Tuesday 29th March, Sylvia Häusermann and Dr. Patrick Bachmann will present their research during the PhD Seminar in Quantitative Marketing Research.

Title and Abstract of Sylvia’s talk:

Why You Keep Purchasing From Brands With a Dark Triad Brand Personality Even if It Makes You Feel Bad

Existing research has extensively documented that through anthropomorphizing a brand, brands, just like humans, possess a personality. However, prior research has predominantly focused on positive brand personalities. But since according to Havas’ meaningful brands report (2021) “75% of brands could disappear overnight, and most people wouldn’t care, or would easily find a replacement” (Introduction section, para. 2), it is now more urgent than ever to look at negative brand personalities, which only few prior research has done. One example is Malär et al. (2022) with their research on the Dark Triad brand personality (DTBP), which consists of brand narcissism, Machiavellianism, and psychopathy. We take this conceptualization to dig deeper into the paradox, that even though the Dark Triad is generally perceived as negative, the existence of brands with such a personality implies, that customers do not seem to (fully) avoid brands with a DTBP. Thus, we examine why consumer purchase from DTBP brands. Our work further aims to shed light on potential drawbacks from the consumption of such brands such as lower consumer well-being and less brand support. We address these questions with a series of surveys and experimental studies with real and fictitious brands. Thereby, we aim to provide relevant implications for marketing scholars and marketers.

Keywords: Dark Triad brand personality, moral decoupling, negative self-conscious emotions, brand support

Title and Abstract of Patrick’s talk:

Not on Every Day Your Average Joe: Extending Probabilistic Modeling of Customers’ Spending Behavior
Patrick Bachmann, Markus Meierer, Jeffrey Näf

In retailing and other non-contractual businesses, many customer-centric initiatives focus on three behavioral processes: attrition, purchase, and spending. In contrast to the former two processes, research has given little attention to the latter. To analyze customers’ spending behavior, scholars and marketers usually turn to the Gamma/Gamma model. However, its assumptions limit the ability to capture a wider variety of commonly observed spending patterns. Extending existing modeling efforts, this study presents a generalization of the Gamma/Gamma model that (a) incorporates time-invariant and time-varying contextual factors, (b) accounts for shifted spending patterns, and (c) allows for dependence of consecutive transaction values for individual customers. This novel approach preserves key features of the original model such as a closed-form maximum likelihood expression facilitating a robust, scalable, and efficient implementation. Evaluating data from five retailers illustrates the impact on the out-of-sample predictive performance. Improvements go up to 22% for individual-level and up to 37% for aggregate-level metrics. Complementing the analysis of customer spending as a key metric on its own, the extended Gamma/Gamma model can also be readily used in further marketing applications. For example, newly derived managerial expressions facilitate its combination with latent attrition models and, thus, more accurate customer value predictions.

Keywords: customer relationship management, customer spending, customer valuation, probability models, Gamma/Gamma model, contextual factors