{"id":"channel-economics","name":"channel-economics","summary":"チャネル経済学:市場投入チャネルの財務構造を設計・分析すること。チャネルミックスの選択、パートナーマージンやTCOのモデリング、パートナーのティアやリベートの設計、チャネルの競合分析などに活用してください。","body":"# Channel Economics\n\nEnd-to-end financial modeling and design of go-to-market channels: direct sales economics, reseller / distributor margin structures, marketplace fees, partner tier economics, channel conflict resolution, and the TCO frameworks that compare channel options apples-to-apples.\n\nThis skill provides the financial backbone for channel strategy. For strategic partnership design (which channel to invest in, how to structure the partnership), see `business-growth/partnerships-architect`. For partner-deal-level approval mechanics, see `business-growth/deal-desk`.\n\n---\n\n## When to use this skill\n\n| Situation | Skill applies |\n|-----------|---------------|\n| Deciding direct vs partner-led for a new product | Yes — start with **channel model decision tree** |\n| Designing a partner tier structure (silver/gold/platinum) | Yes — see **partner tier economics** |\n| Modeling a specific partner deal's margin / payback | Yes — `scripts/channel_margin_calculator.py` |\n| Analyzing channel conflict (overlapping direct + partner deals) | Yes — see **channel conflict** + `scripts/channel_mix_optimizer.py` |\n| Building a partner program rebate / SPIFF structure | Yes — see **rebate design** |\n| Comparing AWS Marketplace vs direct list-price economics | Yes — `scripts/channel_margin_calculator.py --channel marketplace` |\n| Negotiating a specific partner contract | Use `business-growth/contract-and-proposal-writer` for the contract; this for the economics |\n| Strategic partnership design (joint go-to-market, OEM, white-label) | Use `business-growth/partnerships-architect` first |\n\n---\n\n## The channel model decision tree\n\nSix core channel models. Most companies use a mix.\n\n```\nWhat's the product's complexity + price point?\n\nLow complexity, low price (< $10k ACV):\n├── Self-serve / PLG → no channel\n├── E-commerce → direct via web\n└── Marketplace (AWS / Azure / GCP / Salesforce AppExchange) → if buyer already there\n\nMedium complexity, mid-market price ($10k - $250k ACV):\n├── Inside sales / SDR-led direct → if buyer journey is well-understood\n├── Reseller / VAR (Value-Added Reseller) → if local presence / language matters\n├── Marketplace → if buyer prefers procurement via existing relationship\n└── Embedded / OEM → if your product is a component in someone else's offering\n\nHigh complexity, enterprise ($250k+ ACV):\n├── Direct field sales → standard for high-touch enterprise\n├── Strategic SI / Integrator (Accenture, Deloitte, etc.) → if implementation is a substantial project\n├── ISV / Embedded → if you're a feature in a larger platform\n└── Reseller / Distributor → for regional or vertical specialty\n\nOperational / managed-service buyer:\n└── MSP (Managed Service Provider) → if customer wants outsourced operations\n```\n\nSee [references/channel-models-direct-partner-marketplace.md](references/channel-models-direct-partner-marketplace.md) for each model in depth: economic structure, typical margin splits, when each works / fails, contract patterns.\n\n---\n\n## Margin and TCO framework\n\nApples-to-apples channel comparison requires a consistent TCO model. The naive comparison (\"direct gets 100%, reseller gets 70%\") misses critical costs.\n\n### True channel TCO formula\n\n```\nChannel Contribution Margin\n  = Channel-attributed Revenue\n  − COGS\n  − Partner Discount/Commission\n  − Channel-specific Sales Cost (allocated)\n  − Channel-specific Marketing Cost (MDF, co-marketing)\n  − Partner Enablement Cost (training, certification)\n  − Channel Operations Cost (channel manager headcount)\n  − Channel-specific Support Cost (T1 partner support)\n```\n\n### Side-by-side comparison\n\nFor a $100k ACV deal:\n\n| Component | Direct | Reseller (30% off) | AWS Marketplace |\n|-----------|--------|---------------------|-----------------|\n| Customer payment | $100,000 | $100,000 | $100,000 |\n| Reseller / marketplace fee | $0 | -$30,000 (30% discount) | -$3,000 (3% AWS fee) |\n| Revenue to us | $100,000 | $70,000 | $97,000 |\n| COGS (15%) | -$15,000 | -$10,500 | -$14,550 |\n| Sales cost (allocated CAC) | -$25,000 | -$5,000 | -$8,000 |\n| Marketing cost (MDF / listing) | -$2,000 | -$8,000 | -$5,000 |\n| Partner enablement (amortized) | $0 | -$3,000 | -$1,500 |\n| Channel ops (amortized) | $0 | -$2,000 | -$1,000 |\n| Support cost | -$5,000 | -$3,000 | -$5,000 |\n| **Net contribution** | **$53,000** | **$38,500** | **$61,950** |\n| **% of ACV** | 53% | 38.5% | 62% |\n\nThe \"30% discount\" reseller deal is more like 14.5% margin difference once everything's counted. Marketplace can look better than direct on per-deal basis (Amazon's sales team brings the buyer) — but volume varies.