Claude Skill MartBrowse skillsQuick linesLearn by videoTerminal guideWhat is a Skill?
Back to list

Acquisition Channel Advisor

An interactive skill that decides whether to scale, optimize, or kill a growth channel using CAC, LTV, payback, customer quality, and scalability.

Marketing & SEOIntermediate7,057845AI score 9/10Last updated: Sep 1, 2026

What it does

Applies a financial lens to any acquisition channel (paid search, content, outbound SDR, partnerships, events, webinars).

  • Unit economics: computes channel CAC, LTV, LTV:CAC ratio and payback period, then benchmarks against blended metrics
  • Customer quality: compares churn, NRR, and ICP fit by channel
  • Scalability: checks magic number, addressable volume, and CAC trend for saturation
  • Verdict: Scale aggressively / Test & optimize / Kill or pause / Keep as a strategic channel with a spend cap — each with concrete next steps and thresholds
  • Optional multi-channel comparison table plus a budget reallocation plan

It asks up to 4 adaptive questions with 3–5 numbered options at decision points, and includes 10 common pitfalls (vanity metrics, CAC-only thinking, ignoring payback, killing too early).

Who it's for

  • PMs and growth leads who own marketing budget allocation
  • SaaS founders, heads of marketing, and finance/FP&A partners
  • Anyone who needs a defensible answer to "should we put more money into this channel?"

Best with channel-level CAC and retention data; the skill explicitly excludes brand-new channels (<3 months, <100 customers).

Examples

  1. "Paid LinkedIn: CAC $2,400, LTV $9,000, 14-month payback, flat retention" → marginal verdict plus a 4–8 week optimization plan
  2. Compare content marketing, outbound email, and partner referrals side by side to set next year's budget split
  3. Review a money-losing trade-show program and land on "strategic channel, cap spend, re-evaluate in 6 months"

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/deanpeters/Product-Manager-Skills/HEAD/skills/acquisition-channel-advisor/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/acquisition-channel-advisor folder from the GitHub repo deanpeters/Product-Manager-Skills into my ~/.claude/skills/acquisition-channel-advisor/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/deanpeters/Product-Manager-Skills.git && mkdir -p ~/.claude/skills && cp -r Product-Manager-Skills/skills/acquisition-channel-advisor Product-Manager-Skills/skills/workshop-facilitation ~/.claude/skills/

This is a third-party skill. Check the source repository before installing.

  1. Open your terminal.
  2. Clone the repo: git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. Create the skills folder: mkdir -p ~/.claude/skills
  4. Copy this skill plus the facilitation protocol skill it references: cp -r Product-Manager-Skills/skills/acquisition-channel-advisor Product-Manager-Skills/skills/workshop-facilitation ~/.claude/skills/
  5. Restart Claude Code and confirm acquisition-channel-advisor appears in your skill list.
  6. Invoke it: "Use acquisition-channel-advisor on our paid LinkedIn channel: CAC $2,400, LTV $9,000, 14-month payback."
  7. No numbers yet? Just call the skill — it opens by asking which channel you're evaluating and what data you have.
View source on GitHubLicense: NOASSERTION