Market Segmentation Analysis and Visualization using K-Mode Clustering Algorithm for E-Commerce Business

Deepali Kamthania, Ashish Pawa, Sirijit Madhavan

Abstract


Now, all business organizations are adopting data driven strategies to generate more profits out of their business. Growing startups are investing a lot of funds in data economy to maximize profits of the business group by developing intelligent tools backed by machine learning and artificial intelligence. The nature of business intelligence (BI) tool depends on factors like business goals, size, model, technology, etc. In this paper, the architecture of BI tool and decision process has been discussed with a focus on market segmentation, based on user behavior geographical distributions. Principal Component Analysis (PCA) followed by k-mode clustering algorithm has been used for segmentation. The proposed toolkit also incorporates interactive visualizations and maps.


Keywords


clustering, market segmentation, data visualization, principal component analysis (PCA), k-mode

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DOI: https://doi.org/10.20532/cit.2018.1003863

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

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