Complaint Management and the Role of Relationship Quality

Facing dissatisfaction, customers have several alternatives: exit, loyalty and voice. The verbal answer (Voice) can be word-of-mouth communication or a complaint which is a constructive way to express dissatisfaction to obtain a correction or compensation. The management of complaints thus perfectly integrates within scope of customer relationship management to increase loyalty since it gives an organization a last chance to retain dissatisfied clients (Smith et al, 1999). In addition, complaints are a very rich source of valuable information to improve quality continuously. The investigations on complaint management show that the theory of justice (Adams, 1965) explains the satisfaction of complaining customers (Orsingher et al, 2010). However, the questions about the nature and the valence of the compensations as well as which consumer targets to privilege remain unanswered. The principal contribution of this article is thus to determine the most effective dimensions of the theory of justice in the context of customer complaint management to satisfy and retain customers. We differentiate the effectiveness of the complaint management process according to the relationship quality or strength between the firm and the customer. We first describe the key factors for complaint management and then we explain our conceptual model as well as our hypotheses and methodology. Finally, the article shows the results and finishes with a discussion, managerial implications and research directions

La qualité de la relation permet-elle de diminuer les compensations financières dans le cadre du management des réclamations

The purpose of this research is to investigate about the effectiveness of complaint management according to the quality of the relationship between the company and the client. We test how interactional and distributive compensations influence perceived justice of loyal clients with good quality of the relationship and new customers with weak quality of the relationship. The results show that the interactional compensations allow to a) decrease the level of the fi-nancial compensations to customers and b) grant vouchers instead of reimbursement for high relational quality customers.L'objet de cette recherche est d'étudier l'efficacité de la gestion des réclamations selon la qualité de la relation entre l'entreprise et le client. Nous testons comment les efforts interactionnels et les compensations distributives influencent la justice perçue des clients fidèles et nouveaux. Les résultats montrent que les efforts interactionnels permettent de diminuer le niveau des compensations financières adressées aux clients et de privilégier le bon d'achat au remboursement concernant les clients à forte qualité relationnelle

The Long-Term Impact of Sales Promotions on Customer Equity

Sales promotion is an instrument whose effectiveness for shortterm sales is proven (Blattberg and Neslin, 1990). But for the long term, researchers have identified adverse effects without managing to actually determine its impact (Van Heerde et al, 2004). While most investigations analyze the effects of promotions on sales, it is important to consider the global impact, i.e. on the customer portfolio. Although several authors have taken up this issue (Fader and Hardie, 2010; Abe, 2009b), no contribution has integrated the entire portfolio development: customer acquisition, activity of existing customers and churn. This research, therefore, contributes by establishing a long-term vision of the impact of sales promotions on the value of the customer portfolio (customer equity), not just on sales. We combine explanatory and stochastic approaches via the integration of explanatory variables. The second contribution is the application of these models to fast moving consumer goods, a sector that has thus far been over-looked by existing research

BIG DATA-DRIVEN MARKETING: AN ABSTRACT

Customer information plays a key role in managing successful relationships with valuable customers. Big data customer analytics use (BD use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study addresses three research questions: What are the key antecedents of big data customer analytics use? How, and to what extent, does big data customer analytics use influence firm performance? Is competitive advantage, if any, achieved through big data customer analytics use contingent upon its prevalence within an industry? Drawing primarily from market information use theory, we advance a theoretical framework to examine how informational and organizational factors act to enhance big data customer analytics use, which in turn influences customer relationship and financial performance. More specifically, we identify and show how information quality (IQ), big data analytics culture, and customer orientation act as key antecedents of big data customer analytics use, which in turn is the critical mechanism to achieve superior CRM outcomes. Finally, we investigate whether the performance implications of big data customer analytics use vary depending on the prevalence of big data customer analytics use in the firm’s industry. Empirical findings from a survey of 301 senior marketing executives, representing large US-based firms in B2C industries, support our conceptualization of the performance outcomes and antecedents of BD use. First, the results highlight that the characteristics of the customer information (IQ) and the characteristics of the user organization (customer orientation and big data analytics culture) strongly predict BD use. The findings also reveal the relative importance of different customer information characteristics to marketing decision-makers. Second, the results confirm BD use as a key predictor of firm performance, and more specifically, that big data customer analytics use primarily influences financial performance indirectly via customer relationship performance. Third, this study suggests that the performance impacts of BD use are highly contingent on its prevalence among industry rivals. References Available Upon Request

BIG DATA RESOURCES, MARKETING CAPABILITIES, AND FIRM PERFORMANCE.

