A moat is a durable competitive advantage that protects a company’s profits from competitors over time. The term was popularized by Warren Buffett but maps directly onto what VCs underwrite in early-stage startups.

The seven classic moats

1. Network effects

Value increases with each new user.

• Direct network effects: More users = more value (social networks, marketplaces).
• Indirect / two-sided: More sellers attract more buyers, and vice versa (Airbnb, eBay).
• Data network effects: More users → more data → better product → more users (Google Search).

2. Switching costs

Customers face real costs to migrate away.

• Financial: Integration, implementation, retraining.
• Operational: Workflow disruption.
• Data lock-in: Historical data stored in the platform.
• Examples: Salesforce, SAP, deep SaaS platforms with custom integrations.

3. Economies of scale

Unit costs decrease as volume increases.

• Fixed-cost leverage: Amortizing R&D across more customers.
• Supply chain scale: Amazon, Walmart.
• Compute/data scale: Cloud hyperscalers, AI model providers.

4. Proprietary IP or technology

Patents, trade secrets, or complex technical capabilities.

• Biotech patents: Often the primary moat.
• Deep tech: Semiconductors, quantum, fusion.
• Non-patent technical: Unique algorithms, custom hardware.

5. Data moats

Exclusive datasets that improve product quality.

• Proprietary sensor data: Tesla driving data, Waymo fleet data.
• Usage data: Shopify merchant data, Square transaction data.
• Regulatory datasets: FDA submissions, SEC filings.

6. Distribution advantages

Uniquely efficient paths to customers.

• Direct consumer relationships: DTC brands with first-party data.
• Enterprise distribution: Salesforce AppExchange, AWS Marketplace.
• Embedded distribution: Stripe Terminal (in hardware), Plaid (in banking apps).

7. Brand

Customer preference built over time.

• B2C: Nike, Apple, Coca-Cola.
• B2B: Rare as a primary moat; usually secondary to technical or distribution moats.
• Brand is usually the most expensive moat to build.

Moat signals for VCs

1. Retention: High NRR signals switching costs and/or product love.
2. Organic growth: Suggests network effects or brand.
3. Gross margin stability: Points to pricing power.
4. Customer concentration shrinking: Platform dynamics at work.

Common moat mistakes

1. Confusing features with moats: “AI-powered” is not a moat.
2. Assuming first-mover advantage is permanent: It often isn’t.
3. Underinvesting in moat-building: Focusing on growth without strengthening defensibility.
4. Overstating moat depth: Competitors often replicate faster than expected.

Practical takeaway

1. Founders: Identify which moat you’re building within the first 24 months and optimize your roadmap for it.
2. Investors: Moat analysis is more robust than TAM analysis for diligence.
3. Operators: Revisit moat assumptions annually; technology cycles can change them.

Further reading

• NVCA member research: https://nvca.org/