biz-cac-ltv

asgard-ai-platform ｜ 商業與營運 ｜ 原文 ｜ MIT

用 CAC 和 LTV 評估單位經濟效益與行銷效率

---
name: "biz-cac-ltv"
description: "計算並分析客戶獲取成本（CAC）和客戶終身價值（LTV），評估單位經濟效益與行銷效率。當使用者需要評估客戶獲取是否有獲利、最佳化行銷預算分配、或評估商業模式可行性時使用，即使他們說的是「我們是不是廣告花太多了」、「每個客戶值多少錢」或「我們的成長可持續嗎」也一樣。"
metadata:
  category: "WP-14 商學院—行銷"
  tags: ["marketing", "unit-economics", "cac", "ltv"]
---

# CAC 與 LTV 分析

## 概述

CAC（客戶獲取成本）和 LTV（客戶終身價值）是兩個最基本的單位經濟效益指標。合起來，它們回答的是：「每個客戶帶來的營收，比獲取他們的成本多嗎？」LTV:CAC 比率是行銷效率和商業模式可行性唯一最重要的指標。

## 何時使用

**觸發條件：**
- 使用者在評估行銷支出的效率
- 使用者問「每個客戶值多少錢？」或「我們是不是行銷花太多了？」
- 使用者在評估商業模式的可行性或募資指標
- 使用者需要在各個獲取通路之間分配預算

**何時不要用：**
- 產品定價決策 → 用定價策略
- 顧客區隔 → 用 STP 或 RFM
- 完整的財務分析 → 用財務比率

## 框架

```
鐵律：健康的事業，LTV:CAC > 3

要能永續經營，LTV:CAC 比率至少要 3:1。
- < 1:1 = 你每獲取一個客戶就在「賠錢」
- 1-3:1 = 除非能降低 CAC 或提高 LTV，否則不可持續
- 3-5:1 = 健康
- > 5:1 = 可能在成長上投資不足（把市占留給別人）

這個比率適用於「混合」平均。只要整體混合超過 3:1，
個別通路可以低於 3:1。
```

```
鐵律：CAC 必須包含「所有」獲取成本

CAC = 行銷與業務總支出 / 獲得的新客戶數

「總支出」包含：廣告費、行銷團隊薪資、業務團隊薪資、工具、
內容製作、活動，也就是那段期間為了獲取客戶花的「一切」。
排除薪資或工具，會低估真實的 CAC。
```

### 步驟 1：計算 CAC

**基本公式：**
```
CAC = 該期間的總獲取支出 / 該期間獲得的新客戶數
```

**依通路：**
```
CAC（通路 X）= 通路 X 的支出 / 來自通路 X 的客戶數
```

總獲取支出要包含：
- 廣告（數位 + 線下）
- 行銷團隊的薪酬
- 業務團隊的薪酬（B2B）
- 行銷工具和軟體
- 內容製作成本
- 活動和贊助
- 代理商費用

### 步驟 2：計算 LTV

**簡單公式：**
```
LTV = ARPU × 毛利率 % × 平均客戶存續期間
```

其中：
- **ARPU** = 每期（每月或每年）每位使用者的平均營收
- **毛利率 %** = (營收 - COGS) / 營收
- **平均客戶存續期間** = 1 / 流失率

**以 cohort 為基礎（更準確）：**
追蹤每個客戶 cohort 隨時間的實際營收。加總每位客戶的累計營收，再套用毛利率。

### 步驟 3：計算關鍵比率

| 指標 | 公式 | 健康基準 |
|--------|---------|-------------------|
| **LTV:CAC** | LTV / CAC | > 3:1 |
| **回收期** | CAC / (ARPU × 毛利率) | < 12 個月 |
| **CAC 占 LTV 的 %** | CAC / LTV × 100 | < 33% |

### 步驟 4：區隔分析

依以下面向計算 CAC 和 LTV：
- **通路**：哪些獲取通路效率最高？
- **客群**：哪些客群的 LTV:CAC 最高？
- **Cohort**：LTV 隨時間是變好還是變差？

