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channel-economics

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Chinese

channel-economics

渠道经济学

Purpose

用途

Help Head of Commercial / RevOps / VP Sales answer three questions at the quarterly channel review:
  1. What does each channel actually cost to serve, fully loaded? (direct headcount, channel manager attribution, partner discount, MDF, enablement time, support load, allocated overhead)
  2. What is the ROI of each channel under three lenses? (cash ROI year-1, LTV-adjusted ROI, marginal ROI — next dollar of investment)
  3. What is the optimal channel mix subject to our strategic constraints? (minimum direct floor, maximum partner concentration ceiling, sensitivity to CAC shifts)
The skill emits per-channel verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested mix recommendation, and the diminishing-returns inflection point. It does not pick the strategy — humans do, with the numbers loaded honestly for the first time.
帮助商务负责人/RevOps/销售副总裁在季度渠道复盘时解答三个问题：
  1. 各渠道的全负荷实际服务成本是多少？（直销人力成本、渠道经理分摊成本、合作伙伴折扣、市场开发基金(MDF)、赋能时间、支持负载、分配的间接费用）
  2. 从三个视角看，各渠道的ROI分别是多少？（第一年现金流ROI、经LTV调整的ROI、边际ROI——下一美元投资的收益）
  3. 在我们的战略约束下，最优渠道组合是什么？（直销最低占比、合作伙伴最高集中度、客户获取成本(CAC)变动的敏感性）
本技能会输出各渠道结论（DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT）、经敏感性测试的组合建议，以及收益递减拐点。本技能不制定战略——人类基于首次如实呈现的数据做出决策。

When to use

使用场景

  • Quarterly channel review: pipeline is 60/40 or 50/50 direct vs partner and you don't actually know which one is profitable
  • Considering hiring a channel manager — need to know if the channel can clear the loaded-cost bar
  • Partner program ROI question from the board ("we spent $X on MDF — what did we get?")
  • A segment is over-indexed to one channel and you suspect mix dogma is blocking the other
  • About to expand into a new region and need to decide direct-first vs partner-first
  • M&A diligence: target company claims "partner-led at 70% gross margin" — need to validate after loading
Do not use for:
  • Designing partner tiers, joint GTM motion, revshare splits → 
    partnerships-architect
  • SDR-to-AE routing, lead scoring, MQL definitions → 
    business-growth/revenue-operations
  • Strategic CRO decisions ("should we hire a VP Sales?", comp plan design) → 
    c-level-advisor/cro-advisor
  • Quarterly close, GAAP revenue recognition, channel-level P&L for historical reporting → 
    finance/financial-analysis
  • Per-deal discount approval → 
    deal-desk
  • Pricing model design → 
    pricing-strategist
  • 季度渠道复盘：渠道管线为60/40或50/50的直销vs合作伙伴模式，且你无法明确知晓哪类渠道盈利
  • 考虑招聘渠道经理——需确认该渠道能否覆盖全负荷成本门槛
  • 董事会提出的合作伙伴项目ROI问题（“我们在MDF上投入了X美元——获得了什么回报？”）
  • 某细分渠道占比过高，你怀疑组合教条阻碍了其他渠道的发展
  • 即将拓展新区域，需决定优先采用直销还是合作伙伴模式
  • 并购尽职调查：目标公司声称“合作伙伴主导模式毛利率达70%”——需在计入各项成本后验证该数据
请勿用于以下场景：
  • 设计合作伙伴层级、联合GTM运作、收入分成方案 → 
    partnerships-architect
  • SDR到AE的线索分配、线索评分、MQL定义 → 
    business-growth/revenue-operations
  • 首席营收官(CRO)战略决策（“我们是否应招聘销售副总裁？”、薪酬方案设计） → 
    c-level-advisor/cro-advisor
  • 季度结账、GAAP收入确认、用于历史报告的渠道级损益表 → 
    finance/financial-analysis
  • 单笔交易折扣审批 → 
    deal-desk
  • 定价模型设计 → 
    pricing-strategist

