Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThis study presents a framework for segmenting Food Delivery Application (FDA) customers based on
psychographic and behavioral variables as an alternative to existing segmentation. Customer segments
are proposed by applying clustering methods to primary data from an electronic survey. Psychographic
and behavioral constructs are formulated as hypotheses based on existing literature, and then
evaluated as segmentation variables regarding their discriminatory power for customer segmentation.
Detected relevant variables are used in the application of clustering techniques to find adequate
boundaries within customer groupings for segmentation purposes. Characterization of customer
segments is performed and enriched with implications of findings in FDA marketing strategies. This
paper contributes to theory by providing new findings on segmentation that are relevant for an online
context. In addition, it contributes to practice by detailing implications of customer segments in an
online sales strategy, allowing marketing managers and FDA businesses to capitalize knowledge in their
conversion funnel designs
