A Salesforce user with many integrations is less likely to churn, so its API is open. In contrast, Twitter restricted its API to prevent third-party clients from siphoning users away from its ad-supported feed. This fundamental difference in business models dictates a company's API strategy.
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OpenAI embraces the 'platform paradox' by selling API access to startups that compete directly with its own apps like ChatGPT. The strategy is to foster a broad ecosystem, believing that enabling competitors is necessary to avoid losing the platform race entirely.
The need for emotional connection isn't limited to consumer products. All software is used by humans whose expectations are set by the best B2C experiences. Even enterprise products must honor user emotions to succeed, a concept termed 'Business to Human'.
Airbnb's AI-driven party prevention is a pro-host move to counterbalance recent pro-guest changes to its fee structure. This illustrates how platform businesses must continuously alternate which side of the marketplace they favor to keep both groups engaged and prevent churn on either side.
Businesses like jewelers mistakenly dismiss LinkedIn as purely for B2B. This is a flawed view because every professional on the platform is also a consumer ('a C'). This creates a significant, overlooked opportunity for direct-to-consumer sales in a less saturated environment.
In an AI-driven ecosystem, data and content need to be fluidly accessible to various systems and agents. Any SaaS platform that feels like a "walled garden," locking content away, will be rejected by power users. The winning platforms will prioritize open, interoperable access to user data.
Unlike traditional APIs, LLMs are hard to abstract away. Users develop a preference for a specific model's 'personality' and performance (e.g., GPT-4 vs. 3.5), making it difficult for applications to swap out the underlying model without user notice and pushback.
Smaller software companies can't compete with giants like Salesforce or Adobe on an all-in-one basis. They must strategically embrace interoperability and multi-cloud models as a key differentiator. This appeals to customers seeking flexibility and avoiding lock-in to a single vendor's ecosystem.
OpenAI has seen no cannibalization from its open source model releases. The use cases, customer profiles, and immense difficulty of operating inference at scale create a natural separation. Open source serves different needs and helps grow the entire AI ecosystem, which benefits the platform leader.
OpenAI uses two connector types. First-party (1P) "sync connectors" store data to enable higher-quality, optimized experiences (e.g., re-ranking). Third-party (3P) MCP connectors provide broad, long-tail coverage but offer less control. This dual approach strategically trades off deep integration quality against ecosystem scale.
To become indispensable to SMBs, a marketing platform cannot be a standalone tool. It must deeply integrate with the specific, proprietary systems that define an industry's workflow, such as a real estate agent's CRM or a mechanic's booking software. This ecosystem-first approach eliminates the friction of switching between tools, making the marketing platform a natural and effective extension of the SMB's core business operations.
