Sebastian Tillmanns

Last Name

Tillmanns

First Name

Sebastian

ORCID

0000-0001-5190-1309

Organisational unit

03995 - von Wangenheim, Florian / von Wangenheim, Florian

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Publications 1 - 10 of 11

How to Separate the Wheat from the Chaff: Improved Variable Selection for New Customer Acquisition
Tillmanns, Sebastian; Ter Hofstede, Fenkel; Krafft, Manfred; et al. (2017)
Journal of Marketing
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.
Kundenbindungsprogramme: State of the Art und Forschungsperspektiven
Tillmanns, Sebastian; Wissmann, Johannes (2012)
Marketing ZFP
Die Forschung zu Kundenbindungsprogrammen, einem in der Praxis zentralen loyalitätsbildenden Instrument, zeichnet sich durch ein hohes Ausmaß an Diversität und teilweise widersprüchlichen Ergebnissen aus. Der vorliegende Beitrag arbeitet die bestehende Literatur zu Kundenbindungsprogrammen detailliert und systematisch anhand eines auf dem situativen Ansatz basierenden Bezugsrahmens auf. Es wird dargelegt, wie der Erfolg von Kundenbindungsprogrammen durch deren Gestaltung positiv beeinflusst werden kann und welche Kontextfaktoren dabei zu beachten sind. Auf Grundlage der Literaturanalyse werden relevante Forschungsperspektiven in den Teilbereichen des theoretischen Bezugsrahmens identifiziert. Dabei wird aufgezeigt, dass eine Meta-Analyse, die Bedeutung von Kundenwissen sowie der Shareholder Value vielversprechende Ansätze für weitere Forschung im Bereich der Erfolgswirkungen von Kundenbindungsprogrammen bieten. Des Weiteren ist eine nähere Untersuchung von Einflussgrößen, die den Programmerfolg mindern können, sowie die Entwicklung einer Taxonomie von Kundenbindungsprogrammen notwendig, um der Programmvielfalt Rechnung zu tragen.
Ein empirischer Vergleich von Kundenbindungsdeterminanten im Business-to-Business-Bereich
Tillmanns, Sebastian; Götz, Oliver (2011)
Marketing ZFP
In der aktuellen Marketingforschung ist eine Vielzahl von Studien dem Einfluss verschiedener Determinanten auf die Kundenbindung gewidmet. Die Mehrzahl dieser Untersuchungen fokussiert dabei auf eine käuferorientierte Perspektive. Bislang sind dagegen kaum Versuche unternommen worden, eine anbieterbezogene Perspektive des Managements von Kundenbeziehungen zu untersuchen. Insbesondere mangelt es an Studien mit instrumentellem Charakter, die konkrete und steuerbare Treiber der Kundenbindung im Vergleich zueinander prüfen. Der vorliegende Beitrag analysiert die Effektivität von Maßnahmen und Aktivitäten des Kundenbindungsmanagements von 341 Unternehmen im Business-to-Business-Bereich. Aus den Ergebnissen lassen sich wichtige Implikationen für die Wissenschaft und die Unternehmenspraxis ableiten.
Undervalued or Overvalued Customers: Capturing Total Customer Engagement Value
Kumar, V.; Aksoy, Lerzan; Donkers, Bas; et al. (2010)
Journal of Service Research
Customers can interact with and create value for firms in a variety of ways. This article proposes that assessing the value of customers based solely upon their transactions with a firm may not be sufficient, and valuing this engagement correctly is crucial in avoiding undervaluation and overvaluation of customers. We propose four components of a customer’s engagement value (CEV) with a firm. The first component is customer lifetime value (the customer’s purchase behavior), the second is customer referral value (as it relates to incentivized referral of new customers), the third is customer influencer value (which includes the customer’s behavior to influence other customers, that is increasing acquisition, retention, and share of wallet through word of mouth of existing customers as well as prospects), and the fourth is customer knowledge value (the value added to the firm by feedback from the customer). CEV provides a comprehensive framework that can ultimately lead to more efficient marketing strategies that enable higher long-term contribution from the customer. Metrics to measure CEV, future research propositions regarding relationships between the four components of CEV are proposed and marketing strategies that can leverage these relationships suggested.
Understanding the quality–quantity conundrum of customer referral programs
Viswanathan, Vijay; Tillmanns, Sebastian; Krafft, Manfred; et al. (2018)
Journal of the Academy of Marketing Science
The Evolution of Marketing Channel Research Domains and Methodologies: An Integrative Review and Future Directions
Krafft, Manfred; Goetz, Oliver; Mantrala, Murali; et al. (2015)
Journal of Retailing
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. This paper is the first that aims to (1) chart how channels research employing each of the three classes of methodologies – conceptual, empirical, microeconomics model-based – has evolved over seven decades along with current trends; (2) review the contributions and shortcomings of research to date using these methodologies; and (3) suggest future research opportunities using these methodologies, separately or in an integrated fashion.
Drivers of private-label purchase behavior across quality tiers and product categories
Noormann, Philipp; Tillmanns, Sebastian (2017)
Journal of Business Economics
