Pull-Facilitate-Match Model
The three essential functions every platform must perform to generate valuable interactions
The Pull-Facilitate-Match Model identifies the three essential functions that every platform must perform to create a high volume of valuable interactions. Pull means attracting producers and consumers to the platform. Facilitate means providing tools, rules, and infrastructure that make interactions easy, enjoyable, and valuable. Match means using information about each participant to connect them in mutually rewarding ways. All three functions must work well for a platform to succeed.
Pull is uniquely challenging for platforms because they face a chicken-or-egg problem that pipeline businesses do not: users will not come unless the platform has value, and the platform will not have value without users. Pull strategies include solving this cold-start problem, creating feedback loops that keep users returning, and leveraging the growing currency of attention, popularity, and influence that comes with platform scale. Twitter's enormous user base makes a successful tweet far more rewarding than the same message on a smaller platform, which is itself a form of pull.
Facilitate means creating infrastructure where value can be created and exchanged. Unlike pipeline businesses that control value creation directly, platforms create the conditions for value creation by others. This involves reducing transaction friction, providing production tools, and establishing interaction rules. Match is the algorithmic intelligence that ensures the right producers connect with the right consumers. Poor matching floods users with irrelevant content; excellent matching makes the platform feel almost magical in its relevance.
- All three functions must work well; failure in any one can doom the platform
- Pull depends on feedback loops, not just initial acquisition
- Facilitate means creating infrastructure for others to create value, not creating value yourself
- Match quality determines whether users find the platform valuable or frustrating
- The growing size of the network should enhance all three functions through network effects
- Design Your Pull StrategySolve the chicken-or-egg problem using one of the eight launch strategies. Then build feedback loops: single-user feedback loops reward individual activity (LinkedIn profile completeness triggers more profile views), and multi-user feedback loops create cycles between producers and consumers (Facebook status updates generate likes and comments, which generate more updates). Leverage the currency of attention and influence that grows with platform size.
- Build Facilitation InfrastructureCreate the tools, rules, and systems that make interactions seamless. This includes production tools (Instagram's photo filters, YouTube's upload system), interaction rules (Airbnb's booking process, eBay's auction system), and quality controls (review systems, content moderation). The goal is to make it as easy as possible for producers to create value and for consumers to find and engage with it.
- Develop Matching IntelligenceBuild the algorithmic capability to connect the right producers with the right consumers. This could be search-based (Google matching queries to web pages), social-signal-based (Facebook's news feed algorithm), behavior-based (Netflix recommendations), or location-based (Uber's proximity matching). The matching function should improve over time as the platform accumulates more interaction data.
- Diagnose Performance GapsWhen the platform underperforms, use the three-function framework to diagnose the problem. Low user numbers indicate a pull problem. High user numbers but low interaction rates indicate a facilitate or match problem. High interaction initiation but low completion rates indicate a facilitate problem. Low interaction satisfaction despite completion indicates a match problem.
- Create Reinforcing CyclesDesign the three functions to reinforce each other. Better matching creates more successful interactions, which improves the platform's reputation (pull). More users generate more data, which improves matching. Better facilitation tools attract more producers, which gives the matching algorithm more options. When all three functions work together, they create a compounding advantage that is extremely difficult for competitors to replicate.
Facebook's early pull challenge was that users only found the platform valuable after connecting to a minimum number of friends. Facebook shifted marketing from recruiting new users to helping existing users form connections. For facilitation, the news feed algorithm became the primary tool for surfacing relevant content. For matching, Facebook continuously refined its algorithm using signals from past interactions, social connections, and content preferences to determine which status updates, photos, and links each user would see.
The model was developed by the authors as a diagnostic tool for understanding why platforms succeed or fail. By analyzing platforms across many industries, they observed that failures could almost always be traced to a breakdown in one of these three functions: either the platform could not attract users (pull failure), could not make interactions easy and valuable (facilitate failure), or could not connect the right participants (match failure). The framework provides a structured way to diagnose and address these problems.