Workflow

工作流程

Step 1 — Intake channel data

步骤1 — 收集渠道数据

Fill 
assets/channel_data_template.md
(≈ 20 min). Capture per channel: deal count TTM, ARR TTM, avg deal size, gross margin %, CAC, sales-cycle days, retention rate, expansion rate, partner discount %, all attributable costs (SDR / AE / SE / channel manager / CS / support / marketing / partner MDF / tooling / overhead allocation %).
The template surfaces the costs teams most often forget: partner enablement time, certification investment, channel-conflict resolution overhead, channel-manager headcount cost.
填写
assets/channel_data_template.md
（约20分钟）。收集各渠道的以下数据：过去12个月的交易数量、过去12个月的经常性收入(ARR)、平均交易规模、毛利率、客户获取成本(CAC)、销售周期天数、留存率、扩张率、合作伙伴折扣率、所有可分摊成本（SDR/AE/SE/渠道经理/客户成功(CS)/支持/营销/合作伙伴MDF/工具/间接费用分配比例）。
该模板会凸显团队最常忽略的成本：合作伙伴赋能时间、认证投入、渠道冲突解决间接费用、渠道经理人力成本。

Step 2 — Compute cost-to-serve per channel

步骤2 — 计算各渠道的服务成本

Run 
scripts/cost_to_serve_calculator.py --input channel.json --output markdown
.
Output: fully-loaded cost-to-serve per deal AND per dollar of ARR, with direct costs broken out from allocated overhead, and a "true gross margin" line after channel-specific load. Flags double-counting and surfaces hidden costs.
Run once per channel. The "true gross margin" line is the input the next two scripts care about.
运行
scripts/cost_to_serve_calculator.py --input channel.json --output markdown
。
输出：按单笔交易和每美元ARR计算的全负荷服务成本，区分直接成本与分配的间接费用，并显示计入渠道特定成本后的“真实毛利率”项。标记重复计算项并凸显隐性成本。
每个渠道运行一次。“真实毛利率”项是后续两个脚本的输入数据。

Step 3 — Compute ROI per channel under three lenses

步骤3 — 从三个视角计算各渠道的ROI

Run 
scripts/channel_roi_analyzer.py --input roi.json --profile saas --output markdown
.
Output: per channel, three ROI numbers (Cash year-1, LTV-adjusted, Marginal), the diminishing-returns inflection point, and a verdict: DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT.
Verdict logic is deterministic and surfaced in the report. Humans can override; the skill won't.
运行
scripts/channel_roi_analyzer.py --input roi.json --profile saas --output markdown
。
输出：各渠道的三个ROI数值（第一年现金流ROI、经LTV调整的ROI、边际ROI）、收益递减拐点，以及结论：DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT。
结论逻辑是确定性的，并会在报告中呈现。人类可手动覆盖结论，本技能不会干预。

Step 4 — Optimize channel mix subject to constraints

步骤4 — 在约束条件下优化渠道组合

Run 
scripts/channel_mix_optimizer.py --input mix.json --profile saas --output markdown
.
Output: recommended mix that maximizes effective ARR subject to constraints (min direct %, max partner concentration), plus a sensitivity table (what if direct CAC rises 20%? what if partner discount widens 5 points?).
运行
scripts/channel_mix_optimizer.py --input mix.json --profile saas --output markdown
。
输出：在约束条件（直销最低占比、合作伙伴最高集中度）下最大化有效ARR的推荐组合，以及敏感性分析表（若直销CAC上升20%会怎样？若合作伙伴折扣扩大5个百分点会怎样？）。

Step 5 — Decide

步骤5 — 决策

Take the three reports into the quarterly channel review. The skill recommends; the human commits.
将三份报告带入季度渠道复盘会议。本技能提供建议，最终由人类做出决策。

