Search results

1 – 10 of 234
To view the access options for this content please click here
Book part
Publication date: 10 November 2010

Siddharth S. Singh and Dipak C. Jain

Abstract

Details

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

To view the access options for this content please click here
Article
Publication date: 5 March 2018

Cheng-Hsiung Weng and Tony Cheng-Kui Huang

Customer lifetime value (CLV) scoring is highly effective when applied to marketing databases. Some researchers have extended the traditional association rule problem by…

Abstract

Purpose

Customer lifetime value (CLV) scoring is highly effective when applied to marketing databases. Some researchers have extended the traditional association rule problem by associating a weight with each item in a transaction. However, studies of association rule mining have considered the relative benefits or significance of “items” rather than “transactions” belonging to different customers. Because not all customers are financially attractive to firms, it is crucial that their profitability be determined and that transactions be weighted according to CLV. This study aims to discover association rules from the CLV perspective.

Design/methodology/approach

This study extended the traditional association rule problem by allowing the association of CLV weight with a transaction to reflect the interest and intensity of customer values. Furthermore, the authors proposed a new algorithm, frequent itemsets of CLV weight (FICLV), to discover frequent itemsets from CLV-weighted transactions.

Findings

Experimental results from the survey data indicate that the proposed FICLV algorithm can discover valuable frequent itemsets. Moreover, the frequent itemsets identified using the FICLV algorithm outperform those discovered through conventional approaches for predicting customer purchasing itemsets in the coming period.

Originality/value

This study is the first to introduce the optimum approach for discovering frequent itemsets from transactions through considering CLV.

Details

Kybernetes, vol. 47 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

To view the access options for this content please click here
Article
Publication date: 7 May 2019

Bahman Hajipour and Molud Esfahani

The purpose of this paper is to evaluate the relationship between strategy and customer lifetime value (CLV). A new model was proposed for defining customers’ values based…

Abstract

Purpose

The purpose of this paper is to evaluate the relationship between strategy and customer lifetime value (CLV). A new model was proposed for defining customers’ values based on the RFM model and segmenting bank customers using the K-means algorithm. In addition, the authors combined a new category with the delta model in order to analyze the behavior of each cluster.

Design/methodology/approach

This case study was based on an applied method following its objectives and a descriptive-analytic method in terms of data collection. In this research, the AHP, data mining and K-means clustering methods, as well as the discriminant analysis were applied for computing the weights of the indices, examining the relationship between the identified variables, clustering the records and ensuring the clustering accuracy based on the RFM model, respectively.

Findings

The paper confirmed the relationship between the strategies and CLV. For a cluster whose strategy was the best product, customers had a minimal CLV. For a cluster whose strategy was based on total customer solutions, customers had a median CLV. For a cluster whose strategy was a lock-in system, customers had a maximal CLV. The results suggested that the delta model with these three strategies could act as the CLV developers in two stages: conversion of transient customers to attached customers and conversion of attached customers to locked-in customers.

Research limitations/implications

One of the limitations of this study was the lack of access to all the bank accounts and assessment of only the strategy type, while highlighting the exact association between every component of the strategies (e.g. structure, environment, etc.) and CLV as a dependent variable deemed to be of a great necessity. Hence, it is recommended that several studies on the relationships presented in this paper be performed to provide further insights into and guidelines on this issue in the future.

Practical implications

This study emphasized the relevance of strategy and CLV. Managers should differently treat customers in distinct CLV and loyalty levels. In other words, managers must segment their customers based on CLV and apply appropriate strategies for each segment.

Originality/value

This research tried to fulfill an identified need to study how strategy can be effect CLV through the application of the delta model with three strategic options.

Details

Marketing Intelligence & Planning, vol. 37 no. 3
Type: Research Article
ISSN: 0263-4503

Keywords

To view the access options for this content please click here
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…

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

Keywords

To view the access options for this content please click here
Article
Publication date: 6 July 2015

Arash Shahin and Somayeh Mohammadi Shahiverdi

In previous studies, historical information of customer had been used for determining customer lifetime value (CLV). The purpose of this paper is to modify CLV estimation…

Abstract

Purpose

In previous studies, historical information of customer had been used for determining customer lifetime value (CLV). The purpose of this paper is to modify CLV estimation to be applied before producing a new product.

Design/methodology/approach

In this study, the CLV estimation has been modified using Kano satisfaction coefficient. The Kano satisfaction coefficient has been assumed as loyalty indicator in estimating CLV and related equations have been developed for allocating Kano requirements to various phases of product life cycle. The proposed approach has been examined in two new product options of the automobile industry. Finally, by using customers’ purchase records during three years, CLV has been calculated for both product development options.

