Updating the Theory of Industrial Marketing: Industrial Marketing as a Bayesian Process of Belief-updating

Carsten Lund Pedersen*, Thomas Ritter*

*Corresponding author for this work

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While industrial marketing often comprises a process that, at least in principle, mirrors Bayesian reasoning, the notion of Bayesian inference has predominantly been utilized in the marketing field as a methodological tool. This article suggests that the practice of industrial marketing itself should be (re)conceptualized as a Bayesian process of belief-updating that entails a continuous cognitive cycle of formulation of hypotheses (i.e., beliefs about the market) and the subsequent updating of those hypotheses through exposure to market evidence (e.g., data from the market). A Bayesian perspective on industrial marketing enables a synthesis of a broad body of extant research as well as a focus on the interconnection between executives' market beliefs (theories-in-use) and belief-updating (assessing the validity of those beliefs in view of market evidence). A view of industrial marketing as a Bayesian process not only enhances our understanding in general but also fosters insights into market learning in uncertain and volatile situations. A Bayesian conceptualization suggests a new understanding of industrial marketing that also informs a typology of marketing approaches. We outline opportunities for developing a better understanding of the Bayesian foundation of industrial marketing.
Original languageEnglish
JournalIndustrial Marketing Management
Pages (from-to)403-420
Number of pages18
Publication statusPublished - Apr 2022


  • Bayesian inference
  • Theories-in-use
  • Industrial marketing
  • Market responsiveness
  • Market orientation
  • Analytics
  • Learning

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