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Article
Publication date: 22 August 2008

Lyndon Simkin

The creation of a target market strategy is integral to developing an effective business strategy. The concept of market segmentation is often cited as pivotal to…

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14756

Abstract

Purpose

The creation of a target market strategy is integral to developing an effective business strategy. The concept of market segmentation is often cited as pivotal to establishing a target market strategy, yet all too often business‐to‐business marketers utilise little more than trade sectors or product groups as the basis for their groupings of customers, rather than customers' characteristics and buying behaviour. The purpose of this paper is to offer a solution for managers, focusing on customer purchasing behaviour, which evolves from the organisation's existing criteria used for grouping its customers.

Design/methodology/approach

One of the underlying reasons managers fail to embrace best practice market segmentation is their inability to manage the transition from how target markets in an organisation are currently described to how they might look when based on customer characteristics, needs, purchasing behaviour and decision‐making. Any attempt to develop market segments should reflect the inability of organisations to ignore their existing customer group classification schemes and associated customer‐facing operational practices, such as distribution channels and sales force allocations.

Findings

A straightforward process has been derived and applied, enabling organisations to practice market segmentation in an evolutionary manner, facilitating the transition to customer‐led target market segments. This process also ensures commitment from the managers responsible for implementing the eventual segmentation scheme. This paper outlines the six stages of this process and presents an illustrative example from the agrichemicals sector, supported by other cases.

Research implications

The process presented in this paper for embarking on market segmentation focuses on customer purchasing behaviour rather than business sectors or product group classifications ‐ which is true to the concept of market segmentation ‐ but in a manner that participating managers find non‐threatening. The resulting market segments have their basis in the organisation's existing customer classification schemes and are an iteration to which most managers readily buy‐in.

Originality/value

Despite the size of the market segmentation literature, very few papers offer step‐by‐step guidance for developing customer‐focused market segments in business‐to‐business marketing. The analytical tool for assessing customer purchasing deployed in this paper originally was created to assist in marketing planning programmes, but has since proved its worth as the foundation for creating segmentation schemes in business marketing, as described in this paper.

Details

Journal of Business & Industrial Marketing, vol. 23 no. 7
Type: Research Article
ISSN: 0885-8624

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Article
Publication date: 16 October 2017

Gökcay Balci and Ismail Bilge Cetin

Container shipping is a standardized business-to-business service market where carriers need to stay customer focused to survive. Market segmentation is an ideal solution…

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2439

Abstract

Purpose

Container shipping is a standardized business-to-business service market where carriers need to stay customer focused to survive. Market segmentation is an ideal solution to develop customized marketing programs for each segment, but container lines need personalized marketing programs for each customer. Hence, the purpose of this study is to develop a segmentation framework that can help container lines to profile each customer more efficiently considering their needs, strategic importance and demographics.

Design/methodology/approach

This study has adopted an exploratory approach. Semi-structured interviews were conducted with managers of container lines.

Findings

Segmentation bases are the type of customer, container volume, loyalty, seasonality, decision maker, the industry of shipper, cargo characteristics, container type, destination region and export/import. Market segmentation in container shipping can be helpful in developing effective customized marketing offering, including effective price discrimination and customized marketing communications.

Practical implications

A port-specific segmentation approach was adopted and a flexible segmentation framework was proposed for container lines to adapt in different hinterlands.

Originality/value

Unlike the literature, this study suggests market segmentation can be very helpful in customized marketing in business-to-business services like container shipping industry. This study also suggests port-specific market segmentation for container lines instead of route-specific.

Details

Management Research Review, vol. 40 no. 10
Type: Research Article
ISSN: 2040-8269

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Article
Publication date: 13 July 2015

Hülya Güçdemir and Hasan Selim

– The purpose of this paper is to develop a systematic approach for business customer segmentation.

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2938

Abstract

Purpose

The purpose of this paper is to develop a systematic approach for business customer segmentation.

