customer-ltv-calculator

name	customer-ltv-calculator
description	Calculate customer lifetime value using historical purchase data, cohort analysis, and predictive modeling
allowed-tools	["Read","Write","Bash","Grep"]
effort	high

When to activate

• Calculating customer LTV for marketing budget allocation
• Building cohort-based retention and revenue models
• Identifying high-value customer segments
• Forecasting recurring revenue from existing customers
• Evaluating CAC:LTV ratios for channel efficiency

When NOT to use

• For one-time purchase analysis (use analytics-reporter)
• For real-time cart value calculations
• For subscription billing management

Instructions

1. Extract purchase history. Pull order data: customer_id, order_date, order_value, product_category, channel.
2. Build cohort table. Group customers by first-purchase month; track retention and repeat purchase rates over 12 months.
3. Calculate historical LTV. Sum total revenue per customer; compute mean, median, and percentile distributions.
4. Model predictive LTV. Use RFM scoring (Recency, Frequency, Monetary) to project 12-month and 24-month LTV.
5. Segment by LTV tier. Classify: VIP (top 10%), High (10-30%), Medium (30-70%), Low (bottom 30%).
6. Compute CAC:LTV ratio. By acquisition channel — target minimum 3:1 LTV:CAC for sustainable growth.
7. Output report. Cohort heatmap, LTV distribution chart, segment counts, and channel efficiency matrix.

Example

LTV Formula:
LTV = (Average Order Value × Purchase Frequency × Customer Lifespan) × Gross Margin %

Cohort LTV (6-month):
Jan 2026 cohort: $127 avg LTV, 34% retention at M6
Feb 2026 cohort: $142 avg LTV, 38% retention at M5