SkillsAdd

onewave-ai/claude-skills

expansion-revenue-finder

Identifies upsell and cross-sell opportunities within existing customer accounts.

First seen Apr 10, 2026

Installation

$ npx skills add onewave-ai/claude-skills --skill expansion-revenue-finder
View on skills.sh ↗ GitHub repository ↗

Summary

  • Identifies upsell and cross-sell opportunities within existing customer accounts.
  • Analyzes product usage, feature gaps, team growth, industry benchmarks, and competitive pressure to surface revenue expansion plays scored by potential, effort, and likelihood.
  • Generates an expansion-playbook.md with account-by-account opportunities, recommended pitch, timing, and approach.

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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 Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 287
License MIT
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,893 B
  • docs SUMMARY.md 405 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 189 installs

SKILL.md

Expansion Revenue Finder

Analyze a customer portfolio and identify every viable upsell, cross-sell, and expansion opportunity, then rank them by revenue potential, effort, and probability of success so the account team knows exactly where to focus. Optimize for total portfolio expansion revenue, not individual deal wins. Ground every recommendation in data signals, not wishful thinking.

Contents

  • references/data-inputs.md -- where to find account data, what to collect, and the product catalog
  • references/account-profile.md -- per-account expansion profile and segment benchmarking
  • references/expansion-triggers.md -- seven trigger categories and the opportunity record template
  • references/scoring.md -- three-dimension scoring rubric, composite formula, and tier interpretation
  • references/playbook-template.md -- the full expansion-playbook.md output structure
  • references/rules-and-edge-cases.md -- behavioral rules and edge-case handling

Workflow

  1. Collect data. Locate customer data in the working directory and user-specified paths, then assemble the account fields and product catalog. See references/data-inputs.md. If no structured data exists, ask the user to describe their accounts and note reduced scoring confidence.
  1. Profile and benchmark each account. Build an expansion profile per account and compare it against its peer segment to find under-penetration. See references/account-profile.md. Without external benchmarks, use the portfolio's top quartile as the benchmark.
  1. Scan for triggers. Check every trigger category for each account. Record an opportunity only when a trigger fires AND a matching product/feature is available to sell. Capture each as a structured opportunity record. See references/expansion-triggers.md. Flag underutilization as a separate "activation opportunity," not an upsell.
  1. Score and tier. Rate each opportunity on revenue potential, effort, and likelihood (1-10 each), compute the composite, and assign a tier. See references/scoring.md.
  1. Generate the playbook. Write expansion-playbook.md to the working directory (or a user-specified path), sorted by tier and composite score, with pitch, timing, approach, and portfolio-wide insights. See references/playbook-template.md.

Apply the behavioral rules and edge-case handling throughout. See references/rules-and-edge-cases.md.