Scripts

脚本

  • scripts/cost_to_serve_calculator.py
    — fully-loaded cost-to-serve per deal AND per $ ARR, with hidden-cost surfacing
  • scripts/channel_roi_analyzer.py
    — 3-lens ROI (Cash / LTV / Marginal) with verdicts and diminishing-returns inflection
  • scripts/channel_mix_optimizer.py
    — constrained mix optimizer with sensitivity scenarios
All scripts: stdlib only. 
--help
, 
--sample
, 
--input
, 
--output
work on all three. Industry tuning via 
--profile {saas,api,enterprise-software,marketplace,hardware}
on the two analyzers.
  • scripts/cost_to_serve_calculator.py
    — 按单笔交易和每美元ARR计算全负荷服务成本，凸显隐性成本
  • scripts/channel_roi_analyzer.py
    — 三视角ROI分析（现金流/LTV/边际收益），附带结论和收益递减拐点
  • scripts/channel_mix_optimizer.py
    — 带约束条件的组合优化工具，提供敏感性场景分析
所有脚本：仅使用标准库。三个脚本均支持
--help
、
--sample
、
--input
、
--output
参数。两个分析器可通过
--profile {saas,api,enterprise-software,marketplace,hardware}
参数进行行业调优。

References

参考资料

  • references/channel_economics_canon.md
    — Skok, Bessemer State of the Cloud, Tunguz, Pacific Crest / KeyBanc SaaS Survey, Ramanujam, Jay McBain (Canalys)
  • references/cost_to_serve_canon.md
    — Kaplan & Cooper (ABC), Horngren, Jeremy Hope, IBM CTS case studies, McKinsey, Gartner, BCG
  • references/channel_anti_patterns.md
    — Forrester, Tunguz, Hessling, HBR, SiriusDecisions, MIT Sloan, Gartner
  • references/channel_economics_canon.md
    — Skok、Bessemer云状态报告、Tunguz、Pacific Crest/KeyBanc SaaS调研、Ramanujam、Jay McBain（Canalys）
  • references/cost_to_serve_canon.md
    — Kaplan & Cooper（作业成本法ABC）、Horngren、Jeremy Hope、IBM CTS案例研究、麦肯锡、高德纳(Gartner)、波士顿咨询(BCG)
  • references/channel_anti_patterns.md
    — Forrester、Tunguz、Hessling、哈佛商业评论(HBR)、SiriusDecisions、麻省理工斯隆管理学院、高德纳(Gartner)

Assumptions

假设条件

  • Channel economics is a forward-looking question. Historical channel P&L is finance's job; this skill loads forward economics for a decision.
  • "Channel" means a coherent go-to-market motion (direct outbound, partner-led, marketplace, reseller, OEM). It does not mean a marketing source.
  • Cost-to-serve requires honest overhead allocation. The script validates that overhead % is consistent across channels — false partner-margin lift from inconsistent allocation is the #1 anti-pattern.
  • LTV inputs (retention, expansion) are per-channel, not pooled. Partner-sourced customers often retain differently than direct-sourced — this difference is usually the largest economic variable and the most ignored.
  • Industry profiles (
    --profile
    ) tune defaults for benchmarks (e.g., SaaS direct CAC payback target ~12mo, enterprise ~18mo) — they don't override your numbers.
  • This is a decision-support skill. Output is verdicts and a recommended mix, never an automatic resource reallocation.
  • 渠道经济学是一个前瞻性问题。历史渠道损益表是财务部门的工作；本技能加载前瞻性经济数据用于决策。
  • “渠道”指连贯的上市(GTM)运作模式（直销 outbound、合作伙伴主导、市场平台、经销商、OEM）。不指营销来源。
  • 服务成本计算需要如实的间接费用分配。脚本会验证各渠道的间接费用比例是否一致——不一致的分配导致的合作伙伴虚高毛利率是最常见的反模式。
  • LTV输入数据（留存率、扩张率）是按渠道划分的，而非汇总计算。合作伙伴来源的客户通常与直销客户的留存率不同——这种差异通常是最大的经济变量，也是最常被忽略的。
  • 行业配置文件(
    --profile
    )会调整基准默认值（例如SaaS直销CAC回收期目标约12个月，企业级约18个月）——不会覆盖你输入的数据。
  • 本技能是决策支持工具。输出内容为结论和推荐组合，绝不会自动进行资源重新分配。

