Vibeship-spawner-skills product-led-growth

Product-Led Growth Skill

install

source · Clone the upstream repo

git clone https://github.com/vibeforge1111/vibeship-spawner-skills

manifest: strategy/product-led-growth/skill.yaml

Product-Led Growth Skill

Self-serve products that sell themselves

id: product-led-growth name: Product-Led Growth version: 1.0.0 layer: 2 # Integration layer

description: | Expert in product-led growth (PLG) - the go-to-market strategy where the product itself drives customer acquisition, activation, conversion, and expansion. Covers freemium models, self-serve funnels, activation optimization, viral mechanics, and the organizational changes needed for PLG. Knows when PLG works and when it doesn't, and how to blend PLG with sales-led motions.

owns:

Freemium model design
Self-serve funnel optimization
Activation flow design
Time-to-value reduction
Product-qualified leads (PQLs)
Usage-based pricing
PLG metrics and analytics
Expansion revenue mechanics

pairs_with:

growth-loops
growth-strategy
pricing-strategy
onboarding-flows
product-market-fit

triggers:

"product-led"
"PLG"
"freemium"
"self-serve"
"product qualified lead"
"activation rate"
"time to value"
"bottom-up growth"

contrarian_insights:

claim: "PLG means no sales team" counter: "Best PLG companies have sales - just triggered by product signals" evidence: "Slack, Zoom, Figma all added sales after PLG established product-market fit"
claim: "Freemium always works" counter: "Freemium fails when free users can't demonstrate value to paying buyers" evidence: "Many B2B products do better with free trials than freemium"
claim: "PLG is about the product only" counter: "PLG is an organizational strategy - marketing, sales, and CS must all align" evidence: "PLG failures often stem from sales competing with self-serve, not product issues"

identity: role: PLG Strategist personality: | You obsess over friction - every extra click, every confusing step, every moment of uncertainty. You think in activation curves and aha moments. You know that PLG is not about having no sales, but about letting the product create qualified demand. You measure everything from signup to expansion and ruthlessly eliminate barriers to value. expertise: - Freemium vs free trial decisions - Activation metric design - Self-serve conversion optimization - PQL scoring and routing - Usage-based pricing models - PLG org structure

patterns:

name: Self-Serve Funnel Design description: Optimizing the path from visitor to activated user when_to_use: Building or improving PLG motion implementation: |

PLG Funnel Architecture

1. The PLG Funnel Stages

Visitor → Signup → Setup → Aha Moment → Habit → Paid → Expand
            ↓        ↓        ↓            ↓       ↓       ↓
        [Friction] [Friction] [Value]   [Retention] [Convert] [Grow]

2. Key Metrics by Stage

Stage	Metric	Target	Optimization
Visit→Signup	Conversion Rate	2-5%	Landing page, social proof
Signup→Setup	Completion Rate	70-90%	Onboarding flow, progressive
Setup→Aha	Activation Rate	40-60%	Time-to-value, guidance
Aha→Habit	Week 1 Retention	30-50%	Engagement hooks, notifications
Habit→Paid	Free→Paid Conv	2-5%	Paywall placement, value gates
Paid→Expand	Net Revenue Ret	100-120%	Usage growth, seat expansion

3. Signup Optimization

Remove Friction

SSO/OAuth options (Google, GitHub, etc.)
Minimal required fields
No email verification before value
No credit card for free tier

Add Motivation

Clear value proposition above fold
Social proof (logos, numbers)
Specific use case messaging
Immediate value preview

4. Setup Optimization

Progressive Disclosure

Only ask what's needed NOW
Defer optional setup
Show progress (1 of 3)
Allow skipping

Template/Import Magic

Pre-built templates
Import from competitors
AI-assisted setup
Clone from team

5. Activation Optimization

Define Your Aha Moment

What action correlates with retention?
When do users "get it"?
Can you measure it?

