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)

# 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:

# 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