### 步驟 5：最佳化策略

**降低 CAC：**
- 把預算轉移到 CAC 較低的通路
- 提高轉換率（更好的登陸頁、銷售流程）
- 增加自然／推薦的獲取（內容、口碑）

**提高 LTV：**
- 降低流失（改善產品、客戶成功）
- 提高 ARPU（追加銷售、交叉銷售、漲價）
- 延長客戶存續期間（忠誠度方案、轉換成本）

## 輸出格式

```markdown
# CAC-LTV 分析：{公司/產品}

## 單位經濟效益摘要

| 指標 | 數值 | 基準 | 狀態 |
|--------|-------|-----------|--------|
| CAC（混合） | ${X} | — | — |
| LTV | ${X} | — | — |
| LTV:CAC | {X}:1 | > 3:1 | ✓/✗ |
| 回收期 | {X} 個月 | < 12 個月 | ✓/✗ |

## 各通路的 CAC

| 通路 | 支出 | 客戶數 | CAC | 占總額 % |
|---------|-------|-----------|-----|-----------|
| {通路} | ${X} | {N} | ${X} | {X%} |

## LTV 計算

- ARPU：${X}/月
- 毛利率：{X%}
- 平均存續期間：{X} 個月（流失率：{X%}/月）
- LTV = ${X}

## 各區隔的 LTV:CAC

| 區隔 | CAC | LTV | 比率 | 行動 |
|---------|-----|-----|-------|--------|
| {區隔 A} | ${X} | ${X} | {X}:1 | 加碼 / 維持 / 砍掉 |

## 最佳化建議
1. ...
2. ...
```

## 範例

### 正確的應用

**情境：** 台灣一個 B2C 訂閱盒（每月 NT$599）的 CAC-LTV

**CAC 計算：**
| 項目 | 每月支出 |
|------|-------------|
| Facebook/Instagram 廣告 | NT$200,000 |
| Google Ads | NT$80,000 |
| KOL 合作 | NT$50,000 |
| 行銷團隊（2 人） | NT$120,000 |
| **合計** | **NT$450,000** |

當月新客戶：300
**CAC = NT$450,000 / 300 = NT$1,500**

**LTV 計算：**
- ARPU：NT$599/月
- 毛利率：55%
- 每月流失率：8% → 平均存續期間：1/0.08 = 12.5 個月
- **LTV = NT$599 × 0.55 × 12.5 = NT$4,118**

**LTV:CAC = 4,118 / 1,500 = 2.75:1**，低於 3:1 的門檻。需要降低 CAC，或改善留存。

### 錯誤的應用

**哪裡出錯：**
- CAC 只算「廣告費 / 新客戶數」，排除了每月 NT$120K 的行銷團隊薪資 → 真實的 CAC 是 NT$1,500，不是 NT$1,100。違反鐵律：要包含所有獲取成本。
- 回報 LTV:CAC 為 1.8:1，並說「因為我們在成長，所以還好」→ 在 LTV:CAC < 3:1 的情況下成長，代表你是在成長成更大的虧損。違反鐵律：比率必須 > 3:1。

## 常見陷阱

- **歸因很亂**：一位客戶看了 Instagram 廣告、用 Google 搜尋你的品牌、然後透過推薦連結註冊，功勞算給哪個通路？歸因的方法要一致（首次接觸、最後接觸或多點接觸）。
- **混合 vs 邊際 CAC**：混合 CAC 包含所有通路。邊際 CAC 是多獲取「一位」客戶的成本。規模擴大後，邊際 CAC 通常會上升（最好的通路會先飽和）。
- **LTV 永遠是估計值**：未來的流失和消費行為是不確定的。要用保守的假設，並隨著真實 cohort 資料累積而更新。
- **回收期影響現金流**：就算 LTV:CAC 是 5:1，如果回收要 24 個月，你也需要大量的前期資金。快速成長的公司，就算單位經濟效益很好，也可能死於太長的回收期。
- **負流失是超能力**：如果擴張營收（追加銷售）超過流失的營收，淨營收留存率就 > 100%。這代表 LTV 會隨時間成長，是最理想的情況。

