Product-Led Growth

Turn the product into the growth engine: get users to value fast, keep them coming back, and let usage itself acquire the next user. This skill maps the tactics for activation, monetization model, viral loops, habit design, community, and pre-launch validation, and tells you which one a given symptom calls for.

When to use this

Reach for PLG when the lever is inside the product experience, not outside it. Trigger signals:

• Activation gap: users sign up but never reach value; retention drops right after signup;

40-60% of signups never activate; empty first-screen states.

• Model decisions: choosing or fixing freemium vs free trial; a free tier bleeding users

without converting; where to draw the free/paid line.

• Monetization inside the flow: configurable tiers/seats/defaults; team or collaboration

products where you could add value now and bill later.

• Virality / referrals: network-effect products; invitations exist but nobody sends them;

wanting cheaper, higher-quality acquisition from happy users; questions about K-factor or viral cycle time.

• Retention: engagement spikes at signup then decays; a product that needs repeat usage to

deliver value.

• Community: an engaged early base, creation/extensibility (plugins, templates), or a niche

where users already gather.

• Pre-launch: validating demand or a niche before writing code; deciding what to gate.
• Strategy guardrails: "should I copy this competitor feature", "how do I win a crowded

market without bloating the flagship."

When NOT to use this (reach for instead)

• To measure whether a PLG change worked (activation threshold, experiment cadence, cohort

comparison, RICE prioritization) use research/analytics-data. PLG designs the intervention; analytics-data proves it moved the number.

• To lift checkout/landing conversion on existing traffic (page CRO, strategic checkout

friction, tripwire offers) use conversion-cro. PLG friction qualifies and activates users; CRO friction converts existing intent.

• To keep and expand users after activation (lifecycle emails, churn-save, win-back,

expansion revenue) lean on retention-lifecycle. PLG's habit loop starts the retention story; retention-lifecycle runs the ongoing program.

• To decide IF product-led is even your motion (channel-market fit, positioning, the Five

Fits) that is a strategy-fundamentals question.

How this works (decision path)

Diagnose by where the funnel is breaking, then pick the play.

1. Not sure you should build it yet? Start with presell/validation. Take refundable

deposits against a build threshold before writing code.

1. Users never reach value? This is the most common failure. Work the activation stack:

map the aha moment, deliver value before signup where you can, then redesign onboarding backward from the first win.

1. Value delivered but they don't come back? Design a habit loop (trigger, action,

variable reward, investment).

1. Retained but not spreading? Add a viral / referral motion, timed after the aha

moment (an invite before the user values the product converts poorly).

1. Growing but leaving revenue on the table? Set opinionated defaults and invite-now-

bill-later flows; choose the right freemium vs trial model.

1. Want a compounding, low-cost engine? Build community and free standalone on-ramp

products.

1. Tempted to copy a competitor? Run the feature-adaptation test first, then feed the

result to analytics-data to measure it.

Two cross-cutting principles: friction is a tool, not always the enemy (deliberate friction qualifies and commits users), and time every ask after value is felt, never before.

The plays

Activation and onboarding

• Design onboarding to the aha moment (core value → journey → obstacles → 4 principles)
• Execute the activation-gap fix (Bowling Alley bumpers, reverse-engineer the first win, gamify commitment)
• Deliver value before signup (one familiar input, instant shareable output, video demo ladder)

Monetization model and defaults

• Choose freemium vs free trial with the data, then tune trial conversion
• Grow revenue with opinionated defaults + invite-now-bill-later

Virality, invitations, and referrals

• Pick your virality type (pull/content/WOM/push) and instrument K-factor + cycle time
• Engineer the invitation asset (Slack-style invite email, invite-gating, manual WOM)
• Build a referral program that converts (incentives, timing, swipe copy, 3-phase rollout)

Retention and habit

• Build a habit loop with the Hook Model, applied ethically

Community and on-ramps

• Stand up a community growth loop (showcase power users, Discord feature-voting → ship visibly)
• Win saturated markets with free standalone on-ramp products

Friction as a tool

• Use deliberate friction to qualify, gate, and manufacture commitment

Validation and adaptation (pre-build guardrails)

• Validate a niche with real refundable deposits against a build threshold
• Run the three-question test before copying a competitor's feature

Key numbers & benchmarks

• Activation: 40-60% of signups never activate. Most SaaS loses ~95% of new users within 90

days, most of it in onboarding. Lifting the share of signups who hit the first win by 10% beats a 50% jump in raw signups.

