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Distribution Platforms Follow Predictable Open-Close Cycle

by Brian Balfour on August 17, 2025

The Predictable Lifecycle of New Distribution Platforms

Brian Balfour identifies a recurring pattern in how new distribution platforms emerge, evolve, and eventually close down, creating both opportunities and risks for companies that build on them.

The Four-Stage Cycle of Distribution Platforms

Step 0: Market Conditions Are Met

  • There's consensus about a new huge category emerging (social, mobile, AI chatbots)
  • No clear winner yet exists among 5-7 major players battling for dominance
  • Fierce competition as stakes are high (markets typically end in monopolies or duopolies)

Step 1: Identifying and Building the Moat

  • A platform identifies what will create defensibility and help them hit escape velocity
  • They need to gather this moat as fast as possible, which requires ecosystem help
  • They establish a third-party platform with incentives for developers/creators
  • The value exchange: "Develop on our platform, add use cases and engagement, and we'll give you distribution"

Step 2: The Platform Opens Up

  • Platform provides generous organic distribution to third parties
  • Developers/creators rush in to capitalize on the new distribution opportunity
  • This period creates massive growth for both the platform and early adopters
  • Examples: Facebook's canvas apps, Google's organic search results, Apple's App Store

Step 3: The Platform Closes for Control and Monetization

  • Platforms inevitably begin locking down and restricting what was previously open
  • This happens through three primary mechanisms:
    • Shutting down third-party access entirely
    • Developing first-party applications that absorb the highest-value use cases
    • Artificially depressing organic distribution to push creators toward paid mechanisms

Why This Matters Now

  • We're at an inflection point where a new distribution platform is about to emerge
  • ChatGPT is the most likely candidate based on retention metrics and context/memory moats
  • The cycles are getting shorter and shorter, giving companies less time to capitalize
  • This creates a prisoner's dilemma: "There is no opting out of the game"

Strategic Implications for Companies

For Startups:

  • This is the opportunity to disrupt incumbents (like Zynga grew on Facebook)
  • You must choose one platform and go all-in (you don't have resources to spread bets)
  • Focus on the platform with the best retention and engagement, not just user numbers
  • Consider user quality and monetization potential (iOS vs Android economics)
  • Immediately start planning your exit strategy from dependency on the platform

For Incumbents:

  • You must participate even if it feels counterintuitive (like HubSpot connecting to ChatGPT)
  • You can afford to place multiple bets across platforms
  • Customer expectations will shift to include these new experiences
  • If you don't participate, competitors will gain advantage

Evaluating Which Platform to Bet On

  1. Look at retention and depth of engagement over pure user numbers
  2. Assess user quality and monetization potential
  3. Analyze the value exchange being offered
  4. Consider scale, but don't be fooled by vanity metrics
  5. Plan your exit strategy from the beginning

Historical Examples

  • Facebook: Opened canvas to developers, gave access to notifications/feed, then restricted access and built first-party alternatives
  • Google: Slowly reduced organic search visibility while increasing ad real estate
  • LinkedIn: Boosted company pages then personal content, then restricted reach to push toward ads
  • Apple App Store: Created distribution for developers, then added more restrictions and fees

The key insight is that this pattern is predictable and understanding it allows you to capitalize on the opportunity while preparing for the inevitable restrictions that will follow.

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