acquisition-channel-advisor
🤖 AI Summary
This skill evaluates acquisition channels by analyzing unit economics (CAC, LTV, payback), customer quality (retention, NRR), and scalability (magic number, volume potential) to recommend whether to scale, test, or kill each channel.
How to Install
Claude Code:
git clone --depth 1 https://github.com/deanpeters/Product-Manager-Skills.git && cp Product-Manager-Skills/skills/acquisition-channel-advisor ~/.claude/skills/acquisition-channel-advisor -r## Purpose
Guide product managers through evaluating whether to scale, test, or kill an acquisition channel based on unit economics (CAC, LTV, payback), customer quality (retention, NRR), and scalability (magic number, volume potential). Use this to make data-driven go-to-market decisions and optimize channel mix for sustainable growth.
This is not a channel strategy framework—it's a financial lens for channel evaluation that helps you avoid scaling unprofitable channels or killing channels with fixable problems. Use when deciding how to allocate marketing budget across channels.
## Key Concepts
### The Channel Evaluation Framework
A systematic approach to evaluate acquisition channels:
1. **Unit Economics** — What does it cost to acquire, and what's the return?
- CAC (Customer Acquisition Cost)
- LTV (Lifetime Value)
- LTV:CAC ratio
- Payback period
2. **Customer Quality** — Do customers from this channel stick around and expand?
- Cohort retention rate (by channel)
- Churn rate (by channel)
- NRR (Net Revenue Retention by channel)
- Expansion rate
3. **Scalability** — Can this channel sustain growth at the volume you need?
- Magic Number (S&M efficiency)
- Addressable volume (TAM of channel)
- Saturation risk (diminishing returns)
- CAC trend (increasing, stable, decreasing)
4. **Strategic Fit** — Does this channel align with your go-to-market strategy?
- Customer segment match (SMB vs. enterprise)
- Sales motion compatibility (PLG vs. sales-led)
- Brand positioning alignment
### Decision Matrix
| LTV:CAC | Payback | Customer Quality | Scalability | Decision |
|---------|---------|------------------|-------------|----------|
| >3:1 | <12mo | Good retention | High volume | **Scale aggressively** |
| 2-3:1 | 12-18mo | Average retention | Medium volume | **Test & optimize** |
| <2:1 | >18mo | Poor retention | Low volume | **Kill or fix** |
### Anti-Patterns (What This Is NOT)
- **Not vanity metrics:** "We got 10,000 signups!" means nothing if they churn in 30 days
- **Not CAC-only thinking:** Low CAC with terrible retention is worse than high CAC with great retention
- **Not ignoring payback:** 5:1 LTV:CAC with 36-month payback is a cash trap
- **Not scaling broken channels:** Pouring money into inefficient channels accelerates failure
### When to Use This Framework
**Use this when:**
- Evaluating whether to scale a new channel (content, paid, events, etc.)
- Deciding how to allocate marketing budget across channels
- Assessing whether to kill an underperforming channel
- Comparing channels to optimize ROI
- Planning annual marketing budget allocation
**Don't use this when:**
- Channel is brand-new (<3 months, <100 customers) — not enough data
- You're testing channel fit (this is for evaluation, not experimentation)
- Strategic channels (e.g., enterprises require field sales regardless of CAC)
- You don't have channel-level data (need to track CAC, retention by source)
---
### Facilit
Details
| Category | Business → pm |
| Source | deanpeters/Product-Manager-Skills |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 5.3K |
| Est. per Skill | N/A (shared across 54 skills from this repo) |
| Difficulty | Advanced |
| Risk Level | N/A |
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