Findings

Findings indicate that CLV of the first development option is equal to 407 million and 500,000 toumans and of the second option is equal to 392 million toumans, this difference is related to different requirements of the Kano model, and as a result, to different satisfaction coefficients. Therefore, the first option has been suggested for investing in developing new product.

Research limitations/implications

Application of the proposed approach is limited to short time periods. The findings are limited to the automobile industry.

Originality/value

The modified approach of estimating CLV can be applied for prospective new product development in addition to traditional approaches in which, only the historical data of sold products are used. In addition, using Kano satisfaction coefficient in estimation of CLV in short periods, seems an appropriate approach for competitive industries that focus on dynamic needs of customers.

Details

Benchmarking: An International Journal, vol. 22 no. 5
Type: Research Article
ISSN: 1463-5771

Keywords

To view the access options for this content please click here
Article
Publication date: 18 September 2009

Malcolm Smith and Chen Chang

Much empirical evidence is in conflict with the expectations of the service‐profit chain which suggests that increases in customer satisfaction will increase customer…

Abstract

Purpose

Much empirical evidence is in conflict with the expectations of the service‐profit chain which suggests that increases in customer satisfaction will increase customer loyalty and earn additional profits from customers. Management focus on the achievement of customer satisfaction and customer loyalty, and associated investment, might, therefore, be misguided, if they believe that the available empirical evidence supports a link between these variables and firm performance. The purpose of this paper is to help firms understand the value of their intangible assets – most notably the important role played by customers in increasing a firm's value.

Design/methodology/approach

On the basis of survey‐based research carried out in the Taiwanese credit card market, this paper generates a structural equation model facilitating the measurement and evaluation of the relative efficiencies of customer‐related strategies.

Findings

The findings help managers to understand the relationship between customer‐related strategies (customer acquisition, retention, and add‐on selling) and their impact on customer measures and ultimately firm performance. Customer lifetime value is shown to be the most important indicator of financial performance and the firm's shareholder value; the customer loyalty measure is shown to have no impact on shareholder value, and to be negatively related to the implementation of an acquisition strategy.

Research limitations/implications

The paper is conducted within the Taiwanese credit card market, and the findings may not be generalisable to other locations or to other markets.

Practical implications

These empirical findings suggest that marketing strategy has a central role in the formulation of financial policy, since such strategies can be shown to have an impact on the financial value of the business.

Originality/value

The paper provides further evidence linking customers with firm value, which will be important for management decision making and resource use.

Details

Asian Review of Accounting, vol. 17 no. 3
Type: Research Article
ISSN: 1321-7348

Keywords

To view the access options for this content please click here
Article
Publication date: 13 March 2017

Antonia Estrella-Ramón, Manuel Sánchez-Pérez, Gilbert Swinnen and Koen VanHoof

The purpose of this paper is to provide a customer lifetime value (CLV) model to carefully assess and classify banking customers using individual measures and covering…

Abstract

Purpose

The purpose of this paper is to provide a customer lifetime value (CLV) model to carefully assess and classify banking customers using individual measures and covering customers’ relationships with a portfolio of products of the company.

Design/methodology/approach

The proposed model comprises two sub-models: (sub-model 1) modelling and prediction of CLV in a multiproduct context using Hierarchical Bayesian models as input to (sub-model 2) a value-based segmentation specially designed to manage customers and products using the latent class regression. The model is tested using real transaction data of 1,357 customers of a bank.

Findings

This research demonstrates which drivers of customer value better predict the contribution margin and product usage for each of the products considered in order to get the CLV measure. Using this measure, the model implements a value-based segmentation, which helps banks to facilitate the process of customer management.

Originality/value

Previous CLV models are mostly conceptual, generalisation is one of their main concerns, are usually focussed on single product categories using aggregated customer data, and they are not design with a special emphasis on their application as support for managerial decisions. In response to these drawbacks, the proposed model will enable decision makers to improve the understanding of the value of each customer and their behaviour towards different financial products.

To view the access options for this content please click here
Book part
Publication date: 13 November 2017

Robert Kozielski, Michał Dziekoński, Jacek Pogorzelski and Grzegorz Urbanek

The term ‘strategy’ is one of the most frequently used terms in business, and its application in marketing is particularly common. Company strategy, market strategy…

Abstract

The term ‘strategy’ is one of the most frequently used terms in business, and its application in marketing is particularly common. Company strategy, market strategy, marketing strategy, sales strategy, promotion strategy, distribution strategy, low pricing strategy – it would take a long time to list all of them. Although this term is so commonly in use, its definition is not as straightforward and it can be interpreted in different ways. In comparison with tactical decisions, strategy is much more significant for an organisation as it brings long-lasting consequences. It is implemented by higher level managers on a regular basis, and it is based on external, often subjective information, so decisions – especially at the time they are made – are difficult to evaluate.

