Stop Chasing PMF: Build Growth Loops

TL;DR: PMF is a post-hoc story. Real scale comes from loops (creation → distribution → conversion → retention) plus moats (lock-in, exclusivity, deals, capital).

The myth: Find PMF and growth becomes inevitable. The reality: Early traction ≠ fit. It's distribution—your product spreads itself because users can't help but share.

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What PMF Misses

We tell "PMF" after the fact. The winners didn't luck into love; they engineered inevitable sharing.

• Airbnb grew by hijacking Craigslist distribution.
• Dropbox grew by referral loops (free space for invites).
• Slack grew by team invites baked into the workflow.

The pattern isn't "people loved it." It's "every use created the next user." That's a loop.

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The Loop Framework (10 Steps)

Design a system where one action triggers the next user—on repeat.

1. Core Action The single behavior you want repeated (e.g., create listing, send invite). Be literal.

2. Trigger The nudge: in-product prompts, deadlines, social proof, notifications.

3. Incentive Why act now? Status, money, progress bars, FOMO, competitive edge.

4. Creation What gets produced? Listing, post, invite, template, dataset.

5. Distribution Where does it travel? SEO, embeds, social, email, partners, exports.

6. Conversion Who sees it and joins? Obvious CTA, audience match, one-tap signup.

7. Retention What keeps them? Proprietary data, reputation, network ties, workflow dependency.

8. Exclusivity What's only here? Rights, inventory, API access, unique data.

9. Switching Cost What do they lose if they leave? History, followers, configs, integrations.

10. Instrumentation Measure A→B→C, K-factor, time-to-value, 7-day retention. Kill steps that don't move the loop.

45-minute workshop: Map your current flow into these 10 boxes. Circle any step that doesn't create the next user. Cut or rewire it.

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Lock-In & Exclusivity (Moats That Matter)

The companies that scale aren't just liked—they're hard to leave and hard to copy.

Lock-in

• Data: years of history, benchmarks, assets.
• Integration: APIs/webhooks in daily workflows.
• Network: followers, reviews, team roles.
• Learning: muscle memory, templates, certifications.

Exclusivity

• Supply: inventory/talent/content you can't get elsewhere.
• Rights: licenses, geography, partnerships.
• Data: proprietary datasets, comps, market intel.
• Capital: subsidies, inventory float, payment terms.

Design at least one lock-in and one exclusivity per loop.

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Examples & Pitfalls

Loops that work

• Marketplace: buyers → attract sellers → attract buyers (compounding supply).
• Content/SEO: creator posts → ranks → new creators see success → they post.
• Referral: invite for reward → invitees see reward → they invite too.
• Data flywheel: more users → better model/product → attracts more users.

Pitfalls

• Spammy shares (benefit you, not the user).
• 5-step "share" flows (friction kills loops).
• Rewarding vanity, not value (likes vs revenue/time saved).
• Copy-pasting loops across unlike models.

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Designing Switching Costs (Ethical Retention)

Make staying the rational choice by banking value over time.

Data costs

• Transaction history, analytics, saved configs.
• Benchmarks, cohorts, performance over time.
• Integrations and automations.

Network costs

• Reviews, followers, teams/permissions.
• Shared docs/spaces, communication history.

Learning costs

• Shortcuts, templates, custom workflows.
• Badges/certs signaling expertise.

Ship features that grow these balances every week.

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The 3 Fast Wins (ship this week)

1. Embed & Export Make creations travel: public pages, share cards, CSV/PDF exports with attribution links.

2. Native Invites Replace manual "add teammates" with inline invites at the moment of need (share, approval, payment).

3. Proof Pages Auto-generate public "proof" (profiles, portfolios, comps) that rank in search and link back.

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Checklist (before launching any feature)

• [ ] Does this make sharing inevitable, not optional?
• [ ] What do users create that leaves the app and pulls others back?
• [ ] Which lock-in and exclusivity does this add?
• [ ] What does a user lose if they switch?
• [ ] Can we measure viral coefficient and time-to-value?
• [ ] Which step in A→B→C became shorter after this ship?

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FAQ

PMF vs distribution? PMF is a narrative about fit. Distribution is a mechanism that manufactures users. Airbnb's "fit" rode a Craigslist distribution hack.

Examples of loops? Marketplaces (supply ↔ demand), content/SEO (publish → rank → publish), referral (invite → reward → invite), data (usage → better results → more usage).

How do switching costs retain users? By accruing data, network, and learning that's painful to abandon—without dark patterns.

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Want this baked into your MVP?

We run 5-day sprints ($7,500) and $750 quick builds credited if you upgrade within 14 days.

Quick Build ($750) • Full Sprint ($7,500)

Internal links:

• The Anti-Graveyard Roadmap
• The One-Idea Rule
• Go/No-Go: 3 Questions
• The 5-Day MVP Scope
• Tiny MVPs That Convert