• Model economics: freemium roughly halves CAC, delivers ~20% better net retention, and ~2x

NPS; free trials show ~15% lower CAC. Freemium needs a large TAM to fund the free tier.

• Trial conversion tactics: personalized 1-on-1 demos moved one product from 5% to 9%;

end-of-trial discounts up to 60% off for 3-6 months are common.

• Free-sample psychology: retail sampling lifts purchases up to 2000%; even laggard grocery

categories see +71%. The same mechanic applies to a free first result before signup.

• Referrals: 83% of customers say they'd refer, but only ~29% do within 12 months. Referred

customers show ~18% lower churn, ~16% higher LTV, ~37% higher retention. Sample structures: two-sided "Give $20, Get $20"; tapering "$30 first referral, then $10 each." Favor value (product units, upgrades, extended trials) over small cash.

• Virality: K-factor (viral coefficient) = new users per existing user; >1.0 signals viral

potential, >2 signals runaway. Viral cycle time must beat churn to compound. Under ~10 customers/month there is too little volume for word-of-mouth to catch.

• Community proof: one community-led product grew 100 → 1K → 5K → 100K+ users over ~2 years,

~90% from word-of-mouth, with no VC funding.

• Micro-SaaS validation target: vertical niches of 200-2,000 customers at $50-500/mo, too

small for VCs but viable for a domain expert plus AI. Validate with a public build threshold (e.g. "build if 50 pre-orders").

Reference library

Every play above, in full.

Frameworks for the activation gap, Bowling Alley bumpers, reverse-engineering the first-win, and gamified onboarding

The strategy

40-60% of signups never activate, and lifting the share of signups who hit their first win by 10% beats a 50% jump in raw signups. These frameworks turn "improve onboarding" into a concrete process: define the activation metric, reverse-engineer onboarding from it, and use structured bumpers + gamification to pull users to the aha moment. Companion to the onboarding-activation card (which covers the aha-moment mapping); this card is the execution layer.

When to use it

Any product with a signup → value gap and measurable early drop-off. Use when you know activation is the problem but not which steps to cut or add.

How to execute (steps)

1. Define the activation "lightbulb moment." Find the earliest single action that separates retained from churned users. Build onboarding backward from it and delete every non-essential step.
2. Kill empty states. Pre-fill sample data/templates so the first screen already shows value (Duolingo shows a real translation pre-signup; Canva opens on a customizable template). Cut cognitive, emotional, and interaction friction.
3. Run the Bowling Alley framework:

• Phase 1, color-code every onboarding step: green = keep, yellow = delay, red = remove.
• Phase 2, product bumpers: tours, progress bars, checklists, tooltips, empty-state guidance.
• Phase 3, conversational bumpers: welcome, case-study, and trial-expiry emails.

1. Teach by doing, not telling (do > show > explain). Guided practice beats tutorials (Grammarly's dummy page); stagger feature intros; personalize via 1-on-1 demos or choose-your-adventure flows.
2. Gamify commitment. Force a non-dismissable goal-setting step (Duolingo's 3/7/14/30-day streak picker raised chosen goals + retention with no extra drop-off), and reward onboarding-task completion with extra trial days (Deputy) to push users to the aha moment where conversion spikes.

Notes / caveats / examples

• 40-60% never activate + Bowling Alley; 10%-first-win-beats-50%-more-signups + reverse-engineering + empty-state fixes; do>show>explain; forced goal-setting; trial-day rewards.
• Caveat: forced steps only work if they accelerate the first win, a mandatory step that delays value makes the gap worse.

→ Skill conversion note

Strong skill candidate: "Diagnose my activation gap." Input = onboarding steps + retention cohort data. Output = the activation metric, a backward-designed step list (green/yellow/red), a bumper plan, and 1-2 gamification hooks.

Embed community into the product, showcase power users, run a Discord product-dev lab, and let users become the brand

The strategy

Community isn't a marketing channel bolted on the side, for PLG products it can be the growth engine. When users create, connect, and shape the roadmap inside a community, they develop emotional investment that produces retention and near-free word-of-mouth. "Users are the brands."

When to use it

Products with creation/extensibility (plugins, templates, integrations), an engaged early user base, or a niche where users already gather. Especially powerful for bootstrapped/no-VC growth.

How to execute (steps)

1. Highlight power-user creations. Feature what users build on your platform (Figma plugins), it validates the product, gives creators status, and shows prospects what's possible.
2. Connect users to each other. Build or foster a space where users help each other (Optimizely's developer community) so value compounds beyond your team.
3. Run a Discord as a product-dev lab. Let users suggest and vote on features, then ship them visibly so contributors feel ownership. FX Replay grew 100 → 1K (10 weeks) → 5K (8 months) → 100K+ (2+ years), ~90% from word-of-mouth/community, with no VC.
4. Meet users where they already are, then graduate to owning the space: join existing communities first, and later acquire or build your own.

