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The aim of the paper is to show how intelligence emanating from customer profitability analysis (CPA) can help improve strategic marketing planning. Insights into the profitability of individual customers, as well as the distribution of profitability across the customer base, can lead to better decisions in the areas of managing costs and revenues, managing risks and strategic market positioning.

The concept and process of CPA are first explained. The heart of the paper then discusses how the outcomes permit novel analyses related to costs and revenues, risk, and strategic positioning. Finally, the paper explains what is needed to make the shift from retrospective CPA to prospective CPA.

CPA delivers two types of insights: the degree of profitability for each individual customer, and the distribution of profitability among customers within the customer base. Profitability data at the level of the individual customer support better decision making about service levels, marketing investments and pricing strategies. The profitability distribution curve yields information about the vulnerability of future cash flows from customers. Further, DPA data permit segmentation and targeting on the basis of profitability and the development of different value propositions for different profitability segments.

Shareholder value is created through cash flows from customers. CPA uncovers where these cash flows are generated. Armed with customer profitability data, marketers can really develop and implement value‐driven differentiated customer service strategies.

While quite a number of published papers have discussed the technicalities of calculating customer profitability, this paper adds to the literature an overview of how the outcomes of such calculations can help planners make better decisions, to increase the magnitude of cash flows from customers and/or reduce the volatility and vulnerability of such cash flows.

This paper aims to assess the usefulness of cost‐to‐serve for customer profitability management through literature review and a case study in a food‐industry company.

The research is based on a case study. The study presents the state‐of‐the‐art of the literature review related to cost‐to‐serve measurement and customer profitability analysis and a case study of a Brazilian food‐industry company with high operational complexity and an extensive customer product and commercial service line.

The literature review demonstrates that few empirical studies have actually addressed the problem of cost‐to‐serve measurement and customer profitability analysis. The findings of the study show that the measurement of cost‐to‐serve provides specific and detailed customer information that enables a more comprehensive customer profitability analysis than the classical paradigm.

A single case study does not allow the results to be generalized to other organizations.

The paper includes a comprehensive review of literature and the empirical case study in a Brazilian food company offers additional insights in cost‐to‐serve measurement and customer profitability analysis.

The profitability of individual customers can show substantial variation, both in money amounts and in margins (percentages). The literature suggests that larger customers have a higher customer profitability margin: a dollar in revenue from a large customer generates more profit than a dollar in revenue from a small customer. The purpose of this paper is to explore the relationship between customer size and the customer profitability margin.

Draws up a model with five variables (customer size, product margin, exchange efficiency, support, customer profitability margin) and hypothesizes the relationships between the variables. Uses LISREL to test the relationships on a database from a business‐to‐business setting.

The relationship between customer size and customer profitability margin is not direct, but runs through other variables, mainly exchange efficiency. It is not the result of larger customers paying higher product margins or having fewer customer support demands.

Adds to the empirical literature on customer profitability. Ideally, this would be done using panel data rather than the cross‐sectional data used in this paper.

Profitability data at the level of individual customers provide useful insights. Customer size as such is not a driver of the customer profitability margin. Identify the trade‐offs between customer size, product margins (discounts), support demands, and exchange costs that ultimately lead to customer profitability.

Adds to the empirical literature on customer profitability and offers practical implications for managing customer relationships.

The purpose of this paper is to explore the links between customer loyalty attitude, customer loyalty behaviours (measured by customer purchase behaviours) and profitability. The aim is to define a conceptual framework within which to analyse the relationships between attitudes, behaviour, and profitability of the customers.

Reference was made to earlier studies which argued that loyal customers constitute competitive asset of business organizations. Several authors noted that customers generally vary in terms of loyalty behaviours and attitudes and highlighted that differences about customers' loyalty levels affect a firm's profitability results. Customer loyalty, its antecedents and outcomes, and the links between customer satisfaction, customer loyalty and profitability have been analyzed at a customer level.

The results showed support for all but one of the five hypotheses, the exception being H2.

The results of the study provide evidence that a Loyalty Index can give managers an adequate support for market segmentation. This means that actual market segment strategies, based on geographical, demographical and/or psychographic variables, should take into account also loyalty measurement models.

As Lindsay (1994, 1995) encourages validation of existing results, this research replicates Guilding and McManus (2002) in a New Zealand (NZ) context. The usage and perceived merit of customer accounting practices were lower in NZ than in the Australian study. Few of the regressions where customer accounting usage and perceived merit were dependent variables revealed a statistically significant role for competition intensity and market orientation. There was some minor support for the perceived merit of customer accounting being higher in companies experiencing medium levels of competition intensity.

This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

A joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.

The fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.

The analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínez et al., 2019).

In terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).

This paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russo et al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.