Taking into consideration the fact that strategy refers to a long-term rather than a short-term period, strategic decisions serve as the basis for undertaking operational activities. However, marketing refers to the market and the competition. It is possible to claim that marketing strategy is trying to find an answer to the question to which path an organisation should follow in order to achieve its goals and objectives. If, for example, a company has a goal to generate a profit of PLN 1 million by selling 100,000 pieces of a product, the market strategy should answer at least the following two questions:

  1. Who will be our target group, for example, who will purchase the 100,000 pieces of the product?

  2. Why is it us from whom a potential buyer should purchase the product?

Who will be our target group, for example, who will purchase the 100,000 pieces of the product?

Why is it us from whom a potential buyer should purchase the product?

The target market will be defined if a reply to the first question is provided. The second question identifies the foundations of competitive advantage. These two issues, that is, target market and competitive advantage are the strategic marketing issues. You cannot change your target group unexpectedly while competitive advantage is the basis for changing decisions regarding prices, promotions and sales.

This chapter describes the measures of marketing activities which refer to strategic aspects and testify a company’s market position – the measures of the performance of target groups and competitive advantage. Readers’ attention should be also focused on the indices that are less popular in Poland and, therefore, may be underestimated. It seems that some of them, for example, the index of marketing resources allocation and the marketing risk index, provide a lot of valuable information and, at the same time, make it possible to show the value of marketing investments. Their wider use in the near future is only a matter of time.

To view the access options for this content please click here
Article
Publication date: 11 November 2019

Xiaolei Yu and Chunlin Yuan

The purpose of this paper is to investigate factors driving consumers’ social media brand experience and its effect on customer equity and customer lifetime value (CLV). A…

Abstract

Purpose

The purpose of this paper is to investigate factors driving consumers’ social media brand experience and its effect on customer equity and customer lifetime value (CLV). A conceptual model is proposed including the variables of product attributes, brand experience, brand attachment, brand trust, customer equity and CLV.

Design/methodology/approach

The proposed research model is analyzed using a survey of 708 South Korean and Chinese consumers.

Findings

The results indicate that utilitarian and hedonic values influence brand experience, and that brand experience directly influences brand attachment, brand trust and customer equity drivers. There is a positive relationship between brand attachment and trust. As a customer equity driver, brand equity has a positive effect on CLV.

Originality/value

This study sheds light on how brand experience in social media can improve customer equity. It contributes to the theory of brand experience and customer equity as well as smartphone product marketing strategies. From a managerial perspective, guidelines are provided for firms to implement value communication activities using social media, and to maintain and increase their CLV.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 31 no. 5
Type: Research Article
ISSN: 1355-5855

Keywords

To view the access options for this content please click here
Article
Publication date: 6 June 2016

Fariba Safari, Narges Safari and Gholam Ali Montazer

One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime…

Abstract

Purpose

One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime value (CLV) measured by three purchase variables: “Recency,” “Frequency” and “Monetary.” However, due to the ambiguity of these variables, using deterministic approach is not appropriate. For tackling this matter, the purpose of this paper is to propose a new method of customer segmentation and ranking by combining fuzzy clustering (as a segmentation method) and fuzzy AHP (as a ranking method).

Design/methodology/approach

First, customers are classified based on purchase variables using fuzzy c-means clustering algorithm. Second, the variables are weighed applying an optimized version of AHP method. Considering the derived weights and customer groups, this paper follows to ranks segments based on CLV. The developed methodology has been implemented for a large IT company in Iran.

Findings

The results show a tremendous capability to the company to evaluate his customers by dividing them into nine ranked segments. The validity of clusters has been submitted.

Research limitations/implications

For researchers, this study provides a useful literature by combining FCM and an optimized version of fuzzy AHP in order to cover the limitations of previous methodologies. For organizations, this study clarifies the procedure of customer segmentation by which they can improve their marketing activities.

Practical implications

Managers can consider the proposed CLV calculation methodology for selling the next best services/products to the group of customers that are more valuable, by calculating the entire lifetime value of the customers.

Originality/value

This study contributes to the process of customer segmentation based on CLV, proposing a new method which covers the limitations of previous customer segmentation methods.

Details

Marketing Intelligence & Planning, vol. 34 no. 4
Type: Research Article
ISSN: 0263-4503

Keywords

1 – 10 of 234