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    Title: Keywords Effectiveness in Textile Product Sales Performance: A Case Study of the Shopee Website
    Authors: 謝佩璇
    Hsieh, Pei-Hsuan;Phong, Ambrose
    Contributors: 資訊系
    Keywords: Keyword Search;Sales Performance;e-Commerce;Beautiful Soup;TF-IDF (Term Frequency-Inverse Document Frequency)
    Date: 2024-06
    Issue Date: 2025-03-12 11:17:22 (UTC+8)
    Abstract: Online shoppers usually conduct product searches using one or more keywords, in addition to applying filters, to find their favorite products on an e-commerce platform. However, it remains uncertain which combinations of keywords are effective for online sellers to include in their titles to ensure that their listed products match buyers’ search keywords and appear in the search results. The purpose of this study is to identify the keyword strategies that sellers use when listing their products on an e-commerce platform. The study further explores how sales performance can be improved by employing specific strategies for keyword combinations. In this study, web scraping techniques were employed twice to obtain two 30-day product sales datasets from Shopee. One dataset was validated by analyzing the other. The Term Frequency-Inverse Document Frequency statistical method, in conjunction with the Beautiful Soup library, was used for data analysis. The results show that there is indeed a higher sales volume when using the 10 most frequently used keywords in sellers’ product titles. In both datasets, these top 10 keywords consistently appearing in product titles include two textile products (i.e., T-shirt and underpants) and seven adjectives (i.e., breathable, cooling, customized, group, rayon, in stock, Taiwan). The results reveal that sellers can increase their sales by strategically combining these high-frequency keywords. By identifying these keywords, textile product sellers can better optimize their product titles, increase visibility, and attract more interest from potential buyers.
    Relation: International Conference on Human-Computer Interaction, HCI International, pp.176-186
    Data Type: conference
    DOI link: https://doi.org/10.1007/978-3-031-61315-9_12
    DOI: 10.1007/978-3-031-61315-9_12
    Appears in Collections:[Department of Computer Science ] Proceedings

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