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Customer Lifetime Value (CLV or LTV)
Customer Lifetime Value (CLV or LTV) is a predictive metric that reflects the long-term value of a customer beyond their initial purchase.CLV quantifies the net value generated from a customer throughout their engagement with a product or service, considering revenue, retention, and costs.
What is Customer Lifetime Value?
CLV estimates future value based on historical behavior and assumptions, with a monetary focus. It is measured in revenue or profit terms, not just user counts.CLV data is retention-dependent, meaning it incorporates customer longevity and repeat behavior.
These metrics are used to guide marketing spend, customer acquisition, and retention strategies.
How to use CLV and LTV Metrics
Marketing Budget AllocationDetermine cost-effective customer acquisition targets.
Customer Segmentation
Customer Segmentation
Identify high-value vs. low-value customer groups.
Product Development
Product Development
Prioritize features that enhance retention and monetization.
Financial Forecasting
CLV = Average Purchase Value × Purchase Frequency × Customer Lifespan
Average Purchase Value = Total revenue / Number of purchases
Purchase Frequency = Number of purchases / Number of customers
Customer Lifespan = Average number of years/months a customer remains active
CLV = Average Revenue per User (ARPU) × Customer Lifetime
For subscription businesses with churn data.
CLV = (Average Order Value × Gross Margin) × Purchase Frequency × Customer Lifespan
CLV = Σ ( Pₜ / (1 + r)ᵗ )
Calculates Customer Lifetime Value (CLV) by summing the discounted future profits (Pₜ) over the customer's lifespan, where 'Pₜ' is the profit in period 't', 'r' is the discount rate, and 't' is the time period
Used in financial modeling, fundraising, and strategic valuation work. If you want to use this with AI just prepare the correct variables and the computer will perform the calculation.
Net CLV = CLV - Customer Acquisition Cost (CAC)
Shows true customer profitability after marketing spend.
Regression models, machine learning, forecast future purchases, retention probabilities, and personalized CLV per customer, are ideal data pursuits for enterprises with large datasets and data science teams.
Financial Forecasting
Predict revenue and growth from existing customers.
How is CLV Data Collected?
- Transactional data and purchase history
- User behavior and engagement analytics
- Financial data for costs and margins
- Cohort analysis to measure retention over time
Is there a Formula for CLV and LTV?
There isn't just one formula for Customer Lifetime Value, as different business models, data availability, and goals all inform how CLV is determined.
What Are the Formulas for CLV and LTV?
Simple CLV Formula
For a quick estimate or when you have limited data in retail, eCommerce, SaaS businesses.CLV = Average Purchase Value × Purchase Frequency × Customer Lifespan
Average Purchase Value = Total revenue / Number of purchases
Purchase Frequency = Number of purchases / Number of customers
Customer Lifespan = Average number of years/months a customer remains active
Revenue-Based CLV
Focused on gross revenue, not profit.CLV = Average Revenue per User (ARPU) × Customer Lifetime
For subscription businesses with churn data.
Profit-Based CLV
A profitability-focused view.CLV = (Average Order Value × Gross Margin) × Purchase Frequency × Customer Lifespan
Used by finance teams, and when focused on profitability than rather than revenue.
CLV with Discounted Cash Flow (DCF)
A realistic long-term financial model that considers the time value of money:CLV = Σ ( Pₜ / (1 + r)ᵗ )
Calculates Customer Lifetime Value (CLV) by summing the discounted future profits (Pₜ) over the customer's lifespan, where 'Pₜ' is the profit in period 't', 'r' is the discount rate, and 't' is the time period
Used in financial modeling, fundraising, and strategic valuation work. If you want to use this with AI just prepare the correct variables and the computer will perform the calculation.
CLV with Churn Rate (Subscription Model)
Use this when you have reliable churn data.CLV = ARPU / Churn Rate
Works well when churn rate is relatively stable for SaaS and recurring revenue businesses.CLV with CAC (Customer Acquisition Cost)
For factoring in marketing efficiency.Net CLV = CLV - Customer Acquisition Cost (CAC)
Shows true customer profitability after marketing spend.
Predictive CLV (Advanced / Machine Learning)
Use when a predictive model when you have historical behavioral data.Regression models, machine learning, forecast future purchases, retention probabilities, and personalized CLV per customer, are ideal data pursuits for enterprises with large datasets and data science teams.