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  • Open Access

    ARTICLE

    Customer Segment Prediction on Retail Transactional Data Using K-Means and Markov Model

    A. S. Harish*, C. Malathy

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 589-600, 2023, DOI:10.32604/iasc.2023.032030

    Abstract Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers. It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities. The volume and volatility of the business makes it one of the prospective fields for analytical study and data modeling. This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting, customer targeting, customized offers, value proposition etc. The segmentation could be on various… More >

  • Open Access

    ARTICLE

    Sales Prediction and Product Recommendation Model Through User Behavior Analytics

    Xian Zhao, Pantea Keikhosrokiani*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3855-3874, 2022, DOI:10.32604/cmc.2022.019750

    Abstract The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down. The general public has responded to call of the government to stay at home. Offline retail stores have been severely affected. Therefore, in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience, this study aims to utilize historical sales data for exploring, building sales prediction and recommendation models. A novel data science life-cycle and process model with Recency, Frequency, and Monetary (RFM) analysis method with the combination of various analytics algorithms are utilized in this study for… More >

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