User segmentation via interpretable user representation and relative similarity-based segmentation method
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User segmentation via interpretable user representation and relative similarity‑based segmentation method Younghoon Lee1 · Sungzoon Cho2 Received: 12 June 2019 / Accepted: 27 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract User segmentation is an essential element of marketing and product development that considers customers’ needs and recognizes the heterogeneity of those needs. In a key study of smartphone user segmentation, Lee et al. analyzed app usage sequencing using seq2seq architecture. However, despite achieving meaningful results, their approach could not provide a robust interpretation of user segmentation because the seq2seq architecture represented users in a continuous vector space generated from a black box model. In this paper, we propose an interpretable user representation method that combines app clustering with a novel segmentation method. The user representation clusters characteristically similar apps into common clusters, with each user represented by their frequencies of app use within their respective clusters. Two novel techniques are also applied to normalize the value of user representation based on the relative degrees of importance between app clusters and the membership strengths of individual apps within a cluster. Furthermore, to address the limitations of existing segmentation methods, in which the most closely located users are assigned to specific clusters, the proposed method segments represented users using a novel segmentation approach based on relative similarity. Experimental results demonstrate that the proposed method provides an intuitive interpretation for each user’s representation and segmentation results. Furthermore, we effectively show the similarities between the results produced by our method and ground truth and demonstrate that it outperforms existing user segmentation methods. Keywords User segmentation · User representation · App clustering · Relative similarity · Modularity detection · Louvain method
1 Introduction User segmentation is an essential element of product development that considers the customer’s needs while recognizing the heterogeneity of those needs. Kotler reported that a marketer can use segmentation to appropriately create a Communicated by T. Yao. * Sungzoon Cho [email protected] Younghoon Lee [email protected] 1
Department of Industrial Engineering, Seoul National University of Science and Technology, 232, Gongneung‑ro, Nowon‑gu, Seoul 01811, Korea
Department of Industrial Engineering and Institute for Industrial Systems Innovation, Seoul National University, 1 Gwanak‑ro, Gwanak‑gu, Seoul 08826, Korea
2
more fine-tuned product for a target segment, enabling their company to provide better distribution and communication channels to the target segment [18]. With user segmentation, product developers can develop differentiated and personalized products for different segments and marketing personnel can create segmented advertisements and marketing communications for those
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