growth

Growth & Product-Led Growth

In PLG, the product is your best salesperson. This skill helps you design growth into your product — with concrete tactics and prompts you can hand to Claude Code.

Core Principles

• Growth is a system, not a hack. Build loops, not one-time campaigns.
• Activation is the most important metric. A user who never experiences value is already lost.
• Virality is engineered, not accidental. Design sharing into the product.
• Retention is the foundation. Growing on top of a leaky bucket is a losing game.
• For a solo founder: pick ONE growth lever, make it work, then add the next.

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The PLG Funnel

Acquisition → Activation → Retention → Revenue → Referral

The most common mistake: Founders focus on Acquisition first. Focus on Activation and Retention first — there's no point driving signups into a leaky bucket.

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Activation (Start Here)

Define Your Aha Moment

The specific action where users first experience core value:

Product Type	Example Aha Moment
Project management	Created first project + added a task
Email tool	Sent first campaign
Analytics	Saw first dashboard with real data
Design tool	Exported first design
Scheduling	Booked first meeting through the tool

Your aha moment: [Action that makes users say "I get it, this is useful"]

Drive Users to Aha Fast

Every screen between signup and the aha moment is a drop-off risk.

Tell AI:

Design the onboarding flow to get users to [your aha moment] in under 3 minutes:
1. After signup, skip the "check your email" screen — go directly to the product
2. Show a setup wizard (3-5 steps max) that collects only what's needed to deliver value
3. Pre-populate with sample data or templates so the product looks useful immediately
4. Add a progress checklist: "Complete your setup: ☑ Create [X] ☐ [Next step] ☐ [Final step]"
5. Show an empty state with a clear CTA on every empty page ("Create your first [X]")

Activation Emails

Pair your in-product onboarding with a 5-email welcome sequence that nudges unactivated users. See the email skill for the full welcome sequence template with ready-to-paste copy for each email.

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Acquisition Strategies

Pick ONE that matches your product. Don't spread across all of them.

Strategy	Best For	Effort	Time to Results
Free tool / calculator	Products that solve measurable problems	Medium	1-3 months
Template gallery	Products with customizable outputs	Medium	2-4 months
Content-as-product	Products in information-heavy spaces	High	3-6 months
Community-driven	Products with passionate niche users	High	3-6 months
Integrations	Products that connect to other tools	Medium	1-2 months per integration
Freemium	Products where free use drives word-of-mouth	Low	Immediate (but slow growth)

Tell AI:

Build a [free tool / template gallery / calculator] that:
- Solves a specific problem our ICP has (related to our product)
- Requires no signup to use
- Shows a teaser of our full product's value
- Includes a CTA: "Want more? [Product name] does this automatically."
- Is SEO-optimized so it attracts organic traffic

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Viral Loop Design

A viral loop has 4 parts: User gets value → Has reason to share → New user sees value → Converts → Loop repeats.

Viral Mechanics for SaaS

Mechanic	How It Works	Example
Collaboration invites	Product requires multiple users	"Invite your team to edit this"
Shared outputs	User creates something shareable	Reports, links, dashboards with "Made with [Product]"
Referral rewards	Incentivized invitations	"Give $20, get $20"
Public pages	User content is SEO-indexable	Public profiles, portfolios, pages
Embeds	Widget on user's site links back	Badges, chat widgets, forms

Tell AI:

Add a sharing/invite mechanic to our product:
- After a user completes [key action], prompt: "Share this with your team" or "Invite a collaborator"
- Make shared links show a preview of the output (not just a signup page)
- Add "Made with [Product]" branding on shared/public outputs with a link to our homepage
- Track invite sends, invite accepts, and invite-to-signup conversion

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Retention Mechanics

Build Habit Loops

Component	What It Is	Example
Trigger	What brings them back	Email digest, notification, calendar event
Action	What they do in the product	Check dashboard, respond to comment, update status
Reward	Value they get	New insight, progress indicator, completed task
Investment	What makes leaving harder	More data, more connections, more history

Tell AI:

Build retention mechanics into the product:
1. Weekly email digest: summarize what happened this week + one insight or action item
2. Activity notifications: "[Name] commented on your [item]" — not time-based ("It's been 3 days")
3. Progress indicators: Show users their cumulative value ("You've saved 14 hours this month")
4. Data investment: The more they use it, the more valuable their data becomes (history, reports, trends)

Feature Drips

Don't show everything on day 1. Reveal features as users are ready:

Tell AI:

Implement progressive feature disclosure:
- Week 1: Show only core features (the ones needed for the aha moment)
- Week 2: Surface advanced feature with a tooltip: "Now that you've [done X], try [advanced feature]"
- Week 3+: Unlock remaining features with brief explanations
- Gate premium features with a gentle upgrade prompt at the moment of need

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Metrics to Track

Set these up in your analytics tool (see analytics-instrumentation skill):

Stage	Key Metric	How to Calculate
Acquisition	Signup rate	Visitors → Signups
Activation	Activation rate	Signups → Completed aha moment
Activation	Time to aha	Average hours/days from signup to key action
Retention	D1/D7/D30	% of users returning on day 1, 7, 30
Revenue	Free-to-paid	Free users → Paying users
Referral	Viral coefficient	Invites sent × invite conversion rate

Tell AI:

Set up growth tracking:
- Track signup events with source attribution (organic, paid, referral, direct)
- Track [aha moment action] completion with timestamp
- Calculate time-to-activate for each user
- Build a daily dashboard showing: signups, activations, D7 retention, free-to-paid conversion
- Alert me if activation rate drops below [X]% or D7 retention drops below [Y]%

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Growth Experiments

When you want to improve a metric, frame it as a hypothesis:

1. Hypothesis: "If we [change], then [metric] will [improve] because [reason]."
2. Metric: What specifically will you measure?
3. Duration: Run for 1-2 weeks minimum, or until 100+ users have been through the flow.
4. Decide: Did the metric improve? Ship it or revert.
5. Document: Write down what you learned, even (especially) from failures.

For A/B test setup, implementation, and reading results, see the conversion skill's A/B testing section.

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Common Mistakes

Mistake	Fix
Focusing on acquisition before activation	Fix activation first — no point driving users into a broken onboarding
Building viral features nobody uses	Viral loops must be part of the core workflow, not a sidebar feature
Measuring vanity metrics (signups)	Track activation rate and retention, not just signups
Trying all channels at once	Pick ONE, make it work, then add another
Complex A/B testing infrastructure	Use simple feature flags. You don't need Optimizely at 100 users

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Related Skills

• conversion — Funnel optimization, A/B testing, and signup flow CRO
• email — Welcome sequences and lifecycle emails that drive activation
• analytics — Set up the tracking that powers growth metrics
• retention — Deep-dive on churn prevention and win-back
• pricing — Pricing tiers and expansion revenue mechanics