Demoulin, NathalieGamero Jorge, Christian Anthony2022-07-152022-07-152020https://hdl.handle.net/20.500.12640/3036Global consumption trends and technological disruption is creating the path towards an omnichannel approach in food B2C selling. Food companies have seen an unprecedented evolution in this context, that is challenging their marketing strategies. This thesis tackles this problem by developing a segmentation study in France, employing Latent Class Analysis, based on the use of multiple touchpoints across the food purchase process, aiming to identify customer profiles, channel allocation, and psychographic characteristics related to food consumption. Three segments were identified: Early Omnichannel Adopters, Curious Conservatives, and Uninterested Traditional shoppers. The findings reveal key differences in their adoption of online and mobile touchpoints across the purchase stages, in their expertise purchasing food online, and the impact of the COVID-19 pandemic in channel allocation. A Multinomial logistic regression was then performed to determine psychodemographic differences between the segments and allowing to characterize their food-related lifestyles. The insights developed in this research confirms the utility of LCA analysis to segment customers considering different food purchase phases and multiple touchpoints, using the most recent programming language software, and integrating specific covariates relevant to food shoppers. Food marketers can find valuable to implement a similar approach to reinvent strategies.application/pdfenginfo:eu-repo/semantics/openAccessIndustria alimentariaAlimentosComercio electrónicoSegmentación del mercadoComportamiento del consumidorEstrategias de mercadeoinfo:eu-repo/semantics/masterThesishttps://purl.org/pe-repo/ocde/ford#5.02.04