Notes / caveats / examples

• FX Replay's Discord-driven curve + ~90% WOM, no VC; Figma plugin showcase, Optimizely dev community, "users are the brands," community acquisition.
• Caveat: community requires real, visible responsiveness, shipping user-voted features is what converts a chat room into a growth loop; an ignored forum does the opposite.

→ Skill conversion note

Skill candidate: "Stand up a community growth loop." Input = product + where users gather. Output = a power-user showcase plan, a Discord feature-voting → ship-visibly loop, and a join-then-own community sequence.

Grow revenue with opinionated defaults and invite-now-bill-later, set the 90% choice, keep the override easy

The strategy

Defaults quietly steer the vast majority of users, so the default is the decision for the 90% case. Setting revenue-favorable, sensible defaults, and deferring billing until value is proven, lifts average revenue without adding friction, as long as the override stays frictionless (defaults loosely held, not forced).

When to use it

Any product with configurable pricing, tiers, seat counts, or setup choices, and any team/collaboration product where you can let users add value now and bill later.

How to execute (steps)

1. Pre-fill intelligent defaults for the 90%+ case. Airbnb assumes ~$289/night + 2BR + 7 nights to show income potential before any form; Uber defaults the start location to current location (99%+ of rides); Canva defaults to templates. Show value first, ask for input second.
2. Set revenue-nudging defaults you can still change. Patreon changed its default tier from "$1" to "$1, $5" and lifted the average tier price. Keep the override obvious so it reads as helpful, not manipulative.
3. Use opt-out where reversal is harder than the action. Figma defaults to anyone-can-invite + first month free; because revoking existing access is harder than denying it up front, seats (and MRR) rise.
4. Invite now, bill later (free-to-paid). Let users add collaborators immediately and email the admin when they exceed the plan limit (Figma). Loss aversion + the friction of removing seats means they rarely downgrade.
5. In the commit step, pre-select the 80% option, split big actions into micro-steps, and reveal features gradually to cut decision points.

Notes / caveats / examples

• Airbnb/Patreon/Figma/Uber/Canva defaults; invite-now-bill-later Figma; commit-phase defaults + micro-steps.
• Caveat: "loosely held" is the ethical line, a default that's hard to escape is a dark pattern and erodes trust.

→ Skill conversion note

Skill candidate: "Set my opinionated defaults." Input = the config/tier/seat choices in the product. Output = a recommended default per choice (the 90% option), which ones to make opt-out, an invite-now-bill-later flow, and an override-visibility check.

Before copying a competitor's feature, run the three-question adaptation test, why it works there, why it might fail for you, what to change

The strategy

Copying a rival's winning feature verbatim usually fails, because the feature works in that product's context, its audience, motivation, and surrounding mechanics. Before borrowing anything, interrogate the mechanism and adapt it to your context rather than cloning the surface.

When to use it

Any product/growth decision to add a gamification, retention, or engagement feature you saw work somewhere else. A guardrail against cargo-culting competitor tactics.

How to execute (steps)

1. Ask why it works there. What underlying user motivation or context makes the feature succeed in the original product? (A moves-counter works in a casual puzzle game because scarcity creates tension around a fun core loop.)
2. Ask why it might fail for you. Does your audience share that motivation? Does your core loop create the same tension, or will the mechanic feel arbitrary/punishing?
3. Ask what to adapt. Reshape the mechanism to fit your context instead of transplanting it. Duolingo's copy of Gardenscapes' moves-counter flopped until it was reworked into leaderboards and streaks, which fit the motivation of language learners.
4. Ship the adapted version, not the clone, and measure against your own activation/retention metric.

Notes / caveats / examples

• Duolingo's failed Gardenscapes moves-counter → successful leaderboards/streaks rework ("Feature adaptation & rule of 3").
• The lesson generalizes: the transferable asset is the mechanism and the motivation it serves, never the UI.

→ Skill conversion note

Skill candidate: "Adapt a competitor feature." Input = the feature + its source product + your audience. Output = the underlying mechanism, a fit/fail assessment for your context, and a concrete adapted version to build and test.

Win a saturated market with free standalone on-ramps, ship independent, zero-switching-cost products that funnel to the core

The strategy

In a crowded market, don't fight for the core purchase head-on and don't bloat the flagship with features. Instead, ship (or acquire) separate, free, standalone products that solve an adjacent job with zero switching cost, each becomes an independent on-ramp that funnels users into the core platform.

