Fireside Chat, Interview
Network Effects: Measure Them, Nurture Them (3 of 3)
- Network effects metrics are projected to fluctuate over time rather than remain static, with companies exhibiting a doubt amount ratio exceeding 40–50 percent or demonstrating high gross margins and pricing power predicted to possess such effects.
- Retention dynamics involve a tension where early adopters typically show superior loyalty compared to later cohorts, though product developers aim to improve retention in newer groups through continuous product improvements.
- The power user curve is expected to shift toward a right-leaning distribution over time, favoring high-frequency usage (e.g., 30 out of 30 days) among newer cohorts, with an ideal "smile" shape indicating sustained daily or hourly engagement.
- The macro-strength of a network is defined by the capital intensity required for competitors to build functional replicas, ranging from billions of dollars for massive platforms like YouTube to as little as $50 for weaker networks or narrow-use cases like restaurant delivery in a single city district.
- As networks strengthen, multi-tenanting behavior is expected to decrease while user loyalty to single applications increases, leading to pricing power which serves as the ultimate lagging metric for scale.
- Strong network effects are further evidenced by a platform's ability to retain value and demand even when facing competitors offering lower take rates, such as maintaining viability at a 15% take rate against a 10% competitor offering.