\n\nUse `scripts/channel_margin_calculator.py --deal deal.yaml --channel <type>` to model this for any deal.\n\nSee [references/margin-and-tco-frameworks.md](references/margin-and-tco-frameworks.md) for the full TCO framework, per-cost-line guidance, and how to allocate \"fully-loaded\" sales / marketing / ops costs.\n\n---\n\n## Partner tier economics\n\nMulti-tier partner programs (Authorized → Silver → Gold → Platinum) are common. Designed badly, they reward effort that isn't valuable; designed well, they reward outcomes that drive growth.\n\n### Standard tier structure\n\n| Tier | Annual revenue threshold | Discount % | Other benefits | Requirements |\n|------|-------------------------|------------|----------------|--------------|\n| Authorized | None | 10% | Standard support | Sign partner agreement; 1 certified person |\n| Silver | $100k | 15% | Co-marketing eligible (limited MDF) | $100k achieved; 3 certified people; 2 customer wins |\n| Gold | $500k | 20% + 5% rebate at threshold | Dedicated channel manager; MDF; deal registration; lead sharing | $500k achieved; 5 certified; 5 wins; 80% renewal rate |\n| Platinum | $2M | 25% + 7% rebate at threshold | Top-tier support; joint roadmap; preferred status; press release rights | $2M achieved; 10 certified; 10 wins; 90% renewal; participation in advisory board |\n\n### Tier design principles\n\n1. **Outcome-based, not effort-based.** Reward revenue + retention, not training hours or marketing event count.\n2. **Achievable but stretching.** Each tier should be a 12-18 month stretch from the prior.\n3. **Differentiable benefits.** Each tier needs benefits a partner actively wants (not just \"more support\").\n4. **Renewable status.** Tiers re-evaluated annually. Partners can move down if they don't maintain.\n5. **Anti-gaming protection.** Discount-stacking, registration gaming, transfer pricing — design out.\n\nUse `scripts/partner_tier_economics.py --tiers tiers.yaml` to model tier economics: gross margin per tier, partner-side incentive, break-even revenue per partner per tier.\n\n---\n\n## Rebate / SPIFF design\n\nThree common reward structures, each with trade-offs:\n\n### Front-end discount\n\nPartner buys from you at a discount; sells to customer at list (or close). Margin = the spread.\n\n**Pros:** Simple. Cash flow goes to partner immediately.\n**Cons:** Hard to incentivize specific behaviors. Discount is locked in regardless of performance.\n\n### Back-end rebate\n\nPartner pays full price (or near it); earns rebate quarterly / annually based on revenue / tier achievement.\n\n**Pros:** Ties reward to actual achievement; behaviors can be incentivized (e.g., bonus for selling new products).\n**Cons:** Cash-flow burden on partner. Complex to administer.\n\n### MDF (Marketing Development Funds) / SPIFF\n\nPer-deal or per-period bonuses for specific actions: bring leads, attend events, certify staff.\n\n**Pros:** Highly targetable. Rewards specific behaviors you want.\n**Cons:** Easy to game; admin overhead high; partners often expect it without producing.\n\n### Typical mix\n\n| Partner type | Front-end | Back-end | MDF/SPIFF |\n|--------------|-----------|----------|-----------|\n| Reseller (transactional) | 70-80% of total comp | 10-20% | 5-10% |\n| VAR (consultative selling) | 50-60% | 20-30% | 10-20% |\n| Distributor (volume play) | 80-90% | 5-15% | 5% |\n| ISV / Embedded | n/a (rev share) | 100% | 0 |\n| MSP | 40-60% | 20-30% | 10-30% |\n\n---\n\n## Channel conflict\n\nChannel conflict happens when multiple sales paths chase the same customer. Common forms:\n\n### Direct-vs-partner conflict\n\n| Scenario | Resolution pattern |\n|----------|---------------------|\n| Direct rep finds opportunity also touched by partner | Deal registration: first to register wins; partner gets credit if they brought it |\n| Partner finds direct customer | If direct is already engaged: partner deferred (with consolation MDF perhaps); if not: partner leads |\n| Customer asks for direct after partner-led pilot | Honor partner relationship for term; transition at next renewal if appropriate |\n\n### Partner-vs-partner conflict\n\n| Scenario | Resolution pattern |\n|----------|---------------------|\n| Two resellers both pursuing same account | First-registered wins; second is offered alternative leads / regional swap |\n| Vertical specialist vs geographic | Vertical wins (customer values vertical expertise more) |\n| New partner pursues incumbent partner's customer | Incumbent has right of first refusal for 90 days |\n\n### Marketplace-vs-direct conflict\n\nCustomer can buy via AWS Marketplace OR direct. If price is lower direct, customer feels gamed. If price is same, why not just use marketplace? Common resolution:\n\n- **Same price** direct vs marketplace (customer doesn't get punished for procurement choice)\n- **Quota credit** to the direct rep when customer chooses marketplace (so rep isn't disincentivized)\n- **Marketplace listing visibility** as a value-add, not as a different pricing channel\n\nSee [references/channel-conflict-resolution.md](references/channel-conflict-resolution.md) for the full conflict-resolution playbook including deal registration process, neutral arbitration, conflict-of-interest disclosure.\n\n---\n\n## Clarify First\n\nBefore modeling the channel economics, confirm these inputs. If any is unknown or vague, ASK — do not assume:\n\n- [ ] **Channel model(s) in scope** — direct, reseller/VAR, distributor, marketplace, OEM, or MSP (sets which decision-tree branch and TCO comparison to run)\n- [ ] **Target ACV / price point** — sub-$10k vs mid-market vs enterprise (selects the viable channel branch and sizes per-deal margin)\n- [ ] **Fully-loaded cost lines** — COGS %, allocated sales/marketing/ops/support costs (drives the TCO contribution-margin model, not just the headline discount)\n- [ ] **Partner contribution + tier intent** — what the partner does (lead, sell, implement) and whether you're designing tiers/rebates (drives tier economics + rebate/SPIFF mix)\n\nStop rule: ask only the 2-3 that most change the output. If the user says \"just draft it,\" proceed and list your assumptions at the top of the model.\n\n## End-to-end workflows\n\n### Workflow: Design a new partner program\n\n1. **Pick channel models** — direct + reseller? marketplace? OEM? — using the decision tree\n2. **Model the economics** — `scripts/channel_margin_calculator.py` per channel option at expected ACV\n3. **Design tier structure** — `scripts/partner_tier_economics.py` to size the gates and benefits\n4. **Define rebate / SPIFF mix** — per tier and partner type\n5. **Write the partner agreement** (with `business-growth/contract-and-proposal-writer`)\n6. **Build channel ops** — deal registration, MDF approval, certification tracking\n7. **Hire channel manager(s)** — usually 1 manager per 10-15 active partners\n8. **Pilot with 3-5 partners** — measure, iterate, then scale\n\n### Workflow: Evaluate a specific partner deal\n\n1. **Inputs**: ACV, partner discount %, expected close, partner's contribution (lead source? sales effort? implementation?)\n2. **Calculate net contribution** — `scripts/channel_margin_calculator.py --deal deal.yaml --channel partner`\n3. **Compare to direct alternative** — would this deal have closed direct? at what cost?\n4. **Decide**: approve / counter / decline (often via deal desk if it's a non-standard partner discount)\n\n### Workflow: Channel mix analysis\n\n1. **Inputs**: actual revenue by channel for last 4 quarters\n2. **Run mix optimizer** — `scripts/channel_mix_optimizer.py --revenue revenue.csv` examines contribution margin per channel + identifies under-/over-invested channels\n3. **Recommend rebalancing** — e.g., \"Reseller channel: 20% of revenue, 8% of contribution margin — reduce investment; marketplace: 15% of revenue, 25% of contribution — increase listing visibility\"\n4. **Quarterly review**: present to CRO / CFO\n\n### Workflow: Resolve a channel conflict\n\n1. **Document the conflict** — accounts involved, parties, history\n2. **Apply the registration rule** — first-registered partner wins absent overriding facts\n3. **Consider exceptions** — strategic logo, customer preference, vertical expertise\n4. **Communicate decision** — both parties, with reasoning, in writing\n5. **Compensate the loser** — alternative leads, MDF, regional swap; preserve the relationship\n\n---\n\n## Anti-patterns\n\n- **Direct + partner at same price.** Customer feels punished for not using direct (or vice versa); kills partner motivation. Price-to-customer must be consistent across channels.\n- **Discount-only partner program.