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.
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The stickiest software is critical but inexpensive relative to a customer's overall budget, like payroll services. This 'Goldilocks zone' makes the software too small a cost for C-suite review, yet too embedded to easily replace, creating a powerful moat.
Platforms first attract users with good service, then lock them in. Next, they worsen the user experience to benefit business customers. Finally, they squeeze business customers, extracting all value for shareholders, leaving behind a dysfunctional service.
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.
Businesses building their entire model on leads from a single platform like Google or Facebook Ads are at severe risk. An algorithm change can instantly destroy their customer source, highlighting the need for a diversified, systems-based marketing approach rather than tactical dependency.
Managed Service Providers become indispensable to vendors like Microsoft and Google by adding $7-11 of high-value services for every dollar of product revenue they generate. This value creation gives them significant leverage and makes them a more respected and crucial part of the vendor's ecosystem.
Despite its massive user base, OpenAI's position is precarious. It lacks true network effects, strong feature lock-in, and control over its cost base since it relies on Microsoft's infrastructure. Its long-term defensibility depends on rapidly building product ecosystems and its own infrastructure advantages.
To serve its largest customers, Square's open platform is crucial. It allows enterprises to integrate their preferred third-party tools with Square's core services. This flexibility prevents churn by allowing customers to customize their tech stack instead of being locked into a closed ecosystem.
Home Depot became the default shopping destination for so many customers that manufacturers faced a choice: sell through Home Depot or lose access to consumers who wouldn't seek them elsewhere. This created a powerful network effect where scale attracted key suppliers, which reinforced customer loyalty and solidified their market dominance.
New technology like AI doesn't automatically displace incumbents. Established players like DoorDash and Google successfully defend their turf by leveraging deep-rooted network effects (e.g., restaurant relationships, user habits). They can adopt or build competing tech, while challengers struggle to replicate the established ecosystem.
A powerful retention strategy for DaaS vendors is embedding external reference data into a client's core systems (e.g., CRM, ERP). This makes the client's proprietary data more valuable and actionable, creating a deep, value-driven dependency that makes the vendor incredibly difficult and costly to replace.
