicted maximum user base based on new users, attrition rate, and other factors that could impact user growth or retention. It also recommends customizing Google Analytics and tracking user cohorts to understand website dynamics and user behavior over time in order to make more accurate predictions.

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A Crystal Ball for your Internet Startup August 30, 2009 Mike Koss – StartPad.org StartupWeekend – BizSpark/Redmond
Your Site = Social Experiment
Predictions ,[object Object],[object Object],[object Object],[object Object],[object Object]
A Simple Model Active User Base New Users Leave Stay % (Attrition)
A Simple Example Max User Base = New Users/Attrition_rate (1,000)
What Can Change? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
StartPad.org
Example (cont) 958 Unique (Last Month) 836 New Leave 89 Returns 91% (Attrition) Prediction: User Base Peak = 836/91% = 919
A “Freemium” Model Organic New Users Paid Viral Free Trial Users % Conversion Rates % % $$$ Subscription Users Referrals % Leave % Leave %
Data Collection ,[object Object],[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Photo Credits ,[object Object]

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Predict your internet startup's future growth and revenue with a simple user model

  • 1. A Crystal Ball for your Internet Startup August 30, 2009 Mike Koss – StartPad.org StartupWeekend – BizSpark/Redmond
  • 2. Your Site = Social Experiment
  • 3.
  • 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.
  • 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.
  • 11.
  • 12.