# Growth Loops

> When to activate: growth loops, viral loops, referral mechanics, network effects, flywheel design, compounding growth, viral coefficient, k-factor

- Skill: `mattakushi432/growth-loops` (Agent Skill)
- Install (CLI): `npx skillmds@latest add mattakushi432/growth-loops`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mattakushi432/growth-loops/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: Mattakushi432 (https://skillmd.com/u/mattakushi432)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/mattakushi432/growth-loops

---


# Growth Loops

## Loop vs Funnel

| Funnel | Loop |
|--------|------|
| Linear: A → B → C → D | Circular: output becomes next input |
| Each run is independent | Each cycle compounds previous |
| Growth requires constant new top-of-funnel | Growth accelerates with scale |
| Example: paid ad → landing → signup | Example: user invites → new user invites more |

## Core Loop Anatomy
```
[Input] → [Action] → [Output] → feeds back to [Input]
```

## Types of Growth Loops

### 1. Viral / Referral Loop
```
User gets value → Shares with others → New users sign up → They share → ...
```
- **Inherent virality**: Product is better with others (Slack, Notion, Figma)
- **Incentivized virality**: Reward for sharing (Dropbox +500MB, Uber credits)
- **Word of mouth**: Delight → unprompted recommendation
- **Embeds**: Widget/badge on user's site links back to you

**K-factor formula:**
```
K = i × c
i = invitations sent per user
c = conversion rate of invites
K > 1 → exponential growth
K = 0.5 → viral assist (meaningful but not self-sustaining)
```

### 2. Content / SEO Loop
```
Users generate content → Content ranks in search → New users find it →
They create content → More rankings → ...
```
Examples: Quora, Reddit, TripAdvisor, Stack Overflow

### 3. Paid Loop
```
Revenue → Reinvest in ads → More customers → More revenue → ...
```
Sustainable only when: LTV > 3× CAC and payback period < 12 months

### 4. Product-Led Loop
```
Free users get value → Upgrade to paid → Fund product improvements →
Better product → More free users → ...
```

### 5. Sales-Assisted Loop
```
AE closes deal → Customer success → Expansion/upsell →
Champions move to new company → New deals → ...
```

### 6. Community Loop
```
Members join → Create content/connections → Value increases →
More members join → More content → ...
```

## Flywheel Design

### Amazon Flywheel (reference model)
```
Lower prices → More customers → More sellers → 
Wider selection → Better experience → Lower prices
```

### How to Design Your Flywheel
1. List every value-creating activity in your business
2. Identify which outputs from one step become inputs to another
3. Find the highest-leverage entry point (where to push hardest)
4. Identify friction points that slow rotation
5. Measure cycle time: how long does one full rotation take?

### Flywheel Template
```
[CORE VALUE] → [USER ACTION] → [NETWORK EFFECT] →
[PLATFORM IMPROVEMENT] → [BETTER CORE VALUE] → repeat
```

## Loop Instrumentation

### Metrics to Track Per Loop
| Metric | Formula | Target |
|--------|---------|--------|
| K-factor | invites_sent × invite_conversion | > 0.3 (assist), > 1.0 (viral) |
| Cycle time | time for one loop rotation | Minimize |
| Loop conversion | % who complete the loop action | Maximize |
| Amplification | new users per existing user per period | Track trend |

### Loop Health Dashboard
```
Weekly Loop Report:
- Users who triggered a loop action: [N]
- Downstream activations from loop: [N]
- Amplification rate: [ratio]
- Cycle time (median): [days]
- Loop-attributed revenue: [$]
```

## Network Effects

### Types
| Type | Mechanism | Example |
|------|-----------|---------|
| Direct | More users = more value for each user | WhatsApp |
| Indirect | More users → more 3rd party supply | iOS App Store |
| Data | More usage → better product | Google Search |
| Social | Status/identity tied to network | LinkedIn |
| Marketplace | Buyers attract sellers and vice versa | Airbnb |

### Network Effect Strength
Rate yours on 3 dimensions:
1. **Breadth**: How many users does each new user benefit?
2. **Depth**: How much does each additional user improve the experience?
3. **Speed**: How quickly does value compound?

## Compounding Growth vs Linear Growth

### Modeling the Difference (Python)
```python
def project_growth(initial, periods, monthly_rate, loop_multiplier=1.0):
    linear = [initial + initial * monthly_rate * t for t in range(periods)]
    compound = [initial * (1 + monthly_rate * loop_multiplier) ** t for t in range(periods)]
    return linear, compound

# With 10% monthly growth:
# Month 12 linear:  initial × 2.2
# Month 12 compound: initial × 3.1 (at 1.0x multiplier)
# Month 12 compound: initial × 5.4 (at 1.5x multiplier — loop boost)
```

## Loop Activation Strategies

### Making the Loop Fire
1. **Reduce friction** at the sharing/invite moment
2. **Increase perceived value** of the shared artifact
3. **Time the prompt** at peak satisfaction moment
4. **Make sharing native** to the workflow (not an afterthought)
5. **Reward completion** of the full loop, not just initiation

### Common Loop Killers
- Invite flow requires too many steps
- Shared content is not compelling to recipient
- Onboarding of referred users is worse than organic
- Reward feels underwhelming relative to effort
- Loop fires at wrong moment (before user has experienced value)

## Prioritization: Which Loop to Build First

Score each candidate loop:
| Criterion | Weight | Score (1–5) | Weighted |
|-----------|--------|-------------|---------|
| Cycle speed | 30% | | |
| Conversion probability | 25% | | |
| Strategic moat | 25% | | |
| Implementation cost | 20% | | |

Build the highest weighted-score loop first.