When to use it

An established product in a saturated category, or any platform that could own adjacent jobs-to-be-done. Best when you have the resources to build/acquire a genuinely useful standalone tool.

How to execute (steps)

1. Identify adjacent jobs your core users already do in other tools (calendar, email, notes), the surrounding workflow.
2. Build or acquire a standalone product for that job (Notion acquired Cron and Skiff).
3. Rebrand and ship it free and independent (Notion → Calendar and Mail) so a new user can adopt it with zero switching cost, without committing to the core platform first.
4. Funnel to the core. Design the standalone product so natural usage surfaces and pulls users into the flagship, the free tool is the top of a new funnel, not a side project.

Notes / caveats / examples

• Notion acquiring Cron/Skiff, rebranding to Calendar/Mail, shipping them free and independent as zero-switching-cost entry points ("Notion Mail: winning saturated markets").
• Why it beats feature-bloat: separate on-ramps expand top-of-funnel and reach users who'd never sign up for the core product first, whereas cramming features into the flagship raises its adoption cost.

→ Skill conversion note

Skill candidate: "Map my on-ramp products." Input = core product + adjacent user workflows. Output = candidate standalone tools (build vs acquire), how each stays zero-switching-cost, and the funnel path from on-ramp to core.

Choose freemium vs free-trial with the data, and convert trials with onboarding, check-ins, gating, and end-of-trial offers

The strategy

Freemium vs free-trial is a data decision, not a preference. Freemium roughly halves CAC, delivers ~20% better net retention, and ~2× NPS; free trials show ~15% lower CAC. The right choice depends on your friction, stickiness, virality, and market size, and once you pick trials, a handful of specific tactics drive the conversion.

When to use it

Designing or revisiting a SaaS monetization model, or when a free tier / trial is bleeding users without converting them.

How to execute (steps)

1. Score four factors before choosing: friction (how fast users reach value), stickiness (do they stay), virality (do they invite others), and market size (freemium needs a big TAM to fund the free tier).

• Freemium wins for low-friction, sticky, viral products in large markets: ~½ CAC, ~+20% net retention, ~2× NPS.
• Free trial wins when value is fast to demonstrate but costly to give away indefinitely: ~15% lower CAC.

1. Align the free line to the buying cycle. Doopoll used "unlimited free surveys, first 10 responses free, £39/mo after", free where it hooks, paid exactly at the value moment.
2. Convert trials with proven tactics: personalized onboarding (Funnel CRM went 5%→9% via 1-on-1 demos), behavior-triggered emails (Adobe), a midpoint 15-minute check-in (Nextiva), feature gating, and end-of-trial discounts (Dunnly offered up to 60% off for 3-6 months).

Notes / caveats / examples

• Freemium vs trial stats; trial-conversion tactics + Funnel CRM 5→9%; buying-cycle-aligned freemium + Doopoll, whose Notion-gallery LP rebuild also lifted conversion 4%→14% and drove MRR +800% over 6 months.
• Caveat: freemium's lower CAC is offset by the cost of serving free users, it only pays off with a large market and strong free→paid triggers.

→ Skill conversion note

Skill candidate: "Pick + tune my free model." Input = friction/stickiness/virality/market answers. Output = a freemium-vs-trial recommendation, where to draw the free line against the buying cycle, and a trial-conversion tactic stack (onboarding, check-in, gating, end-of-trial offer).

Friction as a Service, use deliberate friction to qualify users, gate features, and manufacture commitment

The strategy

Not all growth comes from removing friction. Deliberately placed friction filters for serious users, gates features behind earned participation, and manufactures commitment, the key is friction that focuses attention rather than frustrates. This is the PLG counterpart to the CRO strategic-friction card: here friction qualifies and activates users rather than lifting checkout conversion.

When to use it

Pre-product (validating demand, gating a waitlist) and post-product (deciding what to gate behind participation or usage). Especially when a fully open free tier attracts low-intent users who never activate.

How to execute (steps)

1. Pre-product: gate signups to qualify demand. Use designed early-access landing pages + surveys/calls instead of an open free tier; skip free tiers and hide pricing while you experiment. Airbnb hand-photographed listings (high-friction, unscalable) and doubled monthly revenue.
2. Post-product: usage-gate unlocks. Require participation to earn features, Hacker News requires karma to downvote; MidJourney unlocked its web app only after a user generated 10,000+ images.
3. Collaboration-gate rewards. Tie rewards to network actions (Dropbox's referral storage).
4. Add support friction that improves quality. Arc requires a screenshot with every bug report, the extra step filters noise and yields better reports.
5. Test the rule: every added step needs a reason it focuses the user (commitment, quality, qualification). If it only annoys, remove it.

