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What are Customer Lifetime Value Models? Customer Lifetime Value (CLV) is a measure of the total value a customer provides to a company or business. CLV models include a variety of analytical methods used to estimate the potential value of a customer. Known as simple forward looking, this model predicts customer lifetime value based on customer purchasing behavior. When predicting the customer's future purchases, information such as the customer's purchasing history and behavioral data is used.

In customer segmentation and malaysia whatsapp data RFM (Recency, Frequency, Monetary) analysis, customer lifetime value is estimated by dividing customers into certain segments and based on past shopping analyzes of these segments. In RFM analysis, it evaluates how often customers purchase, how recently they purchased, and how much they spent in total. In the Customer Lifecycle model, the company or business tracks customer interactions from start to finish. This model considers conversion rates and loyalty program participation to understand what types of interactions customers have at different stages.

The Markov chain model is used to periodically predict customers' likelihood of purchasing a product or service. In this model, customers' future purchasing probabilities are made using historical data. In advanced forecasting and machine learning models, complex machine learning algorithms are used to predict customers' future purchasing behavior. These algorithms are often used to develop strategies such as customer segmentation prediction and personalization based on large amounts of data.