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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.

The authors offer a new approach to segment credit card customers by classifying customers into two unobserved (latent) segments: opportunistic and needy.

The authors develop a finite mixture model to estimate customers’ tendency to borrow using the three alternatives available to them—promotional cash advances, regular cash advances and retail balances.

The results support the presence of at least two segments among credit card customers. The authors find that relative to opportunistic individuals, needy customers are typically more sensitive to interest rates. Additionally, the results indicate that offering promotional cash advances to current credit card customers increases their sensitivity to regular interest rates. Furthermore, the findings indicate that needy customers tend to have a higher stickiness in their debt. In the post-estimation analyses, the authors observe that needy customers generate more revenue than opportunistic customers. Interestingly, the bank does not perform well in targeting needy individuals and targets both groups with the same probability.

The authors argue that teaser rates attract at least two segments of borrowers—the “needy” segment, which is more likely to be cash-strapped, and the “opportunistic” segment, which looks at these teaser rates as an opportunity. However, banks do not observe segment membership. Hence, the authors offer a new approach to identifying these segments and show that understanding the behavior of these latent segments could help a bank target profitable customers more effectively.

This study aims to use big data analysis and sheds light on key hotel features that play a role in the revisit intention of customers. In addition, this study endeavors to highlight hotel features for different customer segments.

This study uses a machine learning method and analyzes around 100,000 reviews of customers of 100 selected hotels around the world where they had indicated on Trip Advisor their intention to return to a particular hotel. The important features of the hotels are then extracted in terms of the 7Ps of the marketing mix. This study has then segmented customers intending to revisit hotels, based on the similarities in their reviews.

In total, 71 important hotel features are extracted using text analysis of comments. The most important features are the room, staff, food and accessibility. Also, customers are segmented into 15 groups, and key hotel features important for each segment are highlighted.

In this research, the number of repetitions of words was used to identify key hotel features, whereas sentence-based analysis or group analysis of adjacent words can be used.

This study highlights key hotel features that are crucial for customers’ revisit intention and identifies related market segments that can support managers in better designing their strategies and allocating their resources.

By using text mining analysis, this study identifies and classifies important hotel features that are crucial for the revisit intention of customers based on the 7Ps. Methodologically, the authors suggest a comprehensive method to describe the revisit intention of hotel customers based on customer reviews.

For agricultural bankers, agribusiness managers, and salespeople, understanding customers and their preferences and behaviors is crucial to success. The two goals of this paper are first to identify today's distinct market segments for financial products for US crop and livestock commercial producers, and second to predict segment membership based on observable characteristics.

Cluster analysis was used to identify four distinct buyer segments for the purchase of financial products and services by US crop and livestock commercial producers. A multinomial logit model was used to predict segment membership based on demographic, behavioral, and business management factors.

Although, traditionally, the financial services industry has segmented the market for commercial producers based primarily on sales/size categories; this research shows that this factor is not a significant predictor of behavior. Instead, this paper proposes a segmentation based on buying behaviors and identify four distinct market segments for financial products and services for US crop and livestock commercial producers: balance, price, convenience, and service. The balance segment being by far the largest segment.

Although the sample size means is representative of the US ag population, it may or may not be representative of the customers of a regional lender. Readers who are lenders are therefore advised to apply this methodology to their customer database and use the results of the paper as a quality check or benchmarking exercise. The findings also raise a number of issues, which require further research, such as how to implement a targeted marketing plan when there is one dominant segment and two other distinct segments.

Lenders need to reconsider their market segmentation methodology.

While there has been some research on market segments for retail financial markets, apparently there has been no work on market segments for agricultural financial products. This study exploits a unique dataset of 2,575 responses to Purdue's Large Commercial Producer Survey and the 2008 survey is the first time the survey included a series of detailed questions on how producers choose a financial service provider. This paper's findings will benefit agricultural bankers and agribusinesses that offer financing to their customers.

The purpose of this paper is to investigate customers' intentions to purchase mobile communications services and how these intentions are affected by the customers' price perceptions in two customer segments – a mobile segment and a combined segment. A further aim was to gain insight into the formation of price perceptions, and customer characteristics that underlie the differences between purchase intentions and price perceptions.

The study was conducted in the Finnish mobile services market. The sample data were collected through a postal survey (n=3,000) sent to customers of a Finnish teleoperator. In analyzing empirical data the explanatory factor analyses, linear regression analyses, and analysis of variance were applied.

