lvtd-llc/skills

eighty-twenty-customer-value-rfm

Segment customers and lists by 80/20 value, responsiveness, recency, frequency, and money. Use when identifying best customers, prioritizing follow-up, finding high-value buyers, pruning low-value accounts, or deciding what customer data to measure.

First seen Jun 21, 2026

Installation

$ npx skills add lvtd-llc/skills --skill eighty-twenty-customer-value-rfm

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 1
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version0.1.0
LicenseMIT
CompatibilityCodex, Claude Code, and other Agent Skills-compatible clients.
Declared agents claude-code codex
More metadata
version
0.1.0
displayName
80/20 Customer Value RFM
category
Marketing
tags
eighty-twenty,rfm,segmentation,customers,analytics

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,077 B
  • docs SUMMARY.md 289 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 57 installs

SKILL.md

80/20 Customer Value RFM

Use this skill to find the customers, buyers, leads, or accounts that deserve disproportionate attention. It is based on 80/20 Sales and Marketing by Perry Marshall.

Source Traceability

Primary source: 80/20 Sales and Marketing, chapters 12, 19, 22, and 23.

  • Chapter 12 covers premium buyer behavior and hidden customer value.
  • Chapter 19 covers removing problem customers and weak performers.
  • Chapter 22 covers choosing the few measurements that matter.
  • Chapter 23 covers recency, frequency, money, and customer-value measurement.

Workflow

1. Define The Customer Set

Capture:

  • Customer or lead population.
  • Time window.
  • Revenue, profit, or strategic value metric.
  • Available behavioral data.
  • Follow-up capacity.

If the data is weak, create a practical scoring plan instead of pretending the segmentation is precise.

2. Score RFM And Responsiveness

Score each customer or segment:

  • Recency: how recently they acted or bought.
  • Frequency: how often they act or buy.
  • Money: how much they spend or can spend.
  • Responsiveness: how quickly and strongly they respond.
  • Fit: whether they match the desired customer profile.

3. Segment The List

Use these groups:

  • Best buyers: high recent value, repeat behavior, strong fit.
  • Expansion candidates: good fit with evidence of premium potential.
  • Nurture: fit is plausible but timing or proof is weaker.
  • Low-value tail: low fit, low value, high effort, or high support burden.
  • Problem customers: negative margin, toxic behavior, or strategic drag.

4. Decide Treatment By Segment

Recommend different action by segment:

  • Personal outreach.
  • Premium offer.
  • Referral request.
  • Automated nurture.
  • Requalification.
  • Sunset, prune, or fire.

Output Format

# Customer Value Segmentation

## Data Available
- Population:
- Time window:
- Fields available:
- Data gaps:

## RFM Segments
| Segment | Recency | Frequency | Money | Responsiveness | Action |
|---------|---------|-----------|-------|----------------|--------|

## 80/20 Findings
- Top customers:
- Hidden expansion group:
- Low-value tail:
- Problem customers:

## Recommended Actions
1. [Action]
2. [Action]
3. [Action]

Quality Bar

  • Do not treat all customers as equally valuable.
  • Do not use revenue without considering effort, margin, or fit.
  • Do not recommend firing customers without a clear reason.
  • Separate premium potential from current spend.
  • State what data would improve the segmentation.