Anti-patterns

反模式

  • Treating "influenced" deals as "sourced" deals. A partner that touched a deal your AE already had is not channel-sourced revenue. Loading this as partner revenue inflates partner ROI and inflates direct CAC simultaneously.
  • Inconsistent overhead allocation. Allocating 25% overhead to direct deals and 5% to partner deals because "the partner handles the overhead" is false. The partner manager, partner program, MDF, certification, and conflict-resolution all live in your P&L.
  • Ignoring enablement time as a cost. Every hour your AE spends co-selling with a partner is a direct cost charged to the partner channel — most teams forget to load it.
  • MDF without ROI tracking. Market Development Funds disbursed without an attributable pipeline ROI are just a partner-discount extension. The skill flags MDF with no return.
  • Channel-mix dogma. "We're a partner-first company" / "we don't sell direct" blocks profitable segments. Mix should follow the math, not the slogan.
  • Computing channel ROI without retention differential. If partner-sourced customers churn 5 points higher than direct, ignoring it overstates partner LTV by 30-50%. Per-channel retention is mandatory input.
  • No cost-attribution for channel-manager headcount. A $200k channel manager managing $4M of partner ARR is $50 of channel-manager cost per $1k ARR — material to the verdict.
  • Confusing this skill with partnerships-architect. That skill designs the partner program. This skill tells you whether the program pays for itself.
  • 将“影响型”交易视为“来源型”交易。合作伙伴接触了AE已跟进的交易，并不代表该收入属于渠道来源。将此类收入计入合作伙伴收入会同时夸大合作伙伴ROI和直销CAC。
  • 不一致的间接费用分配。将直销交易的间接费用分配为25%，合作伙伴交易的分配为5%，理由是“合作伙伴承担间接费用”，这是错误的。渠道经理、合作伙伴项目、MDF、认证、冲突解决等成本均计入你的损益表。
  • 忽略赋能时间成本。AE花在与合作伙伴联合销售上的每一小时都是计入合作伙伴渠道的直接成本——大多数团队会忘记计入这项成本。
  • 无ROI跟踪的MDF。未对应可归因管线ROI的市场开发基金(MDF)只是合作伙伴折扣的延伸。本技能会标记无回报的MDF。
  • 渠道组合教条。“我们是合作伙伴优先的公司”/“我们不做直销”会阻碍盈利细分市场的发展。组合应遵循数据，而非口号。
  • 计算渠道ROI时忽略留存率差异。若合作伙伴来源客户的流失率比直销客户高5个百分点，忽略这一点会高估合作伙伴LTV 30-50%。按渠道划分的留存率是必填输入项。
  • 未分摊渠道经理人力成本。一位年薪20万美元的渠道经理管理400万美元的合作伙伴ARR，相当于每1000美元ARR对应50美元渠道经理成本——这对结论有实质性影响。
  • 混淆本技能与partnerships-architect。后者设计合作伙伴项目，前者判断该项目是否能回本。

