Predicting customer potential value an application in the insurance industry

نویسندگان

  • Peter C. Verhoef
  • Bas Donkers
چکیده

For effective Customer Relationship Management (CRM), it is essential to have information on the potential value of customers. Based on the interplay between potential value and realized value, managers can devise customer specific strategies. In this article we introduce a model for predicting the potential value of a current customer. Furthermore, we discuss and apply different modeling strategies for predicting this potential value. Key-words: Customer Relationship Management, Customer Potential, Marketing Models, Insurance Industry * Corresponding Author: Peter C. Verhoef, Erasmus University Rotterdam, Department of Marketing and Organization, Office H15-12, P.O. Box 1738, NL-3000 DR Rotterdam, The Netherlands, Phone +31 10 408 2809, Fax +31 10 408 9169, Email:[email protected], http://www.few.eur.nl/few/people/verhoef † Bas Donkers, Erasmus University Rotterdam, Department of Marketing and Organization, Office H15-12, P.O. Box 1738, NL-3000 DR Rotterdam, The Netherlands, Phone +31 10 408 2411, Fax +31 10 408 9169, E-mail: [email protected]

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Predicting Customer Churn Using CLV in Insurance Industry

Today, increased level of customer awareness caused themto access to the other suppliers easily and they can get their servicesfrom the competitors with similar or even better quality and same price.Therefore, focusing on customers and preventing them to leave, has beenthe most important strategy for any company. Researches have shownthat retaining former customers is cheaper than attracting ne...

متن کامل

Measuring and Predicting Customer Lifetime Value in Customer Loyalty Analysis: A Knowledge Management Perspective (A Case Study on an e-Retailer)

Modern business organizations have appreciated the significance of having competitive advantage through the delivery of continuous improvement towards the customers, and being knowledge-oriented. Indisputably, Knowledge Management (KM) plays a key role in the success of Customer Relationship Management (CRM). In this regard, Customer Knowledge Management (CKM) is a newly developed concept that ...

متن کامل

Identify and Evaluate the Components of Cause-Related Marketing in the Insurance Industry

Background: Benevolent marketing is one of the new and ethical strategies of marketing businesses to create special value for the customer, according to which a direct relationship between selling the product and helping the business to a charity or charity is defined and promoted to fulfill responsibility. Becomes corporate social. The main purpose of this article is to identify and rank benev...

متن کامل

Customer Retention Based on the Number of Purchase: A Data Mining Approach

Purpose: this study wants to find any relationship between the numbers of purchase and the income the customer brings to the company. The attempt is to find those customers who buy more than one life insurance policy and represent the signs of good payments at the same time by the help of data mining tools. Design/ methodology/ approach: the approach of this research is to use data mining tools...

متن کامل

Artificial Neural Network Model for Predicting Insurance Insolvency

In addition to its primary role of providing financial protection for other industries the insurance industry also serves as a medium for fund mobilization. In spite of the harsh economic environment in Nigeria, the insurance industry has been crucial to the consummation of business plans and wealth creation.  However, the continued downturn experienced by many countries, in the last decade, se...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Decision Support Systems

دوره 32  شماره 

صفحات  -

تاریخ انتشار 2001