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alirezarezvani
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channel-economics

Computes fully-loaded cost-to-serve, three-lens ROI, and optimal channel mix for direct versus partner-led channels.

25.3k|3.6k|Updated Oct 19, 2025
Search Tags:#unit economics#RevOps#channel mix#channel roi#cost-to-serve#channel economics#direct vs partner
One-click install
npx skills add https://github.com/alirezarezvani/claude-skills --skill channel-economics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: channel-economics
Source: https://github.com/alirezarezvani/claude-skills/tree/main/commercial/skills/channel-economics
Command: npx skills add https://github.com/alirezarezvani/claude-skills --skill channel-economics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Quarterly channel reviews often stall because nobody knows which channel actually makes money after CAC, partner discounts, MDF, enablement time, support load, and overhead allocation are loaded in. This Skill computes honest per-channel economics so Head of Commercial, RevOps, and VP Sales can decide where to invest, maintain, defund, or exit.

Core Features & Use Cases

  • Fully-Loaded Cost-to-Serve: Computes cost per deal and per dollar of ARR per channel, breaking out direct costs from allocated overhead and flagging hidden costs like partner enablement time and channel-manager attribution.
  • Three-Lens Channel ROI: Emits Cash ROI (year-1), LTV-adjusted ROI, and Marginal ROI per channel, with deterministic verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT) and the diminishing-returns inflection point.
  • Constrained Mix Optimization: Recommends a channel mix that maximizes effective ARR subject to constraints (minimum direct floor, maximum partner concentration), plus sensitivity scenarios for CAC, discount, and retention shifts.
  • Use Case: A VP Sales facing a 60/40 direct-vs-partner pipeline runs the three scripts in sequence and walks into the quarterly review with true gross margins, per-channel verdicts, and a sensitivity-tested mix recommendation.

Quick Start

Ask the AI to run the channel-economics sample analysis to compute cost-to-serve, ROI verdicts, and an optimal mix for the built-in direct versus partner-led channel data.

Frequently Asked Questions about channel-economics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate fully-loaded cost-to-serve per sales channel?▼

Fill the channel data template with deal volume, gross revenue, and all attributable costs including channel-manager headcount, MDF, and partner enablement time, then run cost_to_serve_calculator.py. It outputs cost per deal, cost per dollar of ARR, and true gross margin, flagging hidden costs left at zero.

How do I compare direct vs partner-led channel ROI?▼

Run channel_roi_analyzer.py with per-channel investment and returns data to get Cash ROI, LTV-adjusted ROI, and Marginal ROI side by side. Each channel receives a deterministic verdict of DOUBLE-DOWN, MAINTAIN, DEFUND, or EXIT with the diminishing-returns inflection point.

What Python dependencies does the channel economics analysis require?▼

None beyond the Python standard library. All three scripts (cost_to_serve_calculator.py, channel_roi_analyzer.py, channel_mix_optimizer.py) are stdlib-only and support --sample, --input, --output, and --profile flags.

Why does my partner channel look more profitable than it really is?▼

The most common causes are inconsistent overhead allocation, treating channel-influenced deals as channel-sourced, and ignoring enablement time and channel-manager headcount. The calculator flags these hidden-cost lines and warns when partner overhead allocation is suspiciously low.

When should I not use channel mix optimization?▼

Do not use it for partner program design, tier structures, or revshare splits, which belong to partnerships architecture work, nor for historical GAAP channel P&L reporting, which is a finance task. This skill is forward-looking decision support for quarterly channel reviews.

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