Notes / caveats / examples

• All examples ("FaaS: Friction as a Service"): Airbnb hand-photography, HN karma gating, MidJourney 10,000-image gate, Dropbox referral storage, Arc screenshot-with-bug-report.
• Caveat: friction-as-filter trades volume for quality, right for high-intent/premium products, wrong when you need broad top-of-funnel reach.

→ Skill conversion note

Skill candidate: "Design qualifying friction." Input = funnel + activation problem. Output = where to add pre-product gates vs open access, which features to usage-gate, and a focus-vs-frustrate test for each added step.

Build retention with the Hook Model, trigger → action → variable reward → investment, applied ethically

The strategy

Sustainable retention comes from products that build a habit loop, not from one-off engagement pushes. Nir Eyal's Hook Model, trigger → action → variable reward → investment, is the design pattern behind the stickiest consumer products, and it can be engineered into your product deliberately (and ethically). Complements the viral and activation cards: virality brings users in, activation gets them to value, the hook keeps them coming back.

When to use it

Any product that needs repeat usage to deliver value or monetize (content, tools, social, health/habit apps). Use when engagement spikes at signup then decays.

How to execute (steps)

1. Trigger, design both external triggers (notifications, emails, placements) and, over time, internal triggers (an emotion or situation that makes the user think of your product unprompted).
2. Action, make the core action as easy as possible to perform in response to the trigger; reduce it to the minimum viable behavior.
3. Variable reward, deliver a reward with an element of unpredictability (new content, social validation, a fresh result). Variability is what sustains attention; a perfectly predictable reward loses its pull (Instagram/TikTok feeds are the exemplars).
4. Investment, prompt the user to put something in (data, content, connections, configuration) that both improves the next experience and increases switching cost, loading the next trigger.
5. Loop it and use it ethically. Each pass should make the next one more likely. Apply to genuinely user-serving value, not compulsion for its own sake.

Notes / caveats / examples

• Hook Model framing + Instagram/TikTok exemplars, "use ethically" caveat.
• Caveat: the same loop that builds a helpful habit can build a harmful one, the investment and reward should serve the user's own goals.

→ Skill conversion note

Skill candidate: "Map my habit loop." Input = the core repeat action + current triggers. Output = a filled Hook Model (external + internal triggers, simplified action, a variable-reward idea, an investment step) plus an ethics check on the loop.

Design onboarding that activates users to their "aha" moment using a 4-step map and four onboarding principles

The strategy

Most SaaS apps lose 95% of new users within 90 days, and most of that loss happens during onboarding. Fix it by mapping the exact path to your product's core value, finding what blocks users from reaching it, and designing onboarding to remove each obstacle, while making users educated, enticed, low-friction, and productive.

When to use it

Any product with a signup-to-value gap: SaaS, apps, tools. Especially urgent when activation/retention drops off right after signup.

How to execute (steps)

1. Identify the core value users get from the product.
2. Map the user journey required to experience that value.
3. Find the obstacles blocking users. Known ones = high-effort or tedious steps. Hidden ones need research: record in-app sessions with Hotjar (or invite users in to observe physical-product use); watch for inefficient paths, broken flows, and repeated deletions/restarts. (Twitter found users who didn't follow ≥5 people right after signup rarely returned, so they forced following 5 interest-matched celebrities.)
4. Design onboarding to clear each obstacle using four principles:

• Educational, immediately answer "what's the value and how do I get it?" via a productive walkthrough (one feature at a time, e.g. start with template selection), a ≤60-second no-fluff captioned video, a full course only if genuinely complex (Webflow University), or sample data + sparse tooltips. Skip education entirely if the product is self-evident.
• Enticing, visualize the magical/max-value moment to pull users through boring steps. Only ask for an action after proving capability (prompt the Chrome extension after the web app hooks them). When value is intangible, use a concrete benefit statement (quit-smoking app: "~15% finish onboarding; once finished, 85% chance of a lifelong quit").
• Low-friction, reduce total workload (pre-fill inputs with smart defaults; defer non-essential asks), reduce perceived complexity (GIFs, break actions into discrete steps), reduce choice anxiety (fill-in suggestions; explain non-obvious fields, e.g. "inviting coworkers lets you share work instantly"). Make the next step obvious and easy at every point.
• Productive, users should exit onboarding having accomplished something they care about (an outlined project + team invited; a cleaned inbox), for a real dopamine hit, not an empty state.