** Partners that only get a discount have no skin in your success; treat you as another vendor; switch easily.\n- **Endless partner expansion without enablement.** Signing 200 partners that don't sell anything; channel manager headcount can't scale; partners stale.\n- **Marketplace as afterthought.** Listing on AWS Marketplace without dedicated investment (listing optimization, co-sell programs) = marketplace generates nothing.\n- **Channel manager as glorified email forwarder.** CM should drive partner pipeline, not just relay leads.\n- **Rebates with no audit.** Partner self-reports revenue; you trust it; reality is 20% off. Build verification.\n- **MDF spent on activities that don't drive pipeline.** Partner runs a great event, generates no pipeline. MDF should require pipeline outcome.\n- **Channel conflict policy that isn't followed.** Policy says first-registered wins, but exec overrides every time → policy is theater.\n- **Different commission per channel for same deal.** Direct rep gets 8% on $100k deal, channel rep gets 6% on $100k deal — direct rep refuses partner help; channel rep undercut.\n- **OEM / embedded deals priced like resale.** OEM = customer doesn't see you at all; ASP can be 50-80% of list. Resale = customer sees you. Different economics; different price points.\n\n---\n\n## Tooling outputs\n\n| Script | Input | Output |\n|--------|-------|--------|\n| `scripts/channel_margin_calculator.py` | Deal spec YAML + channel type | Per-channel net contribution margin, cost line breakdown, comparison vs direct baseline |\n| `scripts/partner_tier_economics.py` | Tier definitions YAML | Per-tier: gross margin to us, gross margin to partner, partner break-even, tier graduation incentive analysis |\n| `scripts/channel_mix_optimizer.py` | Revenue CSV (by channel + quarter) | Per-channel revenue contribution, per-channel margin contribution, recommended rebalancing |\n\nAll scripts: stdlib only, argparse CLI, JSON or markdown output.\n\n---\n\n## References\n\n- [channel-models-direct-partner-marketplace.md](references/channel-models-direct-partner-marketplace.md) — 6 channel models in depth + economic structure + when each works\n- [margin-and-tco-frameworks.md](references/margin-and-tco-frameworks.md) — full TCO framework, allocation guidance, per-channel cost models\n- [channel-conflict-resolution.md](references/channel-conflict-resolution.md) — registration process, conflict patterns, arbitration\n\n---\n\n## Related skills\n\n- `business-growth/partnerships-architect` — strategic partnership design (this skill = the economics; that one = the strategy)\n- `business-growth/deal-desk` — approval mechanics for partner deals (this skill = \"what does it cost\"; deal desk = \"should we approve\")\n- `business-growth/pricing-strategy` — sets list pricing that channel economics deviates from\n- `business-growth/revenue-operations` — channel revenue is segmented in RevOps reporting\n- `business-growth/contract-and-proposal-writer` — drafts partner agreements\n- `sales-success/sales-operations` — runs channel ops (deal registration, MDF approval, certification tracking)\n- `c-level-advisor/cs-cro-advisor` — strategic channel-mix decisions are CRO-level","author":"@borghei","ownerProfile":null,"authorContacts":null,"sourceUrl":"https://github.com/borghei/Claude-Skills/tree/main/business-growth/channel-economics","license":"MIT","category":"design","lang":"en","tokens":3763,"stars":0,"calls30d":2,"claimed":false,"visibility":"public","origin":"crawler","version":"0.1.0","createdAt":"2026-08-22","updatedAt":"2026-08-22","files":[{"path":"references/channel-conflict-resolution.md","size":13916,"sha256":"2728ce6d12d8ad0d0e46068bc3dde90e489398c823487bc37d0ddfa62584b6a0"},{"path":"references/channel-models-direct-partner-marketplace.md","size":15108,"sha256":"048eeee4d87681b51679ee69b4e06aa7ca5dd5c77b069a89fce1739ff02f0e7f"},{"path":"references/margin-and-tco-frameworks.md","size":14220,"sha256":"85064cb11eab2035c07abef5de8bf58a658cd62ea4dea436428e07a9172f1963"},{"path":"scripts/channel_margin_calculator.py","size":11841,"sha256":"ae5560f48e1632a8d4e7153407e5487c7df1b6ccb0e40e392af794ccbbeac1ef"},{"path":"scripts/channel_mix_optimizer.py","size":6836,"sha256":"c4ecdd5530a5eee55032758834ced99e59cf83d71866a85651608792a9bbc220"},{"path":"scripts/partner_tier_economics.py","size":10156,"sha256":"c63a4c8406c169d94f49140ae404b4fa4632a243c52e31416894149eb5221007"}],"requires":{"mcp":[],"tools":[]},"safety":{"flags":[],"scannedAt":"2026-08-22","hasScripts":true,"networkEndpoints":[]}}