/cs-channel-econ

disable-model-invocation: true
description: Direct vs partner-led channel economics — fully-loaded cost-to-serve, channel ROI, optimal channel mix. NOT partnership structure (sibling partnerships-architect). Direct invocation of the channel-economics skill.
argument-hint: "<channels with deal count + ARR + costs, or path to channel JSON>"

/cs-channel-econ — Direct vs partner economics

Run the `channel-economics` skill on this input:

**$ARGUMENTS**

Three-tool workflow

1. **`channel_mix_optimizer.py`** — Per-channel effective LTV, payback period (CAC / monthly margin), LTV/CAC efficiency ratio. Recommends mix maximizing effective ARR subject to constraints (min_direct_pct, max_partner_concentration). Sensitivity table (what if direct CAC rises 20%?).

2. **`cost_to_serve_calculator.py`** — Fully-loaded cost-to-serve per deal AND per $ ARR. Breaks out direct costs vs allocated overhead. Computes "true gross margin" after channel-specific load. Surfaces hidden costs (partner enablement time, certification investment, conflict resolution overhead).

3. **`channel_roi_analyzer.py`** — ROI per channel with 3 lenses: cash ROI year-1, LTV ROI, marginal ROI (diminishing-returns curve). Verdict: DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT + diminishing-returns inflection point.

Hard rule

**No channel ROI computation without retention differential.** Channel CAC alone is meaningless — partner-channel customers often have different retention than direct.

Distinct from

• Sibling `partnerships-architect` — partnership **structure** (tier, GTM, revshare). Channel-economics is the **math**.
• `business-growth/revenue-operations` — process (lead routing, SDR motion)
• `c-level-advisor/cro-advisor` — strategic
• `finance/financial-analysis` — close + report (backward-looking); channel-economics is **forward** per-channel economics