With regards to customer identification, CLV can be used to identify the most and least profitable customers and direct marketing efforts at the most valuable ones by classifying customers into high, medium, and low-value segments. The classification provides customer relationship managers with substantial insight for making marketing decisions regarding the allocation of scarce resources towards selling efforts and service levels.

 Calculating CLV helps the firm to know how much it can invest in retaining the customer so as to achieve a positive ROI. This is possible by knowing the cumulated cash flow of a customer over his or her entire lifetime with the company or the LTV of the customers.

 Once the firm has calculated the CLV of its customers, the framework is also the basis for selecting customers, selling the next best product/service to the customers, and deciding on the customer‐specific communication strategies.

CLV can also be used to help companies test alternative marketing strategies to gauge the profit potential of the alternatives versus previously implemented campaigns. The testing of these marketing strategies can include for example, the measurement of loyalty programs to determine whether they are worth implementing based on the value added to CLV, with and without the programs.

Forecasting for customer defection and customer satisfaction levels can be identified based on CLV that can help firms determine which customers are worth investing more resources on, and what strategies should be used to interact with them. Efforts to increase future retention and win-back strategies can also be examined to curtail customer defection and improve satisfaction.

 CLV can also help companies define their objectives and assess their market position and the value of their existing customer bases. The knowledge gained from this assessment can aid companies in determining the overall company value which can be used during mergers, purchases, and sales.

 CLV enables the decision makers to think in terms of long-term relationships instead of discrete transactions.

The CLV metric acknowledges that customers are likely to alter their behavior due to factors such as changes in competition and/or customer lifestyle. Accounting for these changes allows firms to execute product/service differentiation strategies according to a customer’s expected value.

 With advancements in technology, firms are now able to gather large amounts of customer purchase behavior. The increased data availability has made it possible for firms to conduct sophisticated analyses. Further, the simpler customer value metrics pales in comparison to CLV, in terms of determining individual customer-level profitability. In this light, CLV overcomes the inherent drawbacks of the traditional metrics and provides a reliable estimate of future customer value.

Customers now know that companies treat high-value buyers differently from low-value buyers. However, companies should have a forward-looking approach for the differentiation to be successful in the long run. Today, any firm is faced with the challenge of developing an optimal blend of differential levels of treatments in such a fashion that the profits earned by the firm are maximized over each customer’s lifetime. In this regard, CLV presents a more accurate roadmap for firms to design their offerings.