The results indicated that a significant and positive relationship exists between customers' price perceptions and their purchase intentions, and that the formation of price perceptions is significantly influenced by satisfaction with pricing and services. Price transparency was found to be negatively associated with customers' price perceptions. Gender, age, and experience of service use were found to explain the differences in customers' perceptions.

By segmenting customers according to the research results and targeting pricing schemes specific to these segments would potentially improve customers' price perceptions and their intentions to purchase mobile services. The study also supported the use of multi‐dimensional pricing schemes as it was found to positively influence customers' price perceptions.

This paper provides new practical and theoretical insights into the relationship between purchase intentions and price perception, and into the formation of the price perceptions of mobile services customers.

This paper aims to segment spa customers based on their preferences for a set of spa attributes. With the considerable growth rate of the spa market, it is vital for spa professionals to understand spa-goers’ preferences. However, academics and industry professionals have not devised a structured method by which to manage spa customers.

A survey was conducted using a face-to-face survey with visitors to Hong Kong who had visited a spa. By applying conjoint and cluster analysis, customers could be categorized into distinct segments.

Four customer segments were identified: spa enthusiasts, high spenders, value seekers and price-sensitive spa-goers. Spa enthusiasts were the largest segment among the four, followed by value seekers, price-sensitive spa-goers and high spenders.

Given the limited academic interest in the area, this study contributes to the literature by providing insights into spa-goers’ preferences and how those preferences can be used to segment spa-goers.

Based on the different needs, preferences and socio-demographic characteristics of the four segments – spa enthusiasts, high spenders, value seekers and price-sensitive spa-goers – spa industry managers could customize their strategies and design different spa services and packages to meet the needs of the four segments.

The combined use of conjoint and cluster analysis provides a new method of market segmentation in the spa industry. This study could help spa professionals to design customized spa products for the distinct segments, and thus retain and attract more spa visitors.

Businesses risk losing customers when traditional product‐based features, attributes, and benefits are no longer differentiated. Offsetting that risk requires taking a more customer‐centric approach to the brand and business. This entails developing a far deeper understanding of the customer than can be gained through traditional demographic‐based research. At issue is what motivates the purchase decision, and how well the motivating factors are being addressed or could be better addressed at each customer touch point. Organizations seeking to adopt a more customer‐focused strategy will learn from the approach DuPont Performance Coatings took in grappling with this challenge, based on an extensive program of qualitative and quantitative research with customers around the globe. This article focuses on two particular areas of interest. First is the model and far‐reaching research conducted, which revealed comprehensive details on customer priorities and product usage behaviors. The characteristics uncovered became the basis for segmenting customers into groups that could be better targeted to re‐establish relevance and solidify their relationship with the brand. Second is the customer touch‐point analysis, which facilitated alignment of functional groups within the organization (product, sales, customer service, etc.) and equipped them to deliver on newly developed, segment‐specific value propositions. This major initiative has enabled DuPont to reprioritize internal efforts and business practices and been a catalyst for broader organizational changes notably the dissolution of many functional silos that previously had hindered its ability to deliver against its brand promise.

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.

The purpose of this study is to investigate the relationship marketing (RM) strategy of a retail bank and examine whether – after its implementation – customer relationships were strengthened through perceived improvements in the banking relationship and consequent loyalty towards the bank.

A survey was conducted on two profitability segments, of which the more profitable segment had been directly exposed to a customer oriented RM strategy, whereas the less profitable segment had been subjected to more sales oriented marketing communications.

No significant differences were found between the segments on customers' evaluations of the service relationship or their loyalty toward the bank. Furthermore, regression analysis revealed that relationship satisfaction was less important as a determinant of loyalty in the more profitable segment.

This study was conducted as a case study of one specific branch of a bank group in Finland, which limits the external validity of its results. It was not possible to ascertain if, or to what extent, customers of the more profitable segment had received the intended RM treatment. Other limitations are also discussed.

Customer orientation is desirable within retail banking and more studies are needed on the differential drivers of loyalty across customer profitability segments. By identifying the aspects of a banking relationship that are more highly valued among more profitable customers than among less profitable customers, bank managers would be able to more effectively devise appropriate strategies for different segments.

The study contributes to the RM literature and marketing of financial services by providing empirical evidence of the effects of RM activities on customer relationship perceptions in different profitability segments.