RESEARCH QUESTION Big data may significantly improve the efficiency and effectiveness of the firm's marketing capabilities. However, firms must overcome technological, skill-based and organisational challenges to become data-driven. Academic research has not empirically investigated how strategic big data resources, and to what extent, influence strategic marketing capabilities and, by extension, firm performance. The primary objective of this research is to remedy this crucial knowledge gap. METHOD & DATA We employed a survey study methodology and administered online questionnaires for data collection. Our sampling frame focuses on strategic business units (SBUs) in large (>1000 employees), US-based, B2C manufacturing and service firms who have invested in big data technologies to support marketing decision making. Using a commercial research panel provider, we targeted senior marketing executives in SBUs across a range of B2C industries. The survey was sent to senior marketing executives and 301 usable responses were received in return to form the final sample. Partial Least Squares structural equation modeling (PLS-SEM) was used as the primary analysis method. KEY CONTRIBUTIONS The study makes two important theoretical contributions with managerial relevance. Firstly, this study makes a novel theoretical contribution with the parsimonious conceptualisation of big data resources (BDR). While all three dimensions (big data technology resources, big data analytics skills, organisational big data resources) are necessary and distinct facets of BDR, big data analytics skills are most important in enhancing marketing capabilities (MC). Based on these findings, we advise managers to ensure that all aspects of the firm’s overall big data asset are sufficient. Second, the results show that MC fully mediates the relationship between BDR and firm performance, indicating that BDR is a source of competitive advantage when leveraged in complementary marketing processes. We therefore urge managers to ensure that big data resources are properly aligned with the firm’s marketing processes. SUMMARY OF FINDINGS In this paper, we posit that strategic big data resources (BDR) play a key role in improving strategic marketing capabilities (MC) to achieve competitive advantage. Empirical findings from a survey of 301 senior marketing executives, representing large US-based firms in B2C industries, support the proposed model. The results highlight that BDR, encompassing technological, human and organizational IT resources, is a critical antecedent of MC. The findings also show that BDR is a source of competitive advantage when leveraged by MC

Special issue: Customer empowerment

The second French-German workshop about Consumer Empowerment took place at the University of Karlsruhe (KIT) between January 10-11, 2013. Within the scope of consumer empowerment scientists discussed recent developments in this field and established cross-disciplinary coop- erations in their own fields of research

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Customer information plays a key role in managing successful relationships with valuable customers. Big data analytics use (BD use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study aims to (1) determine whether organizational BD use improves customer-centric and financial outcomes, and (2) identify the factors influencing BD use. Drawing primarily from market information use theory, we advance a model to explain how information quality (IQ), customer orientation and big data analytics culture predict BD use, which in turn influences customer relationship and financial performance.Empirical findings from a survey of 301 senior marketing executives, representing large US-based firms in B2C industries, support our conceptualization of the performance outcomes and antecedents of BD use. All seven hypotheses received empirical support.The results highlight that the characteristics of the customer information (IQ) and the characteristics of the user organization (customer orientation and big data analytics culture) strongly predict BD use. The findings also reveal the relative importance of different customer information characteristics to marketing decision-makers.Practitioners may significantly improve firm performance with BD use, but only if certain antecedent factors facilitate BD use in the organization. We offer managers advice how to overcome challenges specific to BD use by managing the quality aspects of customer information, and by fostering shared customer-oriented and analytics-oriented cultures.</p

Complaint Management: Which efforts to satisfy the complainers: the role of relationship quality?

International audienceThe aim of this communication is to study the effectiveness of complaint management according to the quality of the relationship between the firm and the customer. We compare interactional (relational) and distributive (monetary) compensation in terms of preference for loyal and new customers. The results show that loyal customers prefer interactional efforts and purchase vouchers to refunding. New customers prefer distributive compensations and refunding

The impact of reward personalisation on frequent flyer programmes' perceived value and loyalty

Purpose – The purpose of this research is to contribute to a better theoretical and empirical knowledge about the way frequent flyer programmes influence customer behaviour. It aims to describe the relationships between purchase orientations and personalized rewards on customers' perceived programme value and subsequent loyalty. Design/methodology/approach – The research uses self-determination theory (SDT) and purchase orientations to classify types of rewards in terms of their effect on perceived programme value and loyalty. Scales are developed through exploratory and confirmatory factor analysis. To validate the hypotheses, surveys are realized in a major international airline. Structural equation modelling confirms the research model. Findings – Perceived value and loyalty vary according to purchase orientation, in support of the SDT. Intrinsic (extrinsic) rewards motivate customers to act to obtain a benefit within (apart from) the target of their purchase orientation and influences loyalty positively (have low impact on loyalty). Research limitations/implications – Further testing of reward types, in(ex)trinsic motivation, SDT, across multiple contexts is necessary for validity enhancement. Practical implications – Differentiation through tailored (non-)monetary rewards is possible in markets marked by strong competition to appeal to different segments. Originality/value – This is one of the pioneer articles in the use of SDT in marketing research. The development of scales which focus on reward types and the moderating impact of purchase orientations on frequent flyer programmes' perceived value and loyalty is another contribution