Design/methodology/approach

This study proposes an approach for business customer segmentation that integrates clustering and multi-criteria decision making (MCDM). First, proper segmentation variables are identified and then customers are grouped by using hierarchical and partitional clustering algorithms. The approach extended the recency-frequency-monetary (RFM) model by proposing five novel segmentation variables for business markets. To confirm the viability of the proposed approach, a real-world application is presented. Three agglomerative hierarchical clustering algorithms namely “Ward’s method,” “single linkage” and “complete linkage,” and a partitional clustering algorithm, “k-means,” are used in segmentation. In the implementation, fuzzy analytic hierarchy process is employed to determine the importance of the segments.

Findings

Business customers of an international original equipment manufacturer (OEM) are segmented in the application. In this regard, 317 business customers of the OEM are segmented as “best,” “valuable,” “average,” “potential valuable” and “potential invaluable” according to the cluster ranks obtained in this study. The results of the application reveal that the proposed approach can effectively be used in practice for business customer segmentation.

Research limitations/implications

The success of the proposed approach relies on the availability and quality of customers’ data. Therefore, design of an extensive customer database management system is the foundation for any successful customer relationship management (CRM) solution offered by the proposed approach. Such a database management system may entail a noteworthy level of investment.

Practical implications

The results of the application reveal that the proposed approach can effectively be used in practice for business customer segmentation. By making customer segmentation decisions, the proposed approach can provides firms a basis for the development of effective loyalty programs and design of customized strategies for their customers.

Social implications

The proposed segmentation approach may contribute firms to gaining sustainable competitive advantage in the market by increasing the effectiveness of CRM strategies.

Originality/value

This study proposes an integrated approach for business customer segmentation. The proposed approach differentiates itself from its counterparts by combining MCDM and clustering in business customer segmentation. In addition, it extends the traditional RFM model by including five novel segmentation variables for business markets.

Details

Industrial Management & Data Systems, vol. 115 no. 6
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 1 December 1997

Ali Kara and Erdener Kaynak

Market segmentation has always had a very important place in the marketing literature. Besides being one of the ways of operationalizing the marketing concept, market…

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20084

Abstract

Market segmentation has always had a very important place in the marketing literature. Besides being one of the ways of operationalizing the marketing concept, market segmentation provides effective guidelines for firms’ marketing strategy development and resource allocation among their diverse product markets. As market segmentation simultaneously addresses the roles of both marketers and customers, the segmentation concept has captured the attention of many scholars and practitioners alike in the field. Accordingly, within the last few years, a number of new developments have emerged in market segmentation. Although different terms or concepts may have been used by different researchers, the basic idea behind these developments has been to create more effective and efficient ways of reaching individual consumers in order to satisfy their unique needs and wants. Examines and conceptualizes the recent advancements in market segmentation and development studies and globally explores their managerial implications for marketing practitioners and researchers alike for orderly decision‐making purposes.

Details

European Journal of Marketing, vol. 31 no. 11/12
Type: Research Article
ISSN: 0309-0566

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Abstract

Details

The Organic Growth Playbook: Activate High-Yield Behaviors to Achieve Extraordinary Results – Every Time
Type: Book
ISBN: 978-1-83982-687-0

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Book part
Publication date: 4 December 2020

Irem Ucal Sari, Duygu Sergi and Burcu Ozkan

Customer segmentation is an important research area that helps organizations to improve their services according to customer needs. With the increased information that…

Abstract

Customer segmentation is an important research area that helps organizations to improve their services according to customer needs. With the increased information that shows customer attitudes, it is much easier and also more necessary than before to analyze customer responses on different campaigns. Recency, frequency, and monetary (RFM) analysis allows us to segment customers according to their common features. In this chapter, customer segmentation and RFM analysis are explained first, then a real case application of RFM analysis on customer segmentation for a Fuel company is presented. At the end of the application part, possible strategies for the company are generated.