Distinct from

区别于其他技能

  • commercial/partnerships-architect — partner tier design, joint GTM motion, revshare splits, partner enablement. Partner program structure, not partner program economics. This skill consumes the program structure as input and emits the economic verdict.
  • business-growth/revenue-operations — lead routing, SDR motion, MQL definition, pipeline operations. RevOps owns the funnel mechanics; this skill loads the channel-level economic outcome.
  • c-level-advisor/cro-advisor — strategic CRO judgment: when to hire a VP Sales, comp plan philosophy, territory design, multi-year revenue strategy. CRO advisor consumes channel-economics output as one input among many.
  • finance/financial-analysis — close-and-report on historical channel P&L per GAAP. This skill is forward-looking decision support; finance is historical record. Different time horizon, different audience, different output.
  • commercial/deal-desk — per-deal discount approval. Operates daily; this skill operates quarterly.
  • commercial/pricing-strategist — pricing model and tier design. Pricing is input; channel economics is what happens at that pricing across channels.
  • commercial/partnerships-architect — 合作伙伴层级设计、联合GTM运作、收入分成方案、合作伙伴赋能。负责合作伙伴项目的结构，而非合作伙伴项目的经济学。本技能将项目结构作为输入，输出经济结论。
  • business-growth/revenue-operations — 线索分配、SDR运作、MQL定义、管线运营。RevOps负责漏斗机制；本技能加载渠道级经济结果。
  • c-level-advisor/cro-advisor — 首席营收官(CRO)战略决策：何时招聘销售副总裁、薪酬方案理念、区域设计、多年收入战略。CRO顾问将渠道经济学输出作为众多输入之一。
  • finance/financial-analysis — 按GAAP对历史渠道损益表进行结账和报告。本技能是前瞻性决策支持工具；财务部门负责历史记录。时间范围、受众、输出内容均不同。
  • commercial/deal-desk — 单笔交易折扣审批。日常运作；本技能按季度运作。
  • commercial/pricing-strategist — 定价模型和层级设计。定价是输入项；渠道经济学是该定价在各渠道中的表现。

Forcing-question library (Matt Pocock grill discipline)