Notes / caveats / examples

• Webflow full model: ask 2-3 quick personalizing questions → drop the user into the tool for ~30 seconds of hands-on exploration → at the 30-second mark auto-open a video menu (prevents overwhelm) → first video is a 60-second timelapse of a finished build → later videos teach power-user steps.
• Build virality into onboarding. Three modalities: inherent (product needs others, PayPal, Dropbox, Zoom, Slack, or creates shareable content; just get out of users' way); word-of-mouth (needs an elegant pain solution + enough volume; under ~10 customers/month there's too little kindling); artificial (incentivized referrals presented right after a delight moment, reward with core product value like Dropbox's extra GB, not cash; for non-incrementable products the reward must be big: free product after 5 referrals, or 3 months free for expensive subscriptions).
• Viral coefficient = referrals per user × % of invited users who accept; >1.0 signals viral potential. Also minimize lag between signup and referral.

→ Skill conversion note

Becomes an "onboarding teardown" SKILL.md: given a product's core value + signup flow, it maps the value journey, flags friction against the four principles, and proposes an educational/enticing/low-friction/productive redesign plus a referral hook.

Deliver value before signup, one familiar input, instant output, and a video demo ladder that defers the account

The strategy

The fastest way to activate users is to show value before asking them to sign up. Minimize time-to-first-value with a single familiar input that produces an instant, visible, shareable result, then gate full features (and the account) behind that first "wow." Free-sample psychology explains why: sampling drives huge downstream purchase intent.

When to use it

Any tool where the core value can be demonstrated in one action, and any SaaS currently forcing signup before the user sees anything work.

How to execute (steps)

1. Lead with one familiar input. Replace the signup wall with a single search-bar-style field: Replit's Mad Libs 3-blank homepage, Creati's real-time flowchart preview, MidJourney moving off Discord to a search bar. Defer payment/signup until after value is delivered.
2. Deliver value first, gate later (two-stage TTV). Give real output before account creation (Airbnb location search, SimilarWeb's instant site analysis, Loom/Miro/Calendly), then gate full features behind signup.
3. Exploit free-sample psychology. Make the first output an instant, visible, shareable "dopamine hit." Retail free samples lift purchases up to 2000%, and even laggard grocery categories see +71% after sampling, the same mechanic applies to a free first result.
4. For sales-heavy products, replace 1:1 demos with a video ladder. Ungated 1-min explainer → ungated 2-3 min demo → ungated deep-dive → gated weekly live demo (Otter.ai) lets users self-educate and reach value without booking a call.

Notes / caveats / examples

• Single-familiar-input + free-sample stats (Replit/Creati/MidJourney); two-stage TTV (Airbnb/SimilarWeb/Loom); video demo ladder / Otter.ai.
• Complements the activation-frameworks card, this one is specifically about pushing value before the signup gate.

→ Skill conversion note

Skill candidate: "Design my pre-signup value moment." Input = the product's core action. Output = a single-input homepage concept, the instant/shareable first output, the exact feature to gate behind signup, and (for sales products) a 4-rung video demo ladder.

Validate a niche with real deposits, not opinions, pre-sell against a build threshold before you write code

The strategy

Free feedback is cheap and unreliable; money is the only honest signal of demand. Before building, validate a narrow niche by taking real (refundable) early-access deposits against an explicit build threshold, "I'll build it if 50 people pre-order." This is especially powerful for the vertical micro-SaaS opportunity: small, unsexy markets too small for VCs but ideal for a domain expert plus AI.

When to use it

Pre-build validation for a new product or vertical, and picking which niche to pursue. Ideal for solo founders and small teams targeting focused B2B niches.

How to execute (steps)

1. Pick a vertical micro-SaaS niche. Target 200-2,000 customers at $50-500/mo in spaces too small for VCs (HVAC scheduling, dental billing, construction compliance). A domain-expert-plus-AI beats a generalist coder here, pick a niche you understand.
2. Stand up a landing page + a mocked UI. Use AI to mock the interface so buyers see a concrete product, not a vague promise.
3. Take real early-access deposits. Collect (refundable) deposits, not email signups, money measures commitment; feedback is free and cheap.
4. Set an explicit build threshold. Commit publicly to a bar ("build if 50 pre-orders"). Hitting it validates demand and funds the build; missing it saves you months on a product nobody wanted.

