This article presents a marketing communications process that uses customer relationship management ideas for multichannel retailers. The authors describe and then demonstrate the process with enterprise-level data from a major U.S. retailer with multiple channels. On the basis of the results, the authors develop an initial marketing com-). The authors thank the special issue consulting editors, William Boulding and Richard Staelin, for their helpful comments on this article. They are also grateful for the assistance of Len Berry and the Center for Retailing Studies at Texas A&M University. O ver the past decade, customer relationship management (CRM) has proved critical in helping firms make more money by enabling them to identify the best customers and then satisfy their needs so that they remain loyal to the firm. More recently, CRM has grown increasingly complex with the proliferation of retailers expanding their channels of distribution (Cleary 2000). This has led to the need for enterprise-level data, which are the aggregation of data gathered from all firm interactions with their customers across all channels. Given this data-rich, dynamic environment, how can a firm identify the customers who will migrate among its multiple channels and predict their migration patterns? More important, how does the firm communicate with these customers to influence their channel choices and, ultimately, their value? This research focuses on answering these questions.Thus, this article has two general objectives. First, we illuminate a process by which multichannel retailers can leverage enterprise-level data to understand and predict their customers' channel choices over time. Second, we demonstrate how the information gained from this process can be used to develop strategies for targeting and communicating with customers in a multichannel environment. The benefits achieved from the application of this process include increased efficiency in marketing expenditures and enhanced customer value. In the next section, we outline the general process for managing marketing communications (MARCOM) with multichannel retail customers. Subsequently, we demonstrate the application of the process using an enterprise database of a multichannel retailer. We conclude by noting the limitations of the study and ideas for further research in this area. The Multichannel MARCOM ProcessThe process of managing MARCOM in a multichannel environment begins with the identification of relevant factors that differentiate among customers who use different channels. It continues with the development of a communication strategy for existing customers, and it ends with the prediction of the right communications strategy for prospects and new customers. Step 1: Estimate a Segment-Level Channel Choice ModelThe critical aspect of this step of the process is not choosing the model (e.g., multinomial logit or probit) as much as it is specifying the model. It is important that the variables in the model are factors that (1) drive channel choice, (2) help clas...

The primary goal of this study is to investigate the roles of expectations and purchase criticality on consumers' brand perceptions and attribution behaviors in service delivery failures. The provision of logistics services is often a crucial point in supply chain management that can influence brand perceptions of customers. Indeed, the level and the quality of customer service provided may determine whether the organization will retain existing customers or even attract new ones. As a consequence, a failure in logistics customer service and its effect on overall perceptions of a brand should not be underestimated. Furthermore, the involvement of a third‐party logistics (3PL) company in this failure situation can create considerable shifts in the responses of consumers, especially in the attribution behavior for cause of failure. By applying scenario‐based experiments, this study demonstrates the dynamics by which customer expectations, purchase criticality and 3PL companies affect consumer brand perceptions and attributions. The results suggest the presence of two expectation‐based buffering effects in delivery failures. The first buffering effect is revealed in overall brand evaluation and repurchase intention, while the second buffering effect is observed in consumer brand attribution. The findings indicate that higher expectations may protect the brand and cause more attribution to the third‐party service provider. Additionally, it is shown that criticality of the purchase has crucial impacts on brand evaluations and attributions.

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Purpose This paper aims to examine the relationships between locus of attribution, recovery justice perceptions, recovery satisfaction and repurchase intention after a B2B service failure. Design/methodology/approach Structural equation modeling was used to analyze 300 customer surveys from hospitality businesses. The connections between the selected variables were explored through path analysis using AMOS 24. Findings Based on the results, the more that business customers blame their wholesalers after a service failure, the less they perceive the procedures in the recovery process as fair. Findings also indicate that in the recovery process, interactional connections through fair treatment and inclusion of customer opinions are important to achieve high recovery satisfaction levels. Moreover, if business customers perceive the monetary compensation provided as fair, their recovery satisfaction increases, and recovery satisfaction then helps to retain these business customers after a service failure. Research limitations/implications Starting from the locus of blame, this study highlights the after-failure calculation that business customers make in considering their recovery justice perceptions and the resulting satisfaction level. Practical implications The findings have relevance for B2B relationships. This study provides practical processes for failure and recovery management in B2B settings, especially for wholesale providers who function as resellers rather than as manufacturers. Originality/value The contributions from this study are largely due to examining B2B service failure and recovery as a process that starts at the pre-recovery stage with the locus of attribution followed by recovery justice perceptions. Whereas other studies have focused more on justice perceptions, the authors go back a step in the recovery process to better understand the antecedents of repurchase intention in B2B transactions.

Purpose – The purpose of the paper is to develop and test a psychometrically valid scale for musical intelligence as an individuating variable. This scale can elicit individual differences on reactions to sonic branding stimuli such as audio logos, radio jingles and commercial music. Design/methodology/approach – A two-step confirmatory factor analysis followed by structural equation modeling was used to develop and test the scale. Data were collected across three studies consisting of 470 participants. The scale was developed and nomologically validated. Findings – Findings suggest that musical intelligence discriminates reactions to music as evidenced by the three component conceptualization of musical intelligence. Originality/value – This study offers an original, three-component conceptualization of musical intelligence, proposes a measurement scale and then presents evidence of construct validity. Finally, the paper discusses potential applications of the scale in personality research.