## 腳本

| 腳本 | 說明 | 用法 |
|--------|-------------|-------|
| `scripts/cac_ltv.py` | 計算 CAC、LTV、LTV/CAC 比率和回收期 | `python scripts/cac_ltv.py --help` |

執行 `python scripts/cac_ltv.py --verify` 可以跑內建的健全性測試。

## 參考資料

- 以 cohort 為基礎的 LTV 計算方法，見 `references/cohort-ltv.md`
- 通路歸因模型，見 `references/attribution-models.md`

---
name: "biz-cac-ltv"
description: "Calculate and analyze Customer Acquisition Cost (CAC) and Customer Lifetime Value (LTV) to evaluate unit economics and marketing efficiency. Use this skill when the user needs to assess whether their customer acquisition is profitable, optimize marketing spend allocation, or evaluate business model viability — even if they say 'are we spending too much on ads', 'what's each customer worth', or 'is our growth sustainable'."
metadata:
  category: "WP-14 商學院—行銷"
  tags: ["marketing", "unit-economics", "cac", "ltv"]
---

# CAC and LTV Analysis

## Overview

CAC (Customer Acquisition Cost) and LTV (Customer Lifetime Value) are the two fundamental unit economics metrics. Together they answer: "Does each customer generate more revenue than it costs to acquire them?" The LTV:CAC ratio is the single most important indicator of marketing efficiency and business model viability.

## When to Use

**Trigger conditions:**
- User evaluating marketing spend efficiency
- User asks "what's each customer worth?" or "are we spending too much on marketing?"
- User assessing business model viability or fundraising metrics
- User needs to allocate budget across acquisition channels

**When NOT to use:**
- For product pricing decisions → use Pricing Strategy
- For customer segmentation → use STP or RFM
- For comprehensive financial analysis → use financial ratios

## Framework

```
IRON LAW: LTV:CAC > 3 for Healthy Business

LTV:CAC ratio must be at least 3:1 for sustainable businesses.
- < 1:1 = You're LOSING money on every customer
- 1-3:1 = Unsustainable unless you can reduce CAC or increase LTV
- 3-5:1 = Healthy
- > 5:1 = Potentially underinvesting in growth (leaving market share on the table)

This ratio applies to the BLENDED average. Individual channels can be
below 3:1 if the overall blend exceeds it.
```

```
IRON LAW: CAC Must Include ALL Acquisition Costs

CAC = Total marketing & sales spend / Number of new customers acquired

"Total spend" includes: ad spend, marketing team salaries, sales team
salaries, tools, content production, events — EVERYTHING spent to acquire
customers in that period. Excluding salaries or tools understates true CAC.
```

### Step 1: Calculate CAC

**Basic formula:**
```
CAC = Total acquisition spend in period / New customers acquired in period
```

**By channel:**
```
CAC (Channel X) = Spend on Channel X / Customers from Channel X
```

Include in total acquisition spend:
- Advertising (digital + offline)
- Marketing team compensation
- Sales team compensation (for B2B)
- Marketing tools and software
- Content production costs
- Events and sponsorships
- Agency fees

### Step 2: Calculate LTV

**Simple formula:**
```
LTV = ARPU × Gross Margin % × Average Customer Lifespan
```

Where:
- **ARPU** = Average Revenue Per User per period (monthly or annual)
- **Gross Margin %** = (Revenue - COGS) / Revenue
- **Average Customer Lifespan** = 1 / Churn Rate

**Cohort-based (more accurate):**
Track actual revenue per customer cohort over time. Sum cumulative revenue per customer, apply gross margin.

### Step 3: Calculate Key Ratios

| Metric | Formula | Healthy Benchmark |
|--------|---------|-------------------|
| **LTV:CAC** | LTV / CAC | > 3:1 |
| **Payback Period** | CAC / (ARPU × Gross Margin) | < 12 months |
| **CAC % of LTV** | CAC / LTV × 100 | < 33% |

### Step 4: Segment Analysis

Calculate CAC and LTV by:
- **Channel**: Which acquisition channels are most efficient?
- **Customer segment**: Which segments have highest LTV:CAC?
- **Cohort**: Is LTV improving or degrading over time?

