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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