Notes / caveats / examples

• Pre-sell-with-deposits + build-threshold ("Audience-First Companies"); vertical micro-SaaS thesis, 200-2,000 customers at $50-500/mo, domain-expert-plus-AI ("The Solo Founder Era").
• Related to the CRO refundable-deposit tripwire (issue #273), same commitment mechanic, applied here to validate demand rather than convert existing traffic.

→ Skill conversion note

Skill candidate: "Pre-sell to validate." Input = niche + rough offer. Output = a landing-page + mocked-UI spec, a refundable-deposit pre-order flow, and a build-threshold with a public commitment plan.

Build a referral program that converts, incentive structures, timing, friction-removal, and a 3-phase rollout

The strategy

83% of customers say they'd refer, but only 29% actually do within 12 months, the gap is friction and weak incentives. Close it with a deliberate program: pick one outcome, design the right incentive structure, ask at the right moments, remove all friction with swipe copy + one-click sharing, and roll out in three phases (manual test → proven → scale with software). Prerequisite: the product must already be recommendable, referrals amplify satisfaction, they don't create it.

When to use it

• You have real product-market fit and want cheaper, higher-quality acquisition.
• Existing customers already recommend you organically and you want to systematize it.

How to execute (steps)

1. Pick one primary outcome: brand awareness, lower CAC, urgency, social proof, or revenue.
2. Find existing referral sources: GA (Acquisition > All Traffic > Source/Medium), Twitter Advanced Search for bracketed product mentions, LinkedIn (company name, past-month, latest), and a "Where did you hear about us?" onboarding survey.
3. Create shareable moments: ecommerce = premium unboxing + post-purchase how-to emails; SaaS = micro-moments (celebration animations, progress bars) + sharing that needs no registration.
4. Choose an incentive structure: one-sided (lower CAC, weaker pull), two-sided ("Give $20, Get $20", higher CAC, better conversion), tiered (5 refs = stickers → 1,000 = HQ visit; distributes cost, needs fraud protection), or leaderboard (monthly reset, needs tracking).
5. Set amounts to control CAC: e.g. "$30 for first referral, then $10 each after." Favor value over cash (product units, upgrades, extended trials, personal gift cards), most people don't want small cash. Cash/discounts work best for ecommerce and only when "significant."
6. Ask at the right time, repeatedly: after a high NPS score, at renewal, when they engage with marketing, after the first milestone (Duolingo's first lesson), or 1+ month post-onboarding. Never ask at the end of the sales process before they've used the product, and never just once.
7. Use the original sale's channels: ecommerce = email/SMS/post-purchase; high-ticket SaaS = phone/in-person then email; self-serve SaaS = in-app + push; media = newsletter.
8. Remove friction: write 3-5 pre-written swipe messages (peer-to-peer tone, "avoid messaging that feels like a marketer wrote it"), enable one-click sharing (email/Twitter/FB/SMS/LinkedIn/copy link), and build one referral landing page per persona that leads with "what's in it for me," has a single CTA (test benefit- vs. incentive-focused), and hides FAQ behind expandable sections.
9. Roll out in three phases: Testing (top 10-20% engaged customers, individualized emails, fulfill incentives manually, 1:1) → Proven (remove friction, low-cost automations) → Scaling (deploy software like Rewardful/GrowSurf/Referral Rock, add conversion feedback loops + fraud detection, monitor CAC vs. other channels).
10. Distribute post-launch via email (announcement + receipts + signatures), website (modal/banner/dashboard, not buried in settings), social (recurring case studies + relevant communities), and long-term influencer pushes.

Notes / caveats / examples

• Quality of referred customers: 18% lower churn, 16% higher LTV, and 37% higher retention than non-referred.
• Real structures: Bloomist $35/$35 (min $50 purchase); Zoma $50 gift card / $150 off after sleep trial; Fiverr 10% of first order (up to $100) both sides; Duolingo 1 week Plus (one-sided); Wealthsimple $10k managed free both sides; Whoop 1 month each + 2 bonus; The Hustle tiered (ebook → founder meeting); Airtable $10 credits/invite.
• Fraud control for tiered/leaderboard: track conversion by referrer, flag suspicious patterns, require verified emails.
• Tools: Viral Loops + KickoffLabs (landing pages/templates); Rewardful, GrowSurf, Referral Rock (referral software).

→ Skill conversion note

Becomes a "referral-program builder" prompt: input product + CAC target + sale channel → output the incentive structure + amounts, the ask-timing triggers, swipe-copy variants, a per-persona landing-page brief, and the 3-phase rollout checklist.

