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Marketing channels are among the most important elements of any value chain. This is because the bulk of a nation´s manufacturing output flows through them. The intermediaries (e.g., distributors, wholesalers, retailers) constituting marketing channels perform specific distribution functions,such as transportation, storage, sales, financing, and relationship building, better than most manufacturers. Over his distinguished career, Louis P. Bucklin investigated many questions about the structuring and functioning of marketing channels using conceptual, empirical, and microeconomics model-based methodologies. Today, the academic marketing literature contains hundreds of articles that have employed these three broad classes of methodologies to investigate issues of channel intermediaries´ interorganizational relationships, for example, power-dependence, relational outcomes, conflict and negotiations, and manufacturing firms´ channel strategy, for example, channel structure, selection, coordination and control. So far, however, there has been no review of how the three different methodologies have contributed to advancing knowledge across this set of channels research domains.
How to separate the wheat from the chaff: improved variable selection for new customer acquisition
(2017)
Steady customer losses create pressure for firms to acquire new accounts, a task that is both costly and risky. Lacking knowledge about their prospects, firms often use a large array of predictors obtained from list vendors, which in turn rapidly creates massive high-dimensional data problems. Selecting the appropriate variables and their functional relationships with acquisition probabilities is therefore a substantial challenge. This study proposes a Bayesian variable selection approach to optimally select targets for new customer acquisition. Data from an insurance company reveal that this approach outperforms nonselection methods and selection methods based on expert judgment as well as benchmarks based on principal component analysis and bootstrap aggregation of classification trees. Notably, the optimal results show that the Bayesian approach selects panel-based metrics as predictors, detects several nonlinear relationships, selects very large numbers of addresses, and generates profits. In a series of post hoc analyses, the authors consider prospects’ response behaviors and cross selling potential and systematically vary the number of predictors and the estimated profit per response. The results reveal that more predictors and higher response rates do not necessarily lead to higher profits.
Customer relationship management (CRM) is one of the most frequently adopted management tools and has received much attention in the literature. From a company-wide perspective, CRM is viewed as a complex process requiring interventions in different company areas. Previous research has already highlighted the pitfalls and failures related to a partial and incomplete view of CRM. This study advances research on CRM by investigating the impact of the relative implementation time according to which interventions are implemented in different areas (customer management, CRM technology, organizational alignment, and CRM strategy) on CRM performance. The results of the empirical study reveal that compared to other critical CRM activities, a later implementation of organizational alignment activities has a negative impact on performance. Further, our results show that CRM implementations do not equally address the areas of customer acquisition, growth, and loyalty, since this clearly depends on company objectives and also on geographical differences.
Das Ziel der vorliegenden Studie war es, den Zusammenhang zwischen der Implementierung von CRM-Prozessen und der Kundenzufriedenheit zu analysieren. Unsere Untersuchung ist einigen grundsätzlichen Beschränkunfen unterworfen. CRM ist immer noch ein relativ junges Forschungsgebiet, dessen Prozesse sich im Zeitablauf mit großer Wahrscheinlichkeit noch weiterentwickeln werden. Manche Praktiken werden als ineffektiv identifiziert und verworfen werden; andere existierende Prozesse werden eine Verbesserung erfahren. Es ist zudem zu erwarten, dass neue Prozesse und Aktivitäten entwickelt und eingeführt werden. Als Folge dieser Entwicklungen ist es möglich, dass die hier berichtete Wirkung auf die Kundenzufriedenheit durch die Implementierung von CRM-Prozessen sich im Laufe der Zeit ebenfalls ändern wird. Ein interessanter Forschungsansatz wäre daher die Beobachtung dieser Evolution im Zeitablauf.
Darüber hinaus muss in dieser Studie beachtet werden, dass die Kundenzufriedenzeit lediglich ein vorökonomisches Ziel des CRM ist. Einzelne Investitionen in eine bestehende Geschäftsbeziehung müssen anhand der Wertigkeit des Kunden für das Unvernehmen vorgenommen werden.Bestehen ferner keine Alternativen zum bisherigen Anbieter, so ist es ökonomisch nicht sinnvoll, Ressourcen zur Steigerung der Kundenzufriedenheit einzusetzen, da ein Wechsel des Anbieters unwahrscheinlich ist.
Schließlich nutzten wir für die vorliegende Studie Skalen zur Einschätzung der Einstellungen der Kunden durch die Unternehmen. Da dieses Vorgehen möglichst genaue Beurteilungen erfordert, kann es sein, dass die Daten gewisse Verzerrungen aufweisen. Zukünftige Forschungsansätze könnten die Studie durch eine ergänzende Einschätzung der Kunden zur Kreuzvalidierung sinnvoll erweitern.
While the topic of Customer Relationship Management (CRM) has generated an increasing amount of research attention in recent years, still lacking is a comprehensive overview that helps to explain how companies can implement CRM successfully. To address these issues, this article identifies and discusses factors that are associated with a greater degree of CRM success. More specifically, we identify and discuss determinants on strategy, human resources, information management, structure and processes as well as specific factors within the implementation phase which help to improve CRM success. First, our results indicate that the implementation of CRM processes is associated with better company performance, especially at the relationship initiation and maintenance stage. Second, the findings emphasis a predominant influence of firm-based factors vis-à-vis structural industry, and customer-based factors. Furthermore, cross-functional CRM teams and a top management feeling responsible for CRM projects help to improve CRM success. In addition, internal processes which are related to customer contact points have to be redesigned to enhance the interaction between employees and customers. The current article sheds more light on what really drives CRM success.