By fusing knowledge-based theory, organizational learning theory and dynamics capability theory, this study aims to explore, on the one hand, the linkage between exploration, sensing and tacit knowledge, and on the other hand, exploitation, seizing and explicit knowledge. Thereby, it argues that not only tacit knowledge but also explicit knowledge contributes to competitive advantage for firms. This study also investigates how knowledge transforms into profitability.

The conceptual model is tested with a study sample of 153 industrial organizations using structural equation modelling.

Results confirm the importance of both tacit and explicit knowledge for achieving sustainable competitive advantages. Furthermore, both tacit and explicit knowledge transform into profitability, both directly and through product innovation and customer centricity which play partial mediating roles.

Explicit knowledge strategies can be easier to manage, implement and institutionalize than tacit knowledge strategies, which require human component and intervention to succeed. Managers should hence first implement explicit knowledge strategies to gain expeditious results. Further, with the advent of digital technologies and algorithms that can extract deep customer insights and organizational experiences which are highly tacit in nature and codifying the same into explicit knowledge, the importance of explicit knowledge is further enlarged.

By fusing three adjacent theories to establish a robust model specification, this study is able to demonstrate the contribution of explicit knowledge in the firm’s competitive advantages.

Many researches have proposed a virtuous chain of effects from improved customer satisfaction to profits. In particular, satisfaction is thought to improve share‐of‐spending, which in turn leads to higher customer revenue and customer profitability. This paper aims to examine these proposed linkages using data from the institutional securities industry.

The data used in the analyses were collected as part of an ongoing telephone satisfaction survey of 81 clients of an institutional securities firm across two continents (North America and Europe). Mediation analysis was used to test the hypothesized effects.

Customer revenue was found to correlate negatively with customer profitability for unprofitable customers, and positively for profitable customers.

One of the limitations of this research is that it tests the propositions within a single industry. Future research should attempt to replicate these findings in other contexts.

A simplistic focus on improving customer satisfaction for all customers in order to improve share‐of‐wallet and customer revenue does not seem to represent the best management approach to maximize overall firm profitability. In fact, it could actually result in a negative return on investment. Therefore, customers should first be segmented by their profitability to the firm before expending resources to improve customer satisfaction and share‐of‐wallet.

The results of this paper challenge the conventional belief that customer satisfaction should lead to customer retention in turn, resulting in customer revenue and ultimately customer profitability. The findings indicate that this may not always be true.

The aim of this study is examine customer relationship management (CRM) effect on enhancing customer satisfaction and on improving customer retention. In this study, the impact of CRM on loyalty in the pharmaceutical sector in Tunisia is studied. Service quality perception, customer satisfaction, loyalty, retention and firm profitability have been tested as independent variables. This study highlights the importance of CRM and service quality perception in maintaining a sustainable and profitable relationship with customers.

A survey research design was used to collect data. In total, 221 respondents from 5 pharmaceutical companies in Tunisia were involved in the study. Exploratory and confirmatory analyses were adopted to examine the effect of CRM technology on profitability. Structural equation modeling was used to validate results.

The results show that there are significant relationships between CRM and quality perception, satisfaction and loyalty. However, there are no significant relationships either between CRM and retention or between CRM and profitability.

Fitting CRM scale with the context of the study and the number of the survey companies was the limitation of this research.

This study provides significant results to practitioners to understand the role of establishing a CRM strategy and to understand the selected factors affecting customer satisfaction and retention as well.

This study was conducted in Tunisia to contribute to enrich literature in the implementation of information technology and customer satisfaction.

The purpose of this paper is to propose a method to help firms assess lifetime profitability of customers whose buying behaviors are characterized by purchasing cycles, which are determined by both intrinsic purchasing cycles and cumulative effects of firms’ marketing solicitations.

This paper first proposes a probability model to predict customers’ responses to firms’ marketing solicitations in which a customer’s inter-purchase times are assumed to follow a Poisson distribution, whose parameters vary across customers and follow a gamma distribution. The paper then proposes a customer profitability scoring model that uses customers’ responses as an input to assess their lifetime profitability at a given point of time.

The paper illustrates the proposed method using individual-level purchasing data of 529 customers from a catalog firm. The paper shows that the proposed model outperforms the benchmark model in terms of both explaining and predicting customers’ purchases. The paper also demonstrates significant profit consequences to the firm if incorrect methods are used instead of the proposed method.

The proposed method can help firms select or eliminate customers based on their lifetime profitability so that firms can focus their marketing efforts in a more targeted manner to increase total profits.

The proposed Gamma-Poisson probability model and the profitability scoring method are easy to implement due to the attractive conjugacy property. It is valuable for firms’ customer relationship management applications from the standpoint of making customer selection and inventory management decisions.