Growth loops
Skill Mattakushi432/Claude-Code-Skills-Custom-DevTools-Pack/plugins/devtools-pack/skills/growth-loops
When to activate: growth loops, viral loops, referral mechanics, network effects, flywheel design, compounding growth, viral coefficient, k-factorFrom its SKILL.md
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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
- List every value-creating activity in your business
- Identify which outputs from one step become inputs to another
- Find the highest-leverage entry point (where to push hardest)
- Identify friction points that slow rotation
- 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 | |
| Indirect | More users → more 3rd party supply | iOS App Store |
| Data | More usage → better product | Google Search |
| Social | Status/identity tied to network | |
| Marketplace | Buyers attract sellers and vice versa | Airbnb |
Network Effect Strength
Rate yours on 3 dimensions:
- Breadth: How many users does each new user benefit?
- Depth: How much does each additional user improve the experience?
- Speed: How quickly does value compound?
Compounding Growth vs Linear Growth
Modeling the Difference (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
- Reduce friction at the sharing/invite moment
- Increase perceived value of the shared artifact
- Time the prompt at peak satisfaction moment
- Make sharing native to the workflow (not an afterthought)
- 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.
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