Growth Loop Mapper

Map, analyze, and design growth loops for consumer/mobile products. Goes beyond simple funnels to identify compounding loops — where output from one cycle becomes input for the next.

When to Use

• "Map our growth loops"
• "How do users find us?"
• "Design a referral mechanic"
• "Analyze our funnel"
• "Why isn't growth compounding?"
• When designing viral features, referral programs, or retention mechanics
• Before growth-focused planning or experimentation

Growth Loop Types

1. Viral Loops

User → invites others → new users → they invite others

• Direct viral: user explicitly invites (referrals, share buttons)
• Content viral: user creates content seen by non-users (social posts, shared links)
• Word of mouth: user tells others offline

2. Paid Loops

Revenue → reinvest in acquisition → new users → revenue

• Sustainable when LTV > CAC with margin for reinvestment

3. Content/SEO Loops

Users create content → content gets indexed → new users discover via search → they create content

4. Engagement Loops

User action → trigger → re-engagement → user action

• Push notifications, emails, in-app prompts

5. Data/Network Effect Loops

More users → better product → more users

• Social networks, marketplaces, collaborative tools

Process

1. Map Current Loops

For each growth loop in your product:

The cycle:

• Input: what starts the loop? (new user, content, revenue)
• Action: what does the user do? (sign up, invite, create, purchase)
• Output: what does the action produce? (content, invitation, data, revenue)
• Feedback: how does output become new input? (SEO, notification, ad spend)

The metrics:

• Cycle time: how long is one loop iteration?
• Conversion at each step: what % progress through?
• K-factor (for viral): avg invites sent × conversion rate
• Payback period (for paid): time to recoup CAC

2. Diagnose Loop Health

For each loop, identify:

• Friction points — where do users drop off?
• Amplifiers — what could increase throughput?
• Decay — is the loop weakening over time? Why?
• Ceiling — what's the natural limit of this loop?

3. Design Improvements

For each identified opportunity:

• Hypothesis: "If we [change], then [metric] will [improve] because [reason]"
• Effort: how hard is this to build?
• Reversibility: can we easily revert?
• Risk: could this annoy users or feel spammy?

4. Connect to Strategy

Reference:

• knowledge/products/*/metrics.md for current growth metrics
• knowledge/products/*/roadmap.md for planned growth work
• knowledge/customers/ for segment-specific loop dynamics

Output

## Growth Loop Map: [Product]

**Date:** YYYY-MM-DD

### Active Loops

**Loop 1: [Name] ([Type])**

[Input] → [Action] → [Output] → [Feedback] → [Input]

- Cycle time: [duration]
- Key metric: [k-factor / conversion / payback]
- Health: Strong / Healthy / Weak / Broken
- Bottleneck: [where it breaks down]

**Loop 2: [Name] ([Type])**
[same structure]

### Loop Health Summary
| Loop | Type | Health | K-Factor/Key Metric | Bottleneck |
|------|------|--------|---------------------|------------|
| [name] | [type] | [health] | [metric] | [bottleneck] |

### Opportunities
| Priority | Opportunity | Loop | Expected Impact | Effort |
|----------|------------|------|-----------------|--------|
| 1 | [opportunity] | [loop] | [impact] | [effort] |

### Missing Loops
- [Loops that don't exist yet but could]

### Recommended Experiments
| Experiment | Loop | Hypothesis | Metric | Duration |
|-----------|------|-----------|--------|----------|
| [experiment] | [loop] | [hypothesis] | [metric] | [duration] |

Principles

• Loops > funnels — funnels are linear and leak; loops compound
• One loop at a time — fix the weakest link in your strongest loop first
• Organic > paid — paid loops are rented; organic loops are owned
• User value first — growth mechanics that annoy users are anti-growth