Details

Application of Big Data and Business Analytics
Type: Book
ISBN: 978-1-80043-884-2

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Article
Publication date: 7 September 2020

Cristina Calvo-Porral and Jean-Pierre Lévy-Mangin

Emotional and affective responses are experienced during service use that determine customer behavior; and for this reason, bank services require an better understanding…

Abstract

Purpose

Emotional and affective responses are experienced during service use that determine customer behavior; and for this reason, bank services require an better understanding of the emotions customers feel in service experiences. This research aims to examine whether different customer segments exist in the bank services industry, based on the emotions they experience when using the service.

Design/methodology/approach

The factors were examined through confirmatory factor analysis (CFA). Then, two-step clustering analysis was developed for customer segmentation on data from 451 bank service customers. Finally, an Anova test was conducted to confirm the differences among the obtained customer segments.

Findings

Our findings show that the emotion-based segmentation is meaningful in terms of behavioral outcomes in bank services. Further, research findings indicate that bank service customers cannot be perceived as a homogenous group, since four customer clusters emerge from our research namely “angry complainers”, “pragmatic uninvolved”, “emotionally attached customers” and “happy satisfied customers”.

Research limitations/implications

Our findings show that the emotion-based segmentation is meaningful in terms of behavioral outcomes in bank services. Further, research findings indicate that bank service customers cannot be perceived as a homogenous group, since four customer clusters emerge from our research namely “angry complainers”, “pragmatic uninvolved”, “emotionally attached customers” and “happy satisfied customers”, being the “angry complainers” the most challenging customer group.

Originality/value

The study is the first one to specifically segment bank customers based on the emotions they experience when using the service.

Details

International Journal of Bank Marketing, vol. 38 no. 7
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 1 July 1990

Arun Sharma and Douglas M. Lambert

Customer service represents a significantopportunity for segmenting markets. This articlereviews the importance of customer service andthe conceptual issues associated…

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1037

Abstract

Customer service represents a significant opportunity for segmenting markets. This article reviews the importance of customer service and the conceptual issues associated with segmenting industrial markets on the basis of customer service. A methodology is presented which can be used by managers to classify a market into segments with different customer service needs. Empirical results from a high‐technology industry are also presented. The article emphasises the need to recognise the differing customer service requirements of segments of customers when establishing priorities for customer service expenditures.

Details

International Journal of Physical Distribution & Logistics Management, vol. 20 no. 7
Type: Research Article
ISSN: 0960-0035

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Article
Publication date: 1 August 2016

Robert J. Thomas

The purpose of this paper is to explore the possibility of identifying market segments in multistage markets and assessing whether their alignment could provide a useful…

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7461

Abstract

Purpose

The purpose of this paper is to explore the possibility of identifying market segments in multistage markets and assessing whether their alignment could provide a useful managerial approach to find competitive advantage and better understand market opportunities.

Design/methodology/approach

Using data from a pilot project, need-based market segments from different market stages were identified and their potential alignment evaluated. The data were not designed to test hypotheses, nor were they originally intended to be used to align segments. Nevertheless, they provided a unique opportunity to explore multistage segmentation and segment alignment in a business-to-business (B2B) setting.

Findings

Overall, the findings of this exploratory study should encourage both academics and practitioners to continue to explore the possibility of studying and aligning multistage market segments. The possibility of aligning segments was demonstrated using visual alignment based on managerial judgment of data and alignment based on a combined cluster analysis of customers across the multistage markets.

Research limitations/implications

First, the market research was not specifically designed to formulate and test hypotheses about the feasibility of aligning segments in multistage markets – it is an exploratory study. The research was based on a pilot project, and the survey-derived databases were conveniently available for analysis. While sample sizes were small, they are typical of many B2B markets. Second, to more effectively study complex relationships in multistage markets, it would have been desirable to include a more comprehensive set of needs. Each market stage has not only a set of their own perceived needs but also a set of perceptions of the needs of other stages. Third, as in many B2B studies, the data used in this pilot project were based on single informants.

