Gaining insights into omnichannel usage behaviour of corporate customers in the German pharmacy supplies market: a cluster analysis approach
Purpose With growing access to technologies, the customer journey becomes more omnichannel every day, transforming shoppers’ expectations, interests and behaviours. Demands for omnichannel services have not spared the corporate sector. This study aims to prove the existence of diverse business-to-business customer segments according to varying channel behaviours and identify their characterising traits. Design/methodology/approach Drawing on an exclusive dataset of 616 German pharmacy supply firm business customers, this article explores customers’ channel behaviours in an omnichannel context. Cluster analysis is employed to identify segments, followed by Multivariate Analysis of Variance to reveal their key traits. Findings Five customer segments with varying channel behaviours are detected, most of which show omnichannel tendencies. Constructs like advice orientation or perceived service quality were found to significantly differentiate the segments. Research limitations/implications Though this article provides novel insights into the omnichannel behaviour of business-to-business customers, additional research is needed to validate the applicability of results beyond pharmaceutical packaging. Practical implications The differentiation of clusters entails varying implications on how managers can address customers based on their preferred channel choice and specific characteristics. Moving sales towards digital channels in an omnichannel system may be beneficial and can free up sales representatives’ time to focus on segments with higher consultation needs or higher profitability. Originality/value This research paper addresses a gap in omnichannel customer segmentation literature by investigating, first, B2B customers and, second, the healthcare sector.
Institutions
- Philipps University of Marburg (DE)
Publication Details
- Journal
- Journal of Business and Industrial Marketing
- Published
- 2025-10-08
- DOI
- https://doi.org/10.1108/jbim-12-2024-0950
- Primary Topic
- Spatial and Panel Data Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00