New Media Economics

Review: Foundations

Slides: New Media Economics

  1. Digital: Reach, Richness and Flexibility
    • Traditional, Reach Richness tradeoff
    • Customer controls navigation based on her needs
    • Cookie files (non-Mobile), location data (Mobile)
    • Low marginal cost of reach
    • Flexibility: Utility throughout the purchase process
    • Impact of machine learning (ex. Amazon, Google etc.)
  2. The Long Tail
    • Democratized production and distribution, improved search
    • Niche markets more valuable
    • Example: Search, focus on the Long Tail for keyword optimization (less demand, but better quality)
    • Example: On line retail (Amazon example: My

    • Example: Search Advertising (Marketing budget = variable

    • Enabled by good search, data analytics (collaborative
  3. Cost structure
    • Fixed costs
    • Sunk costs (non recoverable fixed costs)
    • Variable costs (close to zero)
    • Enables versioning and product differentiation
    • Cloud computing, digital advertising: switches costs from fixed to variable

    • Opportunity cost (to customer): you buy an iPhone, you give up the opportunity to have an Android phone
  4. Moore’s Law
    • Increasing power
    • Reduced cost
    • Innovation in computing
    • Moore’s Law: The rule that really matters in tech: Plenty of other industries aren’t as fortunate. You don’t see commercial supersonic airplane travel, home fusion reactors, or 1,000-mile-per-gallon cars. But the computing industry has a fundamental flexibility that others lack: it’s about bits, not atoms.

      “Automobiles and planes are dealing with the physical world,” such as the speed of sound and the size and mass of the humans they carry, said Sam Fuller, chief technology officer of Analog Devices, a chipmaker that’s been in the electronics business even longer than Intel. “Computing and information processing doesn’t have that limitation. There’s no fundamental size or weight to bits. You don’t necessarily have the same constraints you have in these other industries. There potentially is a way forward.”

  5. Installed-base
  6. Network effects
    • Metcalfe’s Law: The value of a network is equal to the square of the number of connected users of the network
    • Reed’s law: growth of possible subgroups, within a network, grows as the network grows
    • Critical problem: gain early adopters
    • Outcomes
    • Examples:
      • Amazon
        • Machine learning: collaborative filtering
      • eBay
        • Reputation
      • Maps: Google versus Apple, versus Nokia
        • Crowd sourcing
        • Machine learning
      • Search: WebCrawler > Alta Vista > Google
        Google versus Bing
        • Better search
          • Big data
          • Machine learning
        • More targeted ads
      • Wikipedia
        • Crowdsourcing Content
      • Facebook versus MySpace
      • Messaging Services (Whatsapp)
      • reddit versus digg
      • Mobile: iOS, Android, Windows, BlackBerry
        • New users versus switching users?
        • App stores and developers priorities?
      • Pandora versus Rdio versus Spotify ?
      • Netflix
  7. Platforms: control? Open versus Closed?
  8. Standards
    • Open:
      Internet versus MSN and AOL (1995)

    • Proprietary: Wintel (controlled by Microsoft and Intel)
  9. Business Model (Andreessen: Bubble Believers ‘Don’t Know What They’re Talking About’)
    1. User growth
    2. User lock in
    3. Monetization
    4. Value share ?