Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report - Responsible AI and Analytics for an Ethical and Inclusive Digitized Society
Conference Papers Year : 2021

Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report

Abstract

The goal of this experience report is to study and advance our understanding on visit and shopper segmentation in retail. Current segmentation studies mainly use customers as unit of analysis to identify shopper segments and mine patterns in their behaviors. Another stream of studies utilizes shopper baskets or visits to perform basket/visit segmentation and elicit shopping patterns. However, given the fact that we live in the era of personalization focusing solely on visits leads on neglecting the shopper. On the other hand, focusing solely on shoppers and their behavior over time, leads on losing his/her daily purchasing behavior. In this study we combine shopper and visit segmentation and we apply data mining to identify purchase patterns using data from an e-commerce grocery retailer.
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hal-03648137 , version 1 (21-04-2022)

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Anastasia Griva, Denis Dennehy. Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report. 20th Conference on e-Business, e-Services and e-Society (I3E), Sep 2021, Galway, Ireland. pp.545-551, ⟨10.1007/978-3-030-85447-8_45⟩. ⟨hal-03648137⟩
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