Private labels hold a substantial share of consumers’ wallets and their popularity is still growing as they spread into various product categories and quality tiers. To determine the right branding strategy, in terms of offering uniform or different private-label brands across product categories, retailers have to know whether consumers use their private-label experience across product categories and private-label tiers. Therefore, we examine different determinants of consumers’ consideration sets. We apply proneness for certain private-label tiers, product categories purchased, purchase frequency, and variety seeking as internal determinants, which contribute to consumers’ knowledge and experience with private labels. Further, we use consumers’ price consciousness and promotion sensitivity as external determinants, which the retailer can use to influence consumers’ consideration sets in the short run. Our analyses are based on large-scale loyalty program data for a period of 24 months. In particular, we use the first 12 months to derive the determinants of consumers’ share of wallets regarding different private-label quality tiers in the second half of the sample. We conduct our analyses for 12 different product categories and aggregate the results by using meta-analytic techniques. Notably, some determinants show dissimilar effects across product categories (e.g., price consciousness and promotion sensitivity), while others (e.g., private-label proneness) are rather similar. We find that consumers’ general proneness for certain private-labels tiers leads to a propensity to purchase them in a specific category and in adjacent quality tiers. Further, we reveal that product category characteristics moderate the determinants of private-label share.
Customer Win-Back: The Role of Attributions and Perceptions in Customers' Willingness to Return
Pick, Doreén; Thomas, Jacquelyn S.; Tillmanns, Sebastian; et al. (2016)
Journal of the Academy of Marketing Science
Interest in customer reacquisition has increased as firms embrace the concept of customer relationship management. Using survey and transactional data from defected subscribers of a publishing company, we investigate how defected customers evaluate their propensity to return to the company prior to any win-back offer. We introduce a new variable for relationship marketing, general willingness to return (GWR), and show that it is strongly and positively related to the actual return decision and the duration of the restarted relationship. Combining attribution theory elements with existing win-back explanations, which focus on economic, social, and emotional value perceptions, provides a more comprehensive understanding of the factors that influence the GWR to a former relationship. Importantly, we learn that regardless of whose fault it is, if the reasons for the relationship termination can change or are preventable and the firm can control those changes, then the defected customer has a higher general willingness to return to the former relationship. Also, we show that the duration of time absence before relationship revival moderates the impact of GWR on second relationship duration. Furthermore, we demonstrate that satisfaction prior to defection and the length of time absence provide a reasonable basis for distinguishing defected customers who differ in their GWR. By applying our findings, we derive recommendations for firms on how to position marketing communications to recapture defected customers according to their general willingness to return.
Unveiling the Drivers and Barriers of Click & Collect Adoption: Insights from 120 Consumer Interviews
Tillmanns, Sebastian; von Wangenheim, Florian (2024)
The COVID-19 pandemic has accelerated the adoption of Click & Collect services, prompting retailers to adapt to changing consumer preferences. This study explores the factors influencing consumers' decisions to use or not use Click & Collect through a qualitative analysis of 120 interviews with generative artificial intelligence. The findings highlight convenience, cost savings, and product availability as key drivers, while a preference for in-store experiences and the desire to inspect items act as barriers. The pandemic has played a significant role in increasing Click & Collect usage, though some consumers have reverted to previous shopping habits post-lockdown. Industry-specific insights and potential service enhancements are discussed, along with future research directions to advance understanding of this evolving retail model.
Logistic Regression and Discriminant Analysis
Tillmanns, Sebastian; Krafft, Manfred (2022)
Handbook of Market Research
Questions like whether a customer is going to buy a product (purchase vs. non-purchase) or whether a borrower is creditworthy (pay off debt vs. credit default) are typical in business practice and research. From a statistical perspective, these questions are characterized by a dichotomous dependent variable. Traditional regression analyses are not suitable for analyzing these types of problems, because the results that such models produce are generally not dichotomous. Logistic regression and discriminant analysis are approaches using a number of factors to investigate the function of a nominally (e.g., dichotomous) scaled variable. This chapter covers the basic objectives, theoretical model considerations, and assumptions of discriminant analysis and logistic regression. Further, both approaches are applied in an example examining the drivers of sales contests in companies. The chapter ends with a brief comparison of discriminant analysis and logistic regression.

Publications 1 - 10 of 11

Sebastian Tillmanns

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