Customer Value Management, CVM

For a long time, the company has not been able to effectively evaluate the future value of customers. It is unable to effectively invest resources in customers, which will result in the company's resources waste but not increasing the company's revenue. If we can understand the customer loss and understand the future potential purchasing of customers, we will be able to effectively use different customer management strategies for different customers, so that customers with different characteristics can contribute the most to the company.

The Customer Value Management system is based on information such as customer revenue, cost, and profit calculated by Activity Value Management (AVM). After integrating the internal customer information, it can automate input to the Customer Value Management System. Using big data analyze to the long-term data of the company, through the artificial intelligence algorithm, calculate the "customer transaction probability", so that the company can take care of the future transaction status of the customer; and then calculate the "customer life time", so that the company can understand customer survival time. In the end, we can predict the "customer life time value", accurately grasp the customer's future profit, and effectively assist the company with customer grouping.

Through this system, we can predict the "customer transaction probability", "customer life time ", "customer life time value", and automatically generate customer value management decision report, which can help companies understand the future trading situation of customers and future short-term and long-term profits. Then, it can effectively group customers, so that companies can develop different management policies and invest limited resources in the most valuable customers. The system can generate diversified customer information that can be applied to customer management decisions, customer grading, customer survival time, customer profit.