Customer Lifetime Value (CLV) is a crucial metric for businesses aiming to understand the long-term value derived from their customer relationships. It quantifies the total revenue a customer generates for a business throughout their entire engagement, considering not only the frequency of purchases but also the monetary value associated with each transaction.

In this article, we'll explore the concept of CLV using data from an online retail dataset and demonstrate how to predict the 3-month CLV using linear regression.

CLV goes beyond evaluating individual purchases; it encompasses the cumulative value a customer brings to a business over their entire interaction history. By analyzing customer behavior and purchase patterns, businesses can tailor their marketing strategies, optimize customer experiences, and prioritize resources to maximize the value derived from each customer.

We'll start by examining the Online Retail dataset, which contains information about customer transactions, including invoice numbers, product details, quantities, prices, and customer IDs.

We preprocess the dataset by removing negative quantities and filtering out entries with blank customer IDs. Then, we analyze the data range to determine the period under consideration.

We create summary statistics at three-month intervals for each customer, including total sales, average spending, and purchase frequency. These features serve as predictors for estimating the CLV.

Using linear regression, we build a predictive model to estimate the 3-month CLV based on the engineered features. We split the data into training and testing sets and assess the model's performance using metrics such as R-squared and median absolute error.

Our analysis reveals insights into customer spending behaviors and allows businesses to forecast the potential revenue generated by individual customers over a three-month period. By understanding CLV, businesses can make informed decisions regarding customer acquisition, retention strategies, and resource allocation.

Customer Lifetime Value is a powerful metric that enables businesses to quantify the long-term impact of their customer relationships. By leveraging data analytics and predictive modeling techniques, businesses can optimize marketing efforts, enhance customer experiences, and drive sustainable growth.

By integrating CLV into their strategic decision-making processes, businesses can foster enduring relationships with their customers and unlock new avenues for profitability and success.