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Book part
Publication date: 10 November 2010

Siddharth S. Singh and Dipak C. Jain

Abstract

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Review of Marketing Research
Type: Book
ISBN: 978-0-85724-728-5

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Book part
Publication date: 4 August 2008

M. Bonacchi, M. Ferrari and M. Pellegrini

The aim of this chapter is to develop a performance measurement framework for understanding the relationships among drivers of customer profitability in internet companies.…

Abstract

The aim of this chapter is to develop a performance measurement framework for understanding the relationships among drivers of customer profitability in internet companies.

We recognize an opportunity to improve management control systems for internet companies, where performance measurement systems currently focus on measuring web data, such as number of customers, cost of service, cost of acquisition (CoA), and churn rate. However these indicators, taken separately, do not provide useful information to make decisions.

To fill this gap we developed a framework, which we designate as the Lifetime Value Scorecard, to investigate the relationships between customer data and financial data, providing an early indication as to whether or not the marketing strategies being implemented are successful. We then offer an application of the Lifetime Value Scorecard to the mobile value-added services industry, where content and services are provided to consumer cell phones, mainly using wireless networks.

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Performance Measurement and Management Control: Measuring and Rewarding Performance
Type: Book
ISBN: 978-1-84950-571-0

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Article
Publication date: 1 March 2005

Hans H. Bauer and Maik Hammerschmidt

Synthesis of the customer lifetime value and the shareholder value (SHV) approach in order to develop an integrated, marketing‐based method for corporate valuation.

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6197

Abstract

Purpose

Synthesis of the customer lifetime value and the shareholder value (SHV) approach in order to develop an integrated, marketing‐based method for corporate valuation.

Design/methodology/approach

Discusses the limitations and assumptions of existing methods to estimate customer value components and examines the limitations of the SHV concept. By linking the customer equity (CE) and the SHV approach, a formal model to calculate corporate value is developed. The discounted cash flow method is used for modelling the profit streams.

Findings

Provides formulas for the estimation of both the individual lifetime value of a customer and CE. Provides a comprehensive model to estimate corporate value based on customer‐related cash flows and traditional financial metrics. Introduces typical cases, in which the use of a customer‐based valuation seems beneficial. Illustrates how our approach can be applied by using a simple case study on M&A in the telecommunication industry. Gives suggestions on how to obtain the necessary data, partially even from publicly available sources.

Research limitations/implications

Advancement of the quantitative techniques for modelling the customer value components would allow for relaxing some restrictive assumptions. The explicit modelling of the future growth of the customer base (the acquisition rate) would increase the applicability of the model. Additionally, taking into account heterogeneity within the customer cohorts is a task for future research. Finally, our model needs to be applied more extensively using real data for the input variables.

Practical implications

A CE‐based valuation approach can guide marketing investments and helps to avoid misallocation of resources. Based on an example in the field of M&A, we demonstrate the usefulness of the approach for obtaining a realistic indicator of firm value. It helps to assess whether an acquisition is economically sensible. We provide evidence for the superiority of a customer‐based approach over traditional financial methods.

Originality/value

While the traditional SHV method considers cash flows at a highly aggregated level, our approach employs disaggregated cash flows on the level of individual customers. Thereby we do incorporate the lifetime values of future customers by considering different cohorts. We do capture customer defection by incorporating retention rates. Our model enables a more detailed and valid estimation of corporate value by accounting for the single customer activities that drive marketing actions. This enables a better forecasting of the free cash flow. Incorporating customer‐related drivers into financial valuation models makes easier to assess the return on marketing investments.

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Management Decision, vol. 43 no. 3
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 27 February 2007

Ben Shaw‐Ching Liu, Nicholas C. Petruzzi and D. Sudharshan

The purpose of this paper is to apply customer lifetime value models to assess the overall value of the service encounter and to establish implications that such an…

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4987

Abstract

Purpose

The purpose of this paper is to apply customer lifetime value models to assess the overall value of the service encounter and to establish implications that such an assessment has for managing customer relationships under a fixed‐size salesforce.

Design/methodology/approach

Using a specific relationship between customer servicing activities and the buying rhythms of customers, an analytical model for assessing the overall value of a service encounter is developed.

Findings

A stochastic parameter is identified, characterizing the level of quality to compute the long‐term value of a given customer and stochastic ordering properties to determine the relative value of different customers.

Research limitations/implications

The implications discussed are analytical to help service managers shaping their thought process in decision making. Future research can empirically test the model proposed.

Practical implications

The theorem specifies the optimal solutions to determine: how much capacity should be committed to a given customer; and how to choose a customer in the first place. These are important and useful tools for managers in making their managerial decisions in service marketing.

Originality/value

A general model of resource allocation is provided, under which those seminal models such as CALLPLAN, DETAILER are special cases. This is particularly valuable as key account management has become more important in globally operated businesses.

Details

Journal of Services Marketing, vol. 21 no. 1
Type: Research Article
ISSN: 0887-6045

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Article
Publication date: 1 May 2005

Lynette J. Ryals and Simon Knox

The calculations which underlie efforts to balance marketing spending on customer acquisition and customer retention are usually based on either single‐period customer

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7254

Abstract

Purpose

The calculations which underlie efforts to balance marketing spending on customer acquisition and customer retention are usually based on either single‐period customer profitability or forecasts of customer lifetime value (CLTV). This paper argues instead for risk‐adjusted CLTV, which is termed the economic value (EV) of a customer, as the means for marketing to assess both customer profitability and shareholder value gains.