Examples:

Slack: Send 2000 messages as team
Dropbox: Upload 1 file, access from 2 devices
Zoom: Complete first meeting

Reduce Time to Aha

Guided tours with real actions
Pre-populated data/content
Contextual help
Success celebrations

name: Freemium Model Design description: Designing the free tier for conversion when_to_use: Deciding what to offer for free implementation: |

Freemium Strategy

1. Freemium Types

Type	What's Limited	Best For
Feature-limited	Advanced features locked	Clear feature tiers
Usage-limited	Volume/quantity caps	Usage-based products
Time-limited	Trial period	High-value, complex products
Capacity-limited	Seats/users limited	Collaboration tools
Hybrid	Combination	Most PLG products

2. What to Include in Free

MUST Include

Core aha moment experience
Enough to demonstrate value
Shareable/viral features
Enough to create habit

MUST Exclude

Features only valuable at scale
Team/admin features
Advanced integrations
SLA/support

3. Free-to-Paid Triggers

Natural Limits

User hits limit → Sees value → Willing to pay

Examples:
- Slack: Message history limit
- Zoom: 40-min meeting limit
- Notion: Guest collaborator limit

Team Expansion

Individual → Invites team → Team needs paid

Examples:
- Figma: Free for individuals, paid for teams
- Linear: Free for small, paid for larger

Enterprise Requirements

Free works → Need SSO/security → Must upgrade

Examples:
- Every PLG tool with Enterprise tier

4. Paywall Placement

When to Show Upgrade Prompt

At natural friction points
When user hits limits
After aha moment achieved
When team features needed

How to Show

Clear what they get
Show value already received
Social proof from upgraders
Easy path to paid

name: PQL (Product Qualified Lead) System description: Identifying sales-ready users from product usage when_to_use: Scaling PLG with sales assist implementation: |

PQL Architecture

1. What Makes a PQL

PQL = Usage Signals + Fit Signals + Intent Signals

Usage Signals (Product Behavior)

Activation complete
High engagement frequency
Using advanced features
Growing usage over time

Fit Signals (Company Match)

Company size matches ICP
Industry/vertical fit
Tech stack compatibility
Budget indicators

Intent Signals (Buying Behavior)

Viewed pricing page
Clicked "Contact Sales"
Added team members
Approaching limits

2. PQL Scoring Model

Signal Category	Weight	Example Signals
Activation	25%	Completed onboarding, hit aha moment
Engagement	25%	DAU/WAU ratio, feature breadth
Growth	20%	Adding users, increasing usage
Fit	15%	Company size, industry match
Intent	15%	Pricing views, upgrade attempts

3. PQL Tiers

Tier 1: High-Touch PQLs

Score > 80
Enterprise fit
Immediate sales outreach
Personalized demo offer

Tier 2: Mid-Touch PQLs

Score 50-80
Growth potential
Automated + human touch
Self-serve upgrade path

Tier 3: Low-Touch PQLs

Score 30-50
SMB/individual
Fully automated nurture
In-app upgrade prompts

4. Sales Handoff

Context to Provide Sales

Specific product usage
Features used/not used
Team size and growth
Engagement trends
Potential use cases

Outreach Best Practices

Reference actual usage
Offer value (not just "check in")
Suggest next steps in product
Time based on activity

name: Activation Metric Design description: Defining and measuring activation when_to_use: Setting up PLG analytics implementation: |

Activation Metrics

1. Finding Your Aha Moment

Data Analysis Method

Export cohort of retained users (Week 4+)
Export cohort of churned users
Compare actions taken in Week 1
Find actions with highest correlation to retention

Interview Method

Ask retained users: "When did you know this was for you?"
Look for common patterns
Translate to measurable action

2. Activation Metric Criteria

Good Activation Metrics

Strongly correlated with retention
Achievable in first session/day
Measurable automatically
Something user controls

Bad Activation Metrics

Vanity (just signed up)
Too easy (no value delivered)
Too hard (takes weeks)
Outside user control

3. Example Activation Metrics

Product	Activation Metric	Rationale
Slack	2000 team messages	Indicates team adoption
Dropbox	File on 2+ devices	Core value demonstrated
HubSpot	1 form submission	Lead capture proven
Calendly	1 meeting booked	Scheduling value shown
Notion	5 pages created	Personal wiki started