Engineer the invitation itself, model Slack's invite email, gate signup behind friend invites, and manufacture word-of-mouth

The strategy

The viral-loop-types card covers the theory (loop types, K-factor, viral cycle time). This card is the concrete mechanics of the invitation, the single asset that determines whether a loop actually spins: how the invite email is structured, whether sharing is required to onboard, and how to seed word-of-mouth manually when the loop is young.

When to use it

Any product with network effects or a referral/invite motion, especially early on when the loop needs manual priming, or when invitations exist but few users send them.

How to execute (steps)

1. Model the invite email on Slack's coworker-invite (per Elena Verna's analysis): make the network effect obvious, the recipient should immediately see who invited them and why the product is better with their team in it.
2. Gate signup behind friend invites for network effects. Require new users to invite (e.g. 4) friends to complete onboarding; auto-generate the invite texts to remove friction and create "insider" status. A dual-score design (e.g. Beli's "Rec Score" vs "Friend Score") drives off-app conversation and pulls invitees back.
3. Manufacture word-of-mouth manually when young. Do unscalable, memorable things that get talked about, Chewy painted 100+ customers' pets and mailed the portraits, generating organic WOM far beyond the cost.
4. Time the ask after the aha moment, not at first login (see the viral-loop-types card), an invite before the user values the product converts poorly.

Notes / caveats / examples

• Gate-behind-4-invites + dual Rec/Friend Score (Beli); Slack invite-email structure per Elena Verna's analysis; Chewy pet-portrait WOM.
• Distinct from the viral-loop-types card (theory + metrics) and the referral-program card (incentive design), this is specifically the invitation asset and its priming.

→ Skill conversion note

Skill candidate: "Write my invite mechanics." Input = product + network-effect logic. Output = a Slack-style invite email, an optional invite-gate spec (how many, auto-generated copy), and 1-2 unscalable WOM stunts to seed the loop.

The four types of virality (pull, content, word-of-mouth, push) and the metrics that govern them

The strategy

Virality is a business-design problem, not a marketing stunt. There are four distinct types (pull, content, word-of-mouth, push) and two governing metrics (K-factor and viral cycle time). Sustainable virality is product-embedded and depends on retention, sharing without stickiness is vanity.

When to use it

• Designing a growth loop into the product rather than hoping for a one-off viral moment.
• Deciding which virality type your product can realistically support.

How to execute (steps)

1. Pick your virality type(s):

• Pull, product-embedded sharing that gets better as others join (Slack, Zoom, Dropbox, Spotify playlists, Venmo). Time invitations after the aha moment, not after first login.
• Content, posts/articles/videos shared across platforms (Instagram egg 55.8M likes; Dollar Shave Club 27M+ views).
• Word-of-mouth, organic recommendations (Allbirds, Hydro Flask; The Greatest Showman earned $314M largely on WOM after a weak opening).
• Push, exposure through visible usage (AirPods, Supreme, Tesla; "Powered by Stripe," "Created with Wix," branded packaging/stickers). Only works if users love the product enough to display it.

1. Design pull loops: make creation easy (Figma sharing, Loom recording), make sharing easy (one-click invite links), and design for collaboration/transactions that require recipient action (GitHub commits, Eventbrite registration). Use "land and expand", one user invites the team.
2. Get the timing right: invite after the aha moment; highlight value during onboarding so recipients don't drop out.
3. Instrument the metrics:

• K-factor (viral coefficient) = new users per existing user (3 conversions = k of 3); >2 = runaway potential. Limitation: ignores time and retention.
• Viral cycle time (VCT) = time from adoption to inviting others (TikTok = seconds; B2B = weeks). VCT must beat churn to compound.

1. Map the three-stage conversion path each share must clear: Receiving → Inception (recipient gets it) → Aha (recipient sees value) → Sharing (becomes an ambassador). Each stage needs its own motivation.

Notes / caveats / examples

• Three non-negotiables: don't chase silver bullets (one meme = short-term win, long-term loss); retention over acquisition (early "address-book spam" failed for lack of stickiness); respect K-factor's limits (use David Skok's viral formula/spreadsheet for rigor).
• Track active use, not likes/forwards, "virality is vanity, engagement and product value win."
• Frameworks cited: Andrew Chen ("virality is a business design problem"), Josh Elman (reach the right people → align with product value → drive the right actions).

→ Skill conversion note

Becomes a "viral-loop designer" prompt: input product type → output which virality type fits, the loop mechanics + invite-timing, and the K-factor/VCT targets needed to outpace churn.

From God of Skills: a curated, hand-tested directory of AI skills, prompts, templates and image style guides. Source: https://godofskills.com/skills/product-led-growth?ref=claude-skill