Design/methodology/approach

Reports on the empirical measurement of EV of customers through a collaborative case study analysis of business‐to‐business relationships in the financial service industry.

Findings

One direct consequence of measuring this risk and the EV of key account customers was a customer portfolio review which led to changes in their relationship marketing strategies and improvements in shareholder value for the firm.

Practical implications

Selective customer retention through lifetime value analysis and a risk‐adjustment process may be the means for developing relationship marketing strategies.

Originality/value

This paper contributes to the field by extending the discussion on customer risk and demonstrating a method that managers can readily adopt to evaluate the risk of their customers.

Details

European Journal of Marketing, vol. 39 no. 5/6
Type: Research Article
ISSN: 0309-0566

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Article
Publication date: 1 February 1997

Duncan McDougall, Gordon Wyner and David Vazdauskas

Customers differ widely in the long‐term value they represent to a company, and the “best” customers are often many times more valuable than the average ones. Cites four…

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2045

Abstract

Customers differ widely in the long‐term value they represent to a company, and the “best” customers are often many times more valuable than the average ones. Cites four customer value components: acquisition cost, revenue stream, cost stream and length of relationship. Argues that by understanding and managing lifetime customer value, a company not only allocates resources to its customers more effectively, but also becomes better able to focus on developing long‐term customer relationships. Examines ways to calculate lifetime customer value and use it as the basis for strategy development.

Details

Managing Service Quality: An International Journal, vol. 7 no. 1
Type: Research Article
ISSN: 0960-4529

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Article
Publication date: 8 April 2014

Yeliz Ekinci, Nimet Uray and Füsun Ülengin

The aim of this study is to develop an applicable and detailed model for customer lifetime value (CLV) and to highlight the most important indicators relevant for a…

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2906

Abstract

Purpose

The aim of this study is to develop an applicable and detailed model for customer lifetime value (CLV) and to highlight the most important indicators relevant for a specific industry – namely the banking sector.

Design/methodology/approach

This study compares the results of the least square estimation (LSE) and artificial neural network (ANN) in order to select the best performing forecasting tool to predict the potential CLV. The performances of the models are compared by the hit ratio, which is calculated by grouping the customers as “top 20 per cent” and “bottom 80 per cent” profitable.

Findings

Due to its higher performance; LSE based linear regression model is selected. The results are found to be highly competitive compared with the previous studies. This study shows that, beside the indicators mostly used in the literature in measuring CLV, two additional groups, namely monetary value and risk of certain bank services, as well as product/service ownership-related indicators, are also significant factors.

Practical implications

Organisations in the banking sector have to persuade their customers to use certain routine risk-bearing transaction-based services. In addition, the product development strategy has a crucial role to increase the CLV of customers because some of the product-related variables directly increase the value of customers.

Originality/value

The proposed model predicts potential value of current customers rather than measuring current value considered in the majority of previous studies. It eliminates the limitations and drawbacks of the majority of models in the literature through simple and industry-specific method which is based on easily measurable and objective indicators.

Details

European Journal of Marketing, vol. 48 no. 3/4
Type: Research Article
ISSN: 0309-0566

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Book part
Publication date: 1 February 2007

Ruth N. Bolton and Crina O. Tarasi

Abstract

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Review of Marketing Research
Type: Book
ISBN: 978-0-7656-1306-6

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Article
Publication date: 2 February 2021

Marco De Marco, Paolo Fantozzi, Claudio Fornaro, Luigi Laura and Antonio Miloso

The purpose of this study is to show that the use of CAM (cognitive analytics management) methodology is a valid tool to describe new technology implementations for businesses.

Abstract

Purpose

The purpose of this study is to show that the use of CAM (cognitive analytics management) methodology is a valid tool to describe new technology implementations for businesses.

Design/methodology/approach

Starting from a dataset of recipes, we were able to describe consumers through a variant of the RFM (recency, frequency and monetary value) model. It has been possible to categorize the customers into clusters and to measure their profitability thanks to the customer lifetime value (CLV).

Findings

After comparing two machine learning algorithms, we found out that self-organizing map better classifies the customer base of the retailer. The algorithm was able to extract three clusters that were described as personas using the values of the customer lifetime value and the scores of the variant of the RFM model.

Research limitations/implications

The results of this methodology are strictly applicable to the retailer which provided the data.

Practical implications

Even though, this methodology can produce useful information for designing promotional strategies and improving the relationship between company and customers.

Social implications

Customer segmentation is an essential part of the marketing process. Improving further segmentation methods allow even small and medium companies to effectively target customers to better deliver to society the value they offer.

Originality/value

This paper shows the application of CAM methodology to guide the implementation and the adoption of a new customer segmentation algorithm based on the CLV.

Details

Journal of Enterprise Information Management, vol. 34 no. 2
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 1 April 2003

Sabrina Helm

Word‐of‐mouth is a rarely quantified phenomenon, in spite of its importance for service firms. Therefore, referrals remain a neglected determinant of customer lifetime

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4359

Abstract

Word‐of‐mouth is a rarely quantified phenomenon, in spite of its importance for service firms. Therefore, referrals remain a neglected determinant of customer lifetime valuation, although some authors claim them to be the astronomical part of customer equity. The paper discusses different approaches to the calculation of positive word‐of‐mouth, leading to a monetary referral value of a company’s customers.

Details

Managing Service Quality: An International Journal, vol. 13 no. 2
Type: Research Article
ISSN: 0960-4529

Keywords

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