--- name: china-unit-economics description: Unit economics analysis for China-focused portfolio companies. Adapted from the original unit-economics skill for Chinese business models, pricing, and market dynamics. Triggers on "A股单位经济模型", "单元经济模型", "unit economics China", "unit economics [company]", "LTV/CAC China", or "Cohort analysis [company]". --- # china-unit-economics ## Purpose Analyze **A股及中国市场单元经济模型** — per-unit economics, customer economics, and cohort analysis for portfolio companies. ## Key Metrics ### Core Framework (Same as Global) | Metric | Formula | Target | |--------|---------|--------| | LTV (Customer Lifetime Value) | ARPU × Lifetime × Gross Margin | >3x CAC | | CAC (Customer Acquisition Cost) | Sales & Marketing / New Customers | <12-month payback | | LTV/CAC | LTV / CAC | >3.0x | | CAC Payback (months) | CAC / (ARPU × Gross Margin %) | <12 months | | NRR (Net Revenue Retention) | (Start + Expansion - Churn) / Start | >100% | | GRR (Gross Revenue Retention) | (Start - Churn) / Start | >85% | | ARR | Annual Recurring Revenue | Growing | | Churn Rate | Lost customers / Total | <5% monthly | ### China-Specific Metrics | Metric | Description | China Context | |--------|-------------|---------------| | 获客成本 | CAC in Chinese context | 线上投放 + 线下渠道 | | 用户生命周期价值 | LTV for Chinese consumers | Higher for tier-1 | | 复购率 | Repeat purchase rate | Critical for DTC brands | | 客单价 | Average order value | 价格敏感 market | | 渠道成本 | Channel economics | 经销商 vs DTC | | 补贴依赖 | Subsidy / discount dependence | Common in China | ## Data Sources ### Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选) ```python # For public companies, extract proxies get_financials(ticker, "income") → Revenue, opex get_financials(ticker, "balance") → Customer-related assets get_financials(ticker, "cashflow") → Cash flow ``` ### Secondary Sources - 巨潮 — company filings with segment data - 管理层指引 — management guidance - 券商研报 — unit economics estimates - 行业数据 — industry benchmarks ## Workflow ### Step 1: Define Unit Economics Model **Business model identification:** | Business Model | Unit Definition | Revenue Model | |----------------|-----------------|---------------| | 消费品 | 每单 / 每用户 | Transaction | | SaaS | 每客户 (年) | Subscription | | 电商 | 每订单 / 每用户 | Transaction | | 制造业 | 每件 / 每吨 | Unit sales | | 平台 | 每GMV / 每交易 | Take rate | | 广告 | 每曝光 / 每点击 | CPM / CPC | ### Step 2: Build Unit Economics Model **Standard model:** ```python # Unit economics calculation Unit_Price = XX元 Unit_Cost = XX元 (COGS) Unit_Contribution = Unit_Price - Unit_Cost # Customer economics (for subscription/DTC) CAC = XX元 (acquisition cost per customer) ARPU = XX元/年 (average revenue per user) Gross_Margin = XX% Customer_Lifetime = X年 (or 1/churn rate) LTV = ARPU × Lifetime × Gross_Margin LTV_CAC = LTV / CAC Payback_Months = CAC / (ARPU × Gross_Margin / 12) ``` ### Step 3: Cohort Analysis **Cohort table (retention):** | Cohort | Month 0 | Month 1 | Month 2 | Month 3 | Month 6 | Month 12 | |--------|---------|---------|---------|---------|---------|----------| | Jan | 100% | XX% | XX% | XX% | XX% | XX% | | Feb | 100% | XX% | XX% | XX% | XX% | XX% | | Mar | 100% | XX% | XX% | XX% | XX% | XX% | **Cohort revenue:** | Cohort | Month 0 | Month 1 | Month 2 | Month 3 | Month 6 | Month 12 | |--------|---------|---------|---------|---------|---------|----------| | Jan | ¥X | ¥X | ¥X | ¥X | ¥X | ¥X | | Feb | ¥X | ¥X | ¥X | ¥X | ¥X | ¥X | ### Step 4: Benchmarking **China-specific benchmarks by industry:** | Industry | CAC Payback | LTV/CAC | Typical ARPU | |----------|-------------|---------|--------------| | 消费品牌 | 6-12 months | 3-5x | ¥200-500 | | SaaS (ToB) | 12-18 months | 3-5x | ¥5,000-50,000 | | 电商 | 1-3 months | 2-4x | ¥100-300 | | 游戏 | 1-2 months | 4-10x | ¥50-200 | | 在线教育 | 3-6 months | 2-4x | ¥1,000-5,000 | | 金融科技 | 6-12 months | 3-5x | ¥500-2,000 | ### Step 5: Sensitivity Analysis **Key sensitivities:** | Variable | -20% | -10% | Base | +10% | +20% | |----------|------|------|------|------|------| | ARPU | | | | | | | Gross margin | | | | | | | Customer lifetime | | | | | | | CAC | | | | | | ### Step 6: Recommendations **Based on unit economics:** | LTV/CAC | Assessment | Recommendation | |---------|------------|---------------| | >5x | Excellent | Scale aggressively | | 3-5x | Good | Scale with monitoring | | 2-3x | Acceptable | Optimize CAC/margin | | 1-2x | Poor | Fix model before scaling | | <1x | Broken | Fundamental rethink | ## China-Specific Considerations ### Customer Acquisition in China | Channel | CAC | Quality | Notes | |---------|-----|---------|-------| | 线上投放 (Online ads) | Medium | Variable | 抖音, 小红书, 百度 | | 社交裂变 (Social referral) | Low | Medium | 拼多多 model | | 经销商 (Distribution) | Low | Depends | 渠道下沉 | | 线下门店 (Offline stores) | High | High | Premium experience | | 直播带货 (Livestream) | Medium | Variable | 抖音, 淘宝直播 | | 私域运营 (Private traffic) | Low | High | WeChat ecosystem | ### China Consumer Behavior | Behavior | Impact on Unit Economics | |----------|-------------------------| | 价格敏感 | Lower ARPU, higher churn on price increases | | 社交驱动 | Viral referral reduces CAC | | 品牌忠诚度 | Higher LTV for established brands | | 渠道偏好 | Multi-channel complexity | | 促销依赖 | Revenue quality concerns | ### E-commerce Unit Economics **Key metrics for China e-commerce:** | Metric | Formula | Benchmark | |--------|---------|-----------| | GMV | Gross merchandise value | Top-line | | Take rate | Revenue / GMV | 3-10% | | Customer acquisition | CAC / order | ¥20-200 | | Return rate | Returns / orders | 5-20% (sector varies) | | AOV | Revenue / orders | ¥50-500 | | Fulfillment cost | Logistics / order | ¥5-30 | ## Quality Checks Before delivering: - [ ] Unit defined clearly - [ ] Revenue model correct - [ ] CAC/LTV calculated correctly - [ ] Cohort data (if available) incorporated - [ ] Benchmarking relevant - [ ] Sensitivities run - [ ] Recommendations actionable > **Data Source Mode Switch**: Set env var `IFIND_DATA_SOURCE_MODE` to control data source preference. > - `ifind-only` (strict): Use iFind only, error if unavailable > - `ifind-fallback` (default): iFind preferred, fallback to AkShare > - `akshare-only, wind-only (Wind only), wind-fallback (Wind first, fallback to iFind → AkShare)`: Skip iFind, use AkShare only