gtm-product-led-growth

What this skill does

# Product-Led Growth

Build self-serve acquisition and expansion motions. But first, figure out if PLG is even the right motion for your product.

## When to Use

**Triggers:**
- "Should we build PLG or sales-led?"
- "How do we drive self-serve adoption?"
- "Freemium to paid conversion isn't working"
- "Developer-led adoption strategy"
- "Which growth channels should we invest in?"
- "How do I know if PLG will work?"

**Context:**
- Developer tools and platforms
- B2B SaaS with self-serve potential
- Products where value is obvious without demo
- Bottom-up adoption motions
- Growth channel prioritization

---

## Core Frameworks

### 1. The PLG Reality Check (Test Before You Commit)

**What I Learned Running Both Motions in Parallel:**

Classic startup debate. PLG camp: "Developers want self-serve." Sales camp: "Enterprises need hand-holding." Instead of arguing, we tested both for 6 months. Same product, two GTM motions, tracked everything.

**The Results:**

PLG: High volume, low ACV (~$5K), fast time-to-revenue, higher churn. Sales-led: Lower volume, high ACV (~$50K), slower time-to-revenue, lower churn. **Sales won 10x on dollars despite 10x less volume.**

**Why:** Product complexity + buyer seniority = sales-led wins. The product required integration with existing infrastructure, change management across teams, and multi-stakeholder alignment. Developers loved self-serve. But they weren't the economic buyer.

**PLG works when:**
- Value is obvious in first 5 minutes
- Implementation is trivial
- Individual user gets value without team buy-in
- No procurement/legal hurdles
- Buyer = user

**Sales-led works when:**
- Product requires integration/setup
- Multiple stakeholders need alignment
- Buyer ≠ user
- Deal size justifies human touch
- Customer needs education to see value

**Before building PLG, test your motion. Don't assume PLG is better because it's trendy.** PLG is efficient at volume, but sales-led can be more profitable with complexity.

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### 2. The Growth Equation (Map Inputs to Outputs)

**The Pattern:**

Growth compounds when you systematize the relationship between activities and user acquisition. Not "do more marketing" — map specific inputs to measurable outputs.

**How to Build Your Growth Equation:**

For each channel, define: Activity (input) → Traffic (output) → Conversions.

- **Organic Search:** 1 quality blog post → 400 users/month → 5% conversion = 20 new users
- **Paid Ads:** $1K spend at 8% conversion on 100K impressions = 8K clicks → conversions at X%
- **Community Events:** 1 event → 60 attendees → 35% conversion = 21 users
- **Referral:** 1 integration partner → N referred users → conversions at Y%

**Why This Matters:**

Once you validate the equation, scaling becomes math. "I need 200 more users next month" → "I need 10 more blog posts" or "I need $5K more ad spend." Without the equation, you're guessing.

**Testing the Equation:**

1. Start with hypothesis: "If I create X, it drives Y conversion"
2. Test with small sample: 1 blog post, measure actual conversion
3. Validate: Does reality match hypothesis?
4. Scale with confidence: If yes, increase input
5. Kill if not: 4 weeks of data is enough to decide

**Common Mistake:**

Guessing at conversion rates without testing. Assuming all users from the same channel are equal quality. Scaling before validating the equation.

---

### 3. Channel Economics (Kill Losers, Double Down on Winners)

**The Pattern:**

Every channel has economics. Without tracking them, you over-invest in losers and under-invest in winners.

**Track Per Channel:**
1. **CAC:** Total spend / new users
2. **Conversion rate:** Signups → paying
3. **Retention:** 30-day, 90-day by source
4. **LTV:** Revenue over customer lifetime, by channel
5. **Payback period:** How long to recoup CAC

**The Decision Framework:**

- CAC < (LTV × margin) → Scale aggressively
- CAC ≈ (LTV × margin) → Optimize, don't scale
- CAC > (LTV × margin) → Kill within 4 weeks

**Monthly channel review:** Which channels are profitable? Which are drains? Quarterly reallocation: 3x budget to winners, kill losers.

