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Analyzing Web Search Queries of Before and After Purchase on e-Commerce Site

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Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration (ICADL 2023)

Abstract

In this study, we investigated how Web search queries change before and after purchasing a product. We focused on the Web searchers who purchased cameras from an e-commerce site. First, we manually classified the words that characteristically appear during pre-purchase and post-purchase searches with cameras. From the manual classification, we found 14 intents. The intents include model number, evaluation, shipping, and accessory, etc. Based on these classified intents, we then analyzed when the words in each intent were used in queries before/after the purchase. Our analyses revealed that the users narrowed the search space with respect to the product as the user nears purchase.

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Notes

  1. 1.

    https://kakaku.com/.

  2. 2.

    Due to the space limitation, we only report the results related to users who issued five queries. We observed a similar trend with respect to users who issued six queries.

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Acknowledgment

This work was supported in part by JSPS KAKENHI Grant Numbers JP21H03774, JP21H03775, JP22H03905.

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Correspondence to Takehiro Yamamoto .

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kawada, Y., Yamamoto, T., Ohshima, H., Yanagida, Y., Kato, M.P., Fujita, S. (2023). Analyzing Web Search Queries of Before and After Purchase on e-Commerce Site. In: Goh, D.H., Chen, SJ., Tuarob, S. (eds) Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. ICADL 2023. Lecture Notes in Computer Science, vol 14457. Springer, Singapore. https://doi.org/10.1007/978-981-99-8085-7_16

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  • DOI: https://doi.org/10.1007/978-981-99-8085-7_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8084-0

  • Online ISBN: 978-981-99-8085-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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