cold-start-problem

The Cold Start Problem

A framework for starting and scaling products that live or die by network effects — marketplaces, social apps, messaging, and collaboration tools — distilled from Andrew Chen's The Cold Start Problem. Use it to launch products that are worthless until other users show up, to sequence growth network by network, and to navigate the five stages: the cold start, the tipping point, escape velocity, hitting the ceiling, and the moat.

Core Principle

Network effects start as a liability, not an asset. Value lives in connections between users, and on day one there are none — the same force that makes a dense network unstoppable makes an empty one useless. You don't escape by launching to a market; you escape by building one tiny, complete, self-sustaining network at a time, solving its hard side first, then tipping adjacent networks with a repeatable playbook until the market follows.

Scoring

Goal: 10/10. Rate launch plans and growth strategies for networked products 0-10 against the principles below. Report the current score and the specific changes needed to reach 10/10.

• 9-10: Named atomic network with an instrumented magic moment, hard side solved first, repeatable tipping playbook, density/liquidity metrics, explicit ceiling and moat plan
• 7-8: Clear atomic network and hard-side focus, but tipping tactics are ad hoc or metrics still track totals over density
• 5-6: Network effects acknowledged, but the launch targets a broad market and both sides are treated equally
• 3-4: Generic user-acquisition plan; network thinking limited to "add invites and hope it spreads"
• 0-2: Big-bang launch to everyone at once, vanity signups, no hard-side strategy, no liquidity measures

Framework

1. Network Effects Fundamentals

Core concept: A networked product connects people with each other — buyers with sellers, creators with audiences, coworkers with coworkers — and becomes more valuable as the right people join. Network effects come in three distinct forms: the acquisition effect (the network pulls in its own new users), the engagement effect (more users make each session more valuable), and the economic effect (density improves monetization and unit economics). A product can be strong in one and weak in the others.