How to Use SQL to Calculate Customer Lifetime Value (LTV)

Understanding your customers' worth over time is crucial for data-driven decision-making. Customer Lifetime Value (LTV) estimates the total revenue a business can expect from a single customer account throughout their relationship. In this post, we’ll break down how to calculate LTV using SQL, provide easy-to-understand examples, and share how AI2sql can simplify the process for analysts, marketers, and anyone looking to turn data into smart business insights.

What is Customer Lifetime Value (LTV)?

Customer Lifetime Value (LTV) is a metric that allows businesses to predict the total value they will receive from a customer during the entire span of their relationship. Knowing LTV helps you:

• Determine customer acquisition costs that make sense

• Identify high-value customer segments

• Allocate resources efficiently

Why Calculate LTV Using SQL?

SQL is widely used for analyzing large datasets found in business databases. Calculating LTV with SQL helps you:

• Automate and scale lifetime value analysis

• Ensure consistency when dealing with transactional data

• Integrate LTV with other customer analytics

Step-by-Step Guide: Calculate LTV with SQL

The most basic formula for LTV is:

LTV = Average Purchase Value × Purchase Frequency × Customer Lifespan

Let’s see how to assemble this using SQL, starting from your typical e-commerce database with orders and customers tables.

1. Calculate Average Purchase Value

SELECT customer_id, AVG(order_total) AS avg_purchase_value
FROM orders
GROUP BY customer_id;

2. Calculate Purchase Frequency

SELECT customer_id, COUNT(order_id) / COUNT(DISTINCT DATE(order_date)) AS purchase_frequency
FROM orders
GROUP BY customer_id;

3. Estimate Customer Lifespan

SELECT customer_id, DATEDIFF(MAX(order_date), MIN(order_date))/365 AS customer_lifespan_years
FROM orders
GROUP BY customer_id;

4. Combine the Results for LTV

SELECT 
  o.customer_id, 
  AVG(o.order_total) * 
  (COUNT(o.order_id) / COUNT(DISTINCT DATE(o.order_date))) * 
  (DATEDIFF(MAX(o.order_date), MIN(o.order_date))/365) AS lifetime_value
FROM orders o
GROUP BY o.customer_id;

Speed Up SQL Analytics with AI2sql

Manual SQL queries can be error-prone and time-consuming, especially for those new to databases. AI2sql automates query generation from plain English. For example, you could type:

"Calculate the customer lifetime value for each customer based on all orders in the last five years."

And let AI2sql generate an optimized SQL query, saving you time and ensuring accuracy. This lets teams focus on analyzing insights, not debugging code.

Best Practices for Accurate LTV Analysis

• Clean your data before running calculations to avoid skewed results

• Segment customers by cohort, channel, or region for deeper insights

• Update LTV regularly as customer behavior changes over time

Conclusion

SQL is a powerful ally in uncovering your true Customer Lifetime Value. By leveraging SQL queries—or streamlining the process with AI2sql—you can better understand your customers and make smarter business decisions. Want to simplify your analytics even more? Try AI2sql free today and see actionable insights faster.