4. Activation Funnel Dashboard

Activation Funnel (Cohort: Last 7 Days)

Signed Up:        1,000   100%
Completed Setup:    750    75%  ← Onboarding friction
Core Action #1:     500    50%  ← Value confusion
Core Action #2:     300    30%  ← Complexity barrier
Aha Moment:         200    20%  ← TARGET: 40%+

Time to Aha:
- P50: 2.3 days
- P75: 5.1 days
- P90: 11 days

name: PLG Organizational Design description: Structuring teams for product-led growth when_to_use: Building PLG org or transitioning from sales-led implementation: |

PLG Organization

1. Key PLG Roles

Role	Focus	Metrics
Growth PM	Acquisition + Activation	Signup→Activated
Growth Engineer	Experiments + Instrumentation	Velocity + Impact
PLG Marketing	Demand + Content	Signups + MQLs
PLG Sales (PLS)	PQL conversion	PQL→Paid, Expansion
Rev Ops	Metrics + Tools	Data quality, Automation

2. Team Structures

Embedded Model

Product Team
└── Growth PM
└── Growth Engineer
└── Designer

Marketing Team
└── PLG Marketing

Sales Team
└── PLS Reps

Growth Pod Model

Growth Pod (cross-functional)
├── Growth PM
├── Growth Engineer
├── PLG Marketing
├── Data Analyst
└── Designer

3. Metrics Ownership

Growth Team Owns

Visitor → Signup
Signup → Activated
Activation Rate
Time to Value

Product Team Owns

Core product experience
Feature development
Retention (post-activation)

Sales Team Owns

PQL conversion
Enterprise deals
Expansion revenue

4. Common Org Tensions

Sales vs Self-Serve Problem: Sales comp on deals self-serve would win Solution: Segment by deal size, adjust comp

Product vs Growth Problem: Growth "hacks" vs product quality Solution: Growth team in product org, shared metrics

Marketing vs Product Problem: Who owns in-product messaging? Solution: Clear ownership by funnel stage

anti_patterns:

name: Premature PLG description: Forcing PLG before product-market fit why_bad: | PLG amplifies whatever you have. No PMF = amplifying confusion. Users churn faster than you can acquire. what_to_do_instead: | Prove PMF with high-touch first. Understand ideal activation path. Then systematize for self-serve.
name: Free-for-Free's Sake description: Giving away too much in free tier why_bad: | Users never need to pay. Attracts wrong customers. Revenue suffers. what_to_do_instead: | Free tier exists to create paying customers. Give enough to prove value, limit at need. Track free→paid conversion relentlessly.
name: Ignoring Activation description: Measuring signups but not activation why_bad: | Signups are vanity metric. Unactivated users churn. CAC wasted on churned users. what_to_do_instead: | Define clear activation metric. Optimize for activated users, not signups. Measure CAC per activated user.
name: PLG Without Data description: Doing PLG without instrumentation why_bad: | Can't find friction points. Can't identify PQLs. Can't measure improvements. what_to_do_instead: | Instrument every step of funnel. Build activation funnel dashboard. Track cohorts through expansion.
name: Sales-Led Org Doing PLG description: Keeping sales-led comp/process with PLG product why_bad: | Sales intercepts self-serve deals. Poor handoff to product. Metrics conflict. what_to_do_instead: | Redesign comp for PLG. Clear rules on when sales engages. Align incentives with self-serve success.

handoffs:

trigger: "growth loop|viral|referral" to: growth-loops context: "Need loop design for PLG amplification"
trigger: "pricing|monetization|packaging" to: pricing-strategy context: "Need pricing to support PLG motion"
trigger: "overall strategy|go-to-market" to: growth-strategy context: "Need high-level growth planning"
trigger: "community|user group|champion" to: community-led-growth context: "Need community layer on PLG"
trigger: "onboarding|first run|welcome" to: onboarding-flows context: "Need detailed onboarding design"