Good Practice for Product Management Decision-Making: Using Amazon’s Dataset and ChatGPT
This study examines how Chat Generative Pre-trained Transformer (ChatGPT) can be effectively utilised as a good practice to analyse Amazon reviews within the creative and cultural industry category of Design, particularly Arts, Crafts & Sewing. By focusing on specific products and reviews ext...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Editura ASE
2025-05-01
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| Series: | Amfiteatru Economic |
| Subjects: | |
| Online Access: | https://www.amfiteatrueconomic.ro/temp/Article_3429.pdf |
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| Summary: | This study examines how Chat Generative Pre-trained Transformer (ChatGPT) can be
effectively utilised as a good practice to analyse Amazon reviews within the creative and
cultural industry category of Design, particularly Arts, Crafts & Sewing. By focusing on
specific products and reviews extracted from a dataset containing over 800,000 products and
nearly nine million reviews, ChatGPT identified common themes and customer issues such
as software problems and product reliability. When we compared ChatGPT’s results with
those from manual data reviews, we found that ChatGPT was adept at identifying main topics
but sometimes missed detailed insights or altered the original reviews when providing
examples. This indicates that while ChatGPT can quickly highlight important areas for
product managers, it should be used in conjunction with human analysis to achieve a
comprehensive understanding. Nonetheless, the results demonstrate that when considering
group creativity, ChatGPT can be a valuable member. |
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| ISSN: | 1582-9146 2247-9104 |