
Martin Walthert
Chief Marketing Officer at Galaxus
Marketing Thought Leader Award
Martin Walthert has succeeded in aligning Digitec Galaxus’ marketing with the new situation of informed, competent and “defensible” customers. The company relies on an editorial content team that produces content instead of advertising. The majority of the marketing measures are developed in-house and only partially by external agencies. The company also succeeds in combining image and product communication in an exemplary manner. In doing so, they use the findings of behavioral economics, such as gamification and status, for their work. Martin Walthert studied journalism at the University of Zurich. Already during his studies, in addition to other part-time jobs, he helped out at Digitec, where he already practiced an early form of content marketing by sending out newsletters. Directly after his studies, he joined Digitec, where he still works. He is responsible for the advertising campaigns of Digitec and Galaxus, which are consistently popular in Switzerland. Digitec stands out for its advertising with positive and especially also negative customer reviews, and Galaxus has been advertising for years with funny parodies of various advertising genres.
Rigour & Relevance Research Award
For their article “The Role of Time-Varying Contextual Factors in Latent Attrition Models
for Customer Base Analysis”, published in 2021 in the highly renowned scientific journal “Marketing Science”, Dr. Patrick Bachmann, Prof. Dr. Markus Meierer, and Jeffrey Näf, jointly received the Rigour & Relevance Research Award 2022.

Dr. Patrick Bachmann
ETH Zurich

Prof. Dr. Markus Meierer
University of Geneva

Jeffrey Näf
ETH Zurich

Niña Sayson
University of Neuchâtel
Best Doctoral Presentation Award
In her presentation, Niña Sayson emphasized how businesses and individuals increasingly rely on artificial intelligence (AI) when making both small and large-scale decisions. However, there is added difficulty in trusting its decisions as it is a “black box”, meaning that how it got to its decision is unexplainable or cannot be understood.
Initial findings show that transparency indeed leads to higher usage intention, particularly when consumers were rejected by the AI. Usage intention further increases as more information is provided explaining the decision or outcome. However, providing more information brings little added benefit, indicating that more-is-not-better with transparency.