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expansion-revenue-finder

expansion-revenue-finder

github.com/onewave-aiMarketing & growth393232 installsUpdated 1w ago
Repository

About expansion-revenue-finder

A sales-planning skill that analyzes customer portfolios to find and prioritize expansion opportunities. It grounds recommendations in account data and produces a ranked playbook for account teams.

Key features

  1. 01Account profiling and segment benchmarks
  2. 02Seven-category trigger scan
  3. 03Revenue, effort, and likelihood scoring
  4. 04Prioritized expansion playbook
  5. 05Portfolio-wide opportunity insights

Use cases

  1. 01Prioritize accounts for upsell and cross-sell
  2. 02Compare account penetration within segments
  3. 03Separate product activation from upsell
  4. 04Plan outreach using ranked opportunities

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/onewave-ai/claude-skills --skill expansion-revenue-finder

After installing, type/expansion-revenue-finderin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
account-profile.md
data-inputs.md
expansion-triggers.md
playbook-template.md
rules-and-edge-cases.md
scoring.md

Details

From the project README

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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

Comments

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