强制问题库（Matt Pocock grill discipline）

Walked one at a time by 
/cs:grill-commercial
or the orchestrator. Recommended answer + canon citation per question. Never bundled.
  1. "What's your fully-loaded cost-to-serve per channel — including channel-manager headcount, MDF, partner enablement time, and overhead allocation?" Recommended: load all four. Most teams load partner discount but forget the channel-manager headcount and the enablement time, inflating partner margin by 8-15 points. Canon: Kaplan & Cooper (HBR 1988) — Measure Costs Right: Make the Right Decisions. Activity-Based Costing was invented precisely because channel costs hide in overhead and distort margin comparisons.
  2. "What is the retention differential between direct-sourced and partner-sourced customers?" Recommended: instrument per-channel retention BEFORE running channel ROI. A 5-point retention gap moves LTV by 30-50%. Canon: David Skok (For Entrepreneurs — SaaS Metrics 2.0). LTV = (ARPA × Gross Margin) / Churn. Channel-blind churn is the most common source of false channel ROI.
  3. "What share of 'channel-sourced' pipeline did your team actually originate?" Recommended: if your AE already had the account, it's not channel-sourced — it's channel-influenced. Influence and source are different economic lines. Canon: SiriusDecisions / Forrester channel attribution research — confused source vs. influence is the #1 reason partner ROI is overstated industry-wide.
  4. "What is the marginal ROI of the next dollar invested in partner program vs. direct sales?" Recommended: compute the diminishing-returns curve on both. Average ROI hides the fact that the next dollar might earn 0.3x while the average earns 2.1x. Canon: Tomasz Tunguz (Tomasz Tunguz blog — channel CAC analyses). Average ROI is a vanity metric; marginal ROI drives investment decisions.
  5. "What's your MDF-to-attributable-pipeline ratio in the last 4 quarters?" Recommended: < 5:1 (every $1 of MDF should generate ≥ $5 of attributable pipeline within 2 quarters). Anything looser is partner-discount theatre. Canon: Jay McBain (Canalys) — State of the Channel research. MDF without attribution discipline is the most expensive form of channel subsidy.
  6. "Is your channel-mix dogma blocking a profitable segment?" Recommended: surface the dogma ("we're partner-first", "we don't sell direct in SMB") explicitly. Mix should follow the segment math. Canon: MIT Sloan Management Review — When Channel Conflict Means Growth. Dogmatic single-channel strategies forfeit 15-25% of TAM in mid-market specifically.
  7. "What overhead-allocation methodology are you applying — and is it consistent across direct and partner?" Recommended: same methodology, same denominator, both channels. Inconsistent allocation is the silent killer of channel-economics analysis. Canon: Charles Horngren (Cost Accounting: A Managerial Emphasis) — allocation consistency is the precondition for cross-segment margin comparison. Without it, every conclusion is contaminated.
Walk depth-first. Lock 1-3 before opening 4-7. After all 7 are answered, invoke 
cost_to_serve_calculator.py
→ 
channel_roi_analyzer.py
→ 
channel_mix_optimizer.py
in sequence.
由
/cs:grill-commercial
或编排器逐一提出。每个问题配有推荐答案和参考资料引用。绝不批量提问。
  1. “各渠道的全负荷服务成本是多少——包括渠道经理人力成本、MDF、合作伙伴赋能时间和间接费用分配？” 推荐答案：计入全部四项成本。大多数团队仅计入合作伙伴折扣，却忽略渠道经理人力成本和赋能时间，导致合作伙伴毛利率被高估8-15个百分点。 参考资料：Kaplan & Cooper（哈佛商业评论1988）——《正确衡量成本：做出正确决策》。作业成本法(ABC)的发明正是因为渠道成本隐藏在间接费用中，扭曲了毛利率对比。
  2. “直销来源与合作伙伴来源客户的留存率差异是多少？” 推荐答案：在计算渠道ROI之前，先按渠道统计留存率。5个百分点的留存率差距会使LTV变动30-50%。 参考资料：David Skok（For Entrepreneurs——SaaS指标2.0）。LTV = (ARPA × 毛利率) / 流失率。不区分渠道的流失率是导致渠道ROI计算错误的最常见原因。
  3. “你们团队实际发起的‘渠道来源’管线占比是多少？” 推荐答案：若AE已跟进该客户，则不属于渠道来源——而是渠道影响。影响和来源是不同的经济范畴。 参考资料：SiriusDecisions/Forrester渠道归因研究——混淆来源与影响是行业内合作伙伴ROI被高估的首要原因。
  4. “合作伙伴项目与直销团队下一美元投资的边际ROI分别是多少？” 推荐答案：计算两者的收益递减曲线。平均ROI掩盖了下一美元投资可能仅获0.3倍回报，而平均回报为2.1倍的事实。 参考资料：Tomasz Tunguz（Tomasz Tunguz博客——渠道CAC分析）。平均ROI是虚荣指标；边际ROI驱动投资决策。
  5. “过去4个季度中，MDF与可归因管线的比例是多少？” 推荐答案：< 5:1（每1美元MDF应在2个季度内产生≥5美元的可归因管线）。比例超过该值就是合作伙伴折扣的幌子。 参考资料：Jay McBain（Canalys）——《渠道状态》研究。无归因规范的MDF是最昂贵的渠道补贴形式。
  6. “你们的渠道组合教条是否阻碍了盈利细分市场的发展？” 推荐答案：明确指出教条内容（“我们是合作伙伴优先”、“我们不在SMB领域做直销”）。组合应遵循细分市场的数据。 参考资料：麻省理工斯隆管理评论——《当渠道冲突意味着增长》。教条式的单一渠道策略会错失中端市场15-25%的总可寻址市场(TAM)。
  7. “你们采用的间接费用分配方法是什么——且在直销与合作伙伴渠道间是否一致？” 推荐答案：采用相同的方法、相同的分母，应用于两个渠道。不一致的分配是渠道经济学分析的隐形杀手。 参考资料：Charles Horngren（《成本会计：管理视角》）——分配一致性是跨细分市场毛利率对比的前提。没有一致性，所有结论都会失真。
按深度优先原则进行。在开启问题4-7之前，先锁定问题1-3的答案。所有7个问题回答完毕后，依次调用
cost_to_serve_calculator.py
→ 
channel_roi_analyzer.py
→ 
channel_mix_optimizer.py
。