**Critical Insight: Channel Quality Varies**

Cheap CAC doesn't mean good CAC. Organic search might deliver users at $0 CAC with 85% 30-day retention. Paid search might deliver users at $12 CAC with 45% 30-day retention. The "free" channel is 10x more valuable when you factor in retention and LTV.

**Systematic Testing:**

Test 2 new channels monthly. Give each 4 weeks of data. Kill decisively if economics don't work. Document learnings regardless of outcome — what didn't work is as valuable as what did.

**Common Mistake:**

Tracking CAC without retention. A cheap channel that churns users costs more than an expensive channel that retains them.

---

### 4. Time to First Value (The Only Activation Metric)

**The Pattern:**

Users decide product value in the first 5-10 minutes. If they don't reach the aha moment fast, they abandon.

**The Activation Audit:**

1. Sign up for your own product as a new user
2. Time how long to first value
3. Count steps to aha moment
4. Where did you get stuck?

**If TTFV > 10 minutes, you have an activation problem.**

**Before:** Sign up → confirm email → fill profile → configure settings → read docs → first action

**After:** Sign up → pre-loaded sample data → first action (immediate aha moment)

**Specific Fixes:**

1. **Pre-load sample data.** Users want to see value, not set up. Give them a working example immediately.
2. **Skip non-essential setup.** Email confirmation, profile, settings — all can wait until after the aha moment.
3. **Progressive disclosure.** Don't show all features upfront. Start with one core workflow. Reveal complexity gradually.
4. **Show, don't tell.** Interactive tutorial > video > text docs. Let them click through a workflow.

**Common Mistake:**

Assuming users will read documentation. They won't. They'll click around for 5 minutes, and if nothing works, they leave.

---

### 5. The $5K → $50K Inflection (When PLG Breaks)

**The Pattern:**

PLG works for $1K-$10K ARR. Between $20K-$50K, the motion breaks because organizational friction kicks in: procurement, legal, security, multi-stakeholder buy-in.

**The Hybrid Approach:**

**PLG ($0-$10K):** Self-serve sign-up → free tier → paid tier → credit card checkout → automated onboarding

**Sales-Assisted ($10K-$50K):** Self-serve discovery → sales engages on usage signals → human-negotiated contract → dedicated onboarding

**Enterprise ($50K+):** Outbound or inbound lead → demo → POC → proposal → legal/security review → executive sponsor

**PQL Signals (When to Trigger Sales):**

- **Usage depth:** Daily active, core features used, approaching limits
- **Expansion signals:** Multiple users from same company, team features, integrations
- **Buying signals:** Requests for SSO/compliance/SLAs, asks about team pricing

**The Handoff:**

Bad: "Hey, I saw you signed up." (Cold, generic, kills trust)
Good: "Your team is using [specific feature] across 12 repos. We can help you [specific value]. Want 15 minutes?" (Warm, specific, offers value)

**Common Mistake:**

Sales engaging too early on <$5K deals. Kills PLG motion, scares users. Let them self-serve until they need help.

---

### 6. Growth Forecasting (Plan for Uncertainty)

**The Pattern:**

Forecasts are always wrong. Plans are still valuable because they force thinking and create accountability.

**Model Three Scenarios:**

**Baseline (current trajectory continues):**
- Organic search: 35% growth → 40K new users
- Paid: Flat → 2K new users
- Community: 10% growth → 400 new users
- Total: 42.4K

**Upside (if all growth initiatives execute):**
- Organic: 50% growth (3x content) → 48K
- Paid: 2x spend, same efficiency → 4K
- New initiative (partnerships): ramp → 3K
- Total: 55K

**Downside (if key channels fail):**
- Organic: 0% growth → 26K
- Paid: CPA doubles → 1K
- Total: 27K

**Use This For:**
- Setting baseline targets (baseline scenario)
- Stretch go