Channel Economics — Business

Channel Economics is a decision-support skill for Heads of Commercial, RevOps, and VP Sales to evaluate direct vs. partner-led channel profitability. It computes fully-loaded cost-to-serve per channel, ROI under cash/LTV/marginal lenses, and an optimal channel mix subject to constraints, producing verdicts (DOUBLE-DOWN/MAINTAIN/DEFUND/EXIT) and a sensitivity-tested recommendation.

commercial claude-code

📂 View skill on GitHub ↗ 🚀 How to use

✨ What it does

Computes fully-loaded cost-to-serve per deal and per dollar of ARR, surfacing hidden costs like enablement time and chan
Generates three-lens ROI (Cash year-1, LTV-adjusted, Marginal) with deterministic verdicts and diminishing-returns infle
Optimizes channel mix subject to constraints (min direct %, max partner concentration) with sensitivity scenarios.
Flags anti-patterns like inconsistent overhead allocation, treating influenced deals as sourced, and ignoring retention
Provides a forcing-question library to grill assumptions before running the scripts.

🎯 When to use it

Quarterly channel review when pipeline is mixed (e.g., 60% direct / 40% partner) and you don't know which channel is profitable after all co
Considering hiring a channel manager and need to know if the partner channel can clear the loaded-cost bar.
Board asks about partner program ROI (e.g., 'we spent $X on MDF — what did we get?').
A segment is over-indexed to one channel and you suspect channel-mix dogma is blocking the other.
Expanding into a new region and need to decide direct-first vs. partner-first.

🚀 How to use

Trigger: /cs:grill-commercial

Trigger by asking for a channel economics review or rebalancing analysis, e.g., 'Run channel economics on our direct vs. partner mix.' The skill expects you to fill the channel data template (assets/channel_data_template.md) with per-channel metrics (deal count, ARR, CAC, retention, partner discount, costs). Then run the three scripts in sequence: cost_to_serve_calculator.py, channel_roi_analyzer.py, channel_mix_optimizer.py. Example prompts:

Run channel economics for our quarterly review. I'll provide the data.
Use the sample data to show me how the cost-to-serve calculator works.

📄 Output: Three markdown reports: fully-loaded cost-to-serve, channel ROI with verdicts, and optimal channel mix with sensitivity analysis.

📦 Add this skill to Claude Code

# 1. Get the skills repo
git clone --depth 1 https://github.com/alirezarezvani/claude-skills /tmp/claude-skills

# 2. Copy this skill into your project (or ~/.claude/skills for all projects)
mkdir -p .claude/skills
cp -r /tmp/claude-skills/commercial/skills/channel-economics .claude/skills/channel-economics

Skill source: commercial/skills/channel-economics/SKILL.md

⚠️ Good to know

Requires honest and complete input data, especially per-channel retention and overhead allocation; it is forward-looking decision support, not historical P&L reporting.

❓ FAQ

What verdicts does the skill output?

It outputs per-channel verdicts: DOUBLE-DOWN, MAINTAIN, DEFUND, or EXIT, based on deterministic logic from the ROI analysis.

Does the skill decide the channel strategy?

No, it provides numbers and recommendations; humans make the final decision.

What is the most common anti-pattern it flags?

Inconsistent overhead allocation between channels, which can falsely inflate partner margins.

🤖 Overview, features, install steps and FAQ were generated from the project's SKILL.md on Sep 4, 2026. Always check the original source before running commands.