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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.

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.

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.

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.

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.

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.

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

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.

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

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.

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

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.

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.

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.

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.

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

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.

This paper aims to examine project management segments based on customer satisfaction drivers and loyalty rather than traditional demographic or behavioural variables.

Data were gathered over 18 consecutive months, and 3,129 surveys were completed using a questionnaire. The statistical methods included partial least squares (PLS) structural equation modelling, finite mixture segmentation, prediction-oriented segmentation (PLS-POS) and multi-group analysis (PLS-MGA).

The findings indicate the existence of three segments among system delivery project customers based on the differences in the strengths of the path coefficients in the customer-centric structural model. In Segment 1, satisfaction based on the proposal was crucial for loyalty, with the value-for-money construct negatively impacting the repurchase intent construct. Segment 2 had a solid value-for-money orientation. In Segment 3, the critical path indicated that satisfaction drove repurchase intention, with satisfaction based mainly on the installation.

The research contributes to the segmentation theory by introducing a new way to segment the systems delivery projects customers based on the perceived strength of the relationships in a customer-centric structural model, which aligns with traditional segmentation theory in a way that most segmentation analyses do not. A new segmentation approach to the domain of project management theory is presented. Based on the results, treating the system delivery project customer base as a single homogenous group can lead to managerially misleading conclusions.

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.

This research aims to comprehend the factors that impact the emerging inclination of consumers toward mobile finance technology (fintech) services over banking institutions. The study focuses on users' demographics and psychographics to delineate their unique segments and profiles.

The study proposes a segmentation and profiling framework that includes variance analysis, two-step cluster analysis and pairwise statistical tests. This framework is applied to a dataset of customers using a range of mobile fintech services, specifically robo-investment, peer-to-peer (P2P) payments, robo-advisory and digital savings. The analysis creates distinct customer profile clusters, which are later validated using pairwise statistical tests based on segmentation output.

Empirical results reveal that P2P payment service users exhibit a higher frequency of usage, proficiency and intention to continue using the service compared to users of robo-investment or digital savings platforms. In contrast, individuals utilizing robo-advisory services are identified to have a significantly greater familiarity and intention to sustain engagement with the service compared to digital savings users.

The findings provide financial institutions, especially traditional banks with actionable insights into their customer base. This information enables them to identify specific customer needs and preferences, thereby allowing them to tailor products and services accordingly. Ultimately, this understanding may strategically position traditional banks to maintain competitiveness amidst the increasing prominence of fintech enterprises.

This research provides an in-depth examination of customer segments and profiles within the mobile fintech services sphere, thus giving a nuanced understanding of customer behavior and preferences and generating practical recommendations for banks and other financial institutions. This study thereby sets the stage for further research and paves the way for developing personalized products and services in the evolving fintech landscape.

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.

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.

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.

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.

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.

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.

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.

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

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.