2019
DOI: 10.1016/j.dss.2019.01.007
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Family profile mining in retailing

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Cited by 9 publications
(5 citation statements)
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“…Due to the mobility of customers who may visit different stores located in different areas, it is difficult to collect individual customers' data for segmentation attributes. Using store based transaction data is much cheaper, more effective, less time consuming and more powerful (Lian, Xu, and Zhang 2019). In the study of Kolyshkina et al (2010) the authors considered just drink items while this study considered all of the items sold in a grocery store.…”
Section: Discussionmentioning
confidence: 99%
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“…Due to the mobility of customers who may visit different stores located in different areas, it is difficult to collect individual customers' data for segmentation attributes. Using store based transaction data is much cheaper, more effective, less time consuming and more powerful (Lian, Xu, and Zhang 2019). In the study of Kolyshkina et al (2010) the authors considered just drink items while this study considered all of the items sold in a grocery store.…”
Section: Discussionmentioning
confidence: 99%
“…Thus, inferring customer profiles from transaction data becomes an attractive alternative since transaction data provide a full view of the market (Lian, Xu, and Zhang 2019). Second, the idea of "a customer's transaction data can reflect purchasing behavior of that customer" is extended to the idea of "similar grocery stores can be grouped into the same cluster by detecting similar purchasing behavior of their customers" (Liao and Chang 2016;Weng and Huang 2015).…”
Section: Development Of a New Store Segmentation Approachmentioning
confidence: 99%
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“…On a different perspective, Balakrishnan et al (2018) have worked on a co-clustering algorithm to determine efficient product recommendations for groups of buyers with similar purchasing patterns. Other researchers suggested that family profiling would help retailers reach specific customers with product recommendations more efficiently (Lian et al , 2019).…”
Section: Discussionmentioning
confidence: 99%
“…These must be aggregated, classified and stored in a customer data platform [60]. The profiles then serve for databased CRM to derive tailored offers and communication [37] based on the individual information such as demographic data or psychographic data. Building a database should be seen as a profitable investment, as customer information significantly increases the efficiency of marketing activities [17,43,57] and allows companies to generate a higher return on investment [33].…”
Section: Introductionmentioning
confidence: 99%