### Step 5: Optimization Strategies

**To reduce CAC:**
- Shift budget to lower-CAC channels
- Improve conversion rates (better landing pages, sales process)
- Increase organic/referral acquisition (content, word-of-mouth)

**To increase LTV:**
- Reduce churn (improve product, customer success)
- Increase ARPU (upsell, cross-sell, price increases)
- Extend customer lifespan (loyalty programs, switching costs)

## Output Format

```markdown
# CAC-LTV Analysis: {Company/Product}

## Unit Economics Summary

| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| CAC (blended) | ${X} | — | — |
| LTV | ${X} | — | — |
| LTV:CAC | {X}:1 | > 3:1 | ✓/✗ |
| Payback Period | {X} months | < 12 months | ✓/✗ |

## CAC by Channel

| Channel | Spend | Customers | CAC | % of Total |
|---------|-------|-----------|-----|-----------|
| {channel} | ${X} | {N} | ${X} | {X%} |

## LTV Calculation

- ARPU: ${X}/month
- Gross Margin: {X%}
- Avg Lifespan: {X} months (churn rate: {X%}/month)
- LTV = ${X}

## LTV:CAC by Segment

| Segment | CAC | LTV | Ratio | Action |
|---------|-----|-----|-------|--------|
| {seg A} | ${X} | ${X} | {X}:1 | Invest / Maintain / Cut |

## Optimization Recommendations
1. ...
2. ...
```

## Examples

### Correct Application

**Scenario:** CAC-LTV for a Taiwanese B2C subscription box (monthly NT$599)

**CAC calculation:**
| Item | Monthly Spend |
|------|-------------|
| Facebook/Instagram ads | NT$200,000 |
| Google Ads | NT$80,000 |
| KOL partnerships | NT$50,000 |
| Marketing team (2 people) | NT$120,000 |
| **Total** | **NT$450,000** |

New customers in month: 300
**CAC = NT$450,000 / 300 = NT$1,500**

**LTV calculation:**
- ARPU: NT$599/month
- Gross Margin: 55%
- Monthly churn: 8% → Avg lifespan: 1/0.08 = 12.5 months
- **LTV = NT$599 × 0.55 × 12.5 = NT$4,118**

**LTV:CAC = 4,118 / 1,500 = 2.75:1** — Below the 3:1 threshold. Need to either reduce CAC or improve retention.

### Incorrect Application

**What went wrong:**
- CAC calculated as "ad spend / new customers" only, excluding NT$120K/month marketing team salary → True CAC is NT$1,500, not NT$1,100. Violates Iron Law: include ALL acquisition costs.
- LTV:CAC of 1.8:1 reported as "good because we're growing" → Growth at LTV:CAC < 3:1 means you're growing into larger losses. Violates Iron Law: ratio must be > 3:1.

## Gotchas

- **Attribution is messy**: A customer who saw an Instagram ad, Googled your brand, then signed up via a referral link — which channel gets credit? Be consistent in attribution methodology (first-touch, last-touch, or multi-touch).
- **Blended vs marginal CAC**: Blended CAC includes all channels. Marginal CAC is the cost of acquiring ONE MORE customer. As you scale, marginal CAC typically rises (best channels saturate first).
- **LTV is always an estimate**: Future churn and spending behavior are uncertain. Use conservative assumptions and update with real cohort data as it accumulates.
- **Payback period matters for cash flow**: Even with LTV:CAC of 5:1, if payback takes 24 months, you need significant upfront capital. Fast-growing companies can die from long payback periods despite great unit economics.
- **Negative churn is a superpower**: If expansion revenue (upsells) exceeds lost revenue (churn), Net Revenue Retention > 100%. This means LTV grows over time — the best possible scenario.

## Scripts

| Script | Description | Usage |
|--------|-------------|-------|
| `scripts/cac_ltv.py` | Compute CAC, LTV, LTV/CAC ratio, and payback period | `python scripts/cac_ltv.py --help` |

Run `python scripts/cac_ltv.py --verify` to execute built-in sanity tests.

## References

- For cohort-based LTV calculation methods, see `references/cohort-ltv.md`
- For channel attribution models, see `references/attribution-models.md`