Practical implications

A common complaint among firms is that B2B market segmentation does not really work that well for them. An unexplored reason for this may be that true market segmentation does not stop with one’s direct customer, but should also include the customer’s customer and so on, in a multistage market segmentation structure. One implication of the research presented here suggests that better understanding the segmentation structure in a multistage market can enlighten the opportunities and risks of implementing such a strategy. Multistage market segmentation alignment may lead to innovative positioning and message levers for the sales force to use as an argument to gain advantage according to common and unique aligned segment needs.

Social implications

The process may be applied to social institutions in addition to commercial organizations.

Originality/value

While it is obvious that market segmentation can be applied to any single market of customers, the question of applying it to complex multistage markets needs additional exploration. The original idea in this paper is that the potential for strategically aligning multistage markets and segments can have both conceptual and managerial implications for establishing competitive advantage and more efficient and effective resource allocation. The paper shows that that such alignment is possible; however, research and research methods in this area are nascent and will require continued step-by-step learning about these complex market structures to build up to a more definitive understanding of the processes involved to guide future research and managerial thinking.

Details

Journal of Business & Industrial Marketing, vol. 31 no. 7
Type: Research Article
ISSN: 0885-8624

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Article
Publication date: 1 August 2016

Peiman Alipour Sarvari, Alp Ustundag and Hidayet Takci

The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary…

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2705

Abstract

Purpose

The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary (RFM) considerations as well as demographic factors. In this study, the impacts of RFM and demographic attributes have been challenged in order to enrich factors that lend comprehension to customer segmentation. Different types of scenario were designed, performed and evaluated meticulously under uniform test conditions. The data for this study were extracted from the database of a global pizza restaurant chain in Turkey. This paper summarizes the findings of the study and also provides evidence of its empirical implications to improve the performance of customer segmentation as well as achieving extracted rule perfection via effective model factors and variations. Accordingly, marketing and service processes will work more effectively and efficiently for customers and society. The implication of this study is that it explains a clear concept for interaction between producers and consumers.

Design/methodology/approach

Customer relationship management, which aims to manage record and evaluate customer interactions, is generally regarded as a vital tool for companies that wish to be successful in the rapidly changing global market. The prediction of customer behaviors is a strategically important and difficult issue because of the high variance and wide range of customer orders and preferences. So to have an effective tool for extracting rules based on customer purchasing behavior, considering tangible and intangible criteria is highly important. To overcome the challenges imposed by the multifaceted nature of this problem, the authors utilized artificial intelligence methods, including k-means clustering, Apriori association rule mining (ARM) and neural networks. The main idea was that customer clusters are better enhanced when segmentation processes are based on RFM analysis accompanied by demographic data. Weighted RFM (WRFM) and unweighted RFM values/scores were applied with and without demographic factors and utilized to compose different types and numbers of clusters. The Apriori algorithm was used to extract rules of association. The performance analyses of scenarios have been conducted based on these extracted rules. The number of rules, elapsed time and prediction accuracy were used to evaluate the different scenarios. The results of evaluations were compared with the outputs of another available technique.

Findings

The results showed that having an appropriate segmentation approach is vital if there are to be strong association rules. Also, it has been determined from the results that the weights of RFM attributes affect rule association performance positively. Moreover, to capture more accurate customer segments, a combination of RFM and demographic attributes is recommended for clustering. The results’ analyses indicate the undeniable importance of demographic data merged with WRFM. Above all, this challenge introduced the best possible sequence of factors for an analysis of clustering and ARM based on RFM and demographic data.

Originality/value

The work compared k-means and Kohonen clustering methods in its segmentation phase to prove the superiority of adopted segmentation techniques. In addition, this study indicated that customer segments containing WRFM scores and demographic data in the same clusters brought about stronger and more accurate association rules for the understanding of customer behavior. These so-called achievements were compared with the results of classical approaches in order to support the credibility of the proposed methodology. Based on previous works, classical methods for customer segmentation have overlooked any combination of demographic data with WRFM during clustering before proceeding to their rule extraction stages.

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