Even while losing significant money, a company's massive user base can be its core asset. This leverage allows it to influence the market cap of its suppliers simply by choosing them, demonstrating that user aggregation is more powerful than immediate profitability in today's market.
Businesses become critically dependent on platforms for even a small fraction of their revenue (e.g., 20%). This 'monopsony power' creates a stronger lock-in than user network effects, as losing that customer base can bankrupt the business.
According to Ben Thompson's Aggregation Theory, OpenAI's real moat is its 800 million users, not its technology. By monetizing only through subscriptions instead of ads, OpenAI fails to maximize user engagement and data capture, leaving the door open for Google's resource-heavy, ad-native approach to win.
High customer concentration risk is mitigated during hypergrowth phases. When customers are focused on speed and market capture, they prioritize effectiveness over efficiency. This provides a window for suppliers to extract high margins, as customers don't have the time or focus to optimize costs or build in-house alternatives.
Despite losing money, OpenAI leveraged its massive user base to secure warrants for 10% of AMD. This contrasts with NVIDIA, who received equity in OpenAI, showcasing how user control dictates power in strategic partnerships, even with hardware giants.
During major platform shifts like AI, it's tempting to project that companies will capture all the value they create. However, competitive forces ensure the vast majority of productivity gains (the "surplus") flows to end-users, not the technology creators.
Snap's $400M deal with Perplexity, paid largely in stock, pioneers a new strategy for consumer platforms. They can leverage their massive user bases as a capital asset, trading distribution for significant equity stakes in capital-rich AI startups that desperately need user growth.
Ben Thompson's analysis suggests OpenAI is in a precarious position. By aggregating massive user demand but avoiding the optimal aggregator business model (advertising), it weakens its defense against Google, which can leverage its immense, ad-funded structural advantages in compute, data, and R&D to overwhelm OpenAI.
The stark contrast between niche paid apps and the trillion-dollar companies dominating the top free app charts highlights a critical insight for the AI race. An existing user base of billions, which companies like Google and Meta possess, is a more powerful competitive advantage than having a marginally better model.
Unlike industrial firms, digital marketplaces like Uber have immense operational leverage. Once the initial infrastructure is built, incremental revenue flows directly to the bottom line with minimal additional cost. The market can be slow to recognize this, creating investment opportunities in seemingly expensive stocks.
While startups like OpenAI can lead with a superior model, incumbents like Google and Meta possess the ultimate moat: distribution to billions of users across multiple top-ranked apps. They can rapidly deploy "good enough" models through established channels to reclaim market share from first-movers.