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Novel next-group recommendation approach based on sequential market basket information

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Abstract

A market basket is a set of items included in a retail assortment that a customer buys on a shopping trip. The purpose of market basket analysis is to persuade a customer to spend more money through upselling or cross-selling. Most recommendation systems only suggest a single next-item or the top n items that a customer is most likely to buy. A company might succeed in convincing a customer to spend more money to increase sales revenue if a recommendation system can suggest the next or top n groups of items that customers are likely to buy according to the items in their basket. Based on the similarity upper approximation clustering, Borda majority count and PrefixSpan algorithm, this paper proposes a novel next-group recommendation approach according to sequential market basket information. Compared with the previous methods, the proposed approach can provide next-group instead of next-item recommendation, which may create more opportunities for customers to increase their spending.

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Acknowledgements

This work was supported by the Ministry of Science and Technology of the Republic of China (Grant Number: MOST 108-2410-H-239-011-MY3).

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  1. Department of Information Management, National United University, 1, Lienda, Miaoli, 36003, Taiwan, ROC

    Li-Ching Ma

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Ma, LC. Novel next-group recommendation approach based on sequential market basket information. Electron Commer Res 23, 2399–2418 (2023). https://doi.org/10.1007/s10660-022-09543-x

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