Advanced Approaches to Estimating and Utilizing Customer Lifetime Value in Business Strategy

Ankit Bansal

Abstract: Customer Lifetime Value (CLV) holds importance in the field of analytics as it gives an assessment of the total revenue a company expects to generate from a customer, over their interaction period with the business entity. This metric goes beyond measurements by providing a perspective on customer profitability which aids in making more informed business decisions. Precise estimation of CLV depends on accurate data collection and advanced analytical methods such as machine learning and predictive modeling. By leveraging insights, from CLV analysis companies can enhance their marketing strategies boost customer loyalty and foster growth in the run. This article delves into the ways of determining LTVs value. How it is used in sectors to influence data driven choices; highlighting its essential role, in improving business outcomes and managing customer relationships effectively.

Keywords: Customer Lifetime Value, CLTV, CLV, LTV, Data Analytics, Predictive Modeling, Customer Segmentation, Business Strategy, Retention Strategies, design marketing offers, Profitability Analysis, customer acquisition