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http://hdl.handle.net/10362/186008| Title: | Enhancing product recategorization in the toys industry: a comprehensive approach integrating classification machine learning model and industry trend analysis |
| Author: | Ocariz, Amaia Jinrong Salazar Ochoa de |
| Advisor: | Belo, Rodrigo |
| Keywords: | DRI – Directed Research Internship KPI – Key Performance Indicator EAN – European Article Number ML – Machine Learning MP – Marketplace OPS – Order Product Sales TTM – Trailing Twelve Months AWS – Amazon Web Services |
| Defense Date: | 24-Jan-2025 |
| Abstract: | This project encompasses a complete business analysis of the retail toys industry in a renowned company of this sector, which was conducted,first,with the development of a machine learning model which served to correctly categorize toys products into eleven predefined categories and, secondly, by performing a deep analysis at different granularity levels regarding the exanimated toys items, which served to analyse the most important pillars trends regarding the retailing business model, these being: pricing trends, availability trends, selection analysis and search trends. This industry analysis was accomplished by the usage of different automatized data pulling techniques such as complex SQL queries and python programs, in addition to the usage of data visualization methods. |
| URI: | http://hdl.handle.net/10362/186008 |
| Designation: | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics |
| Appears in Collections: | NSBE: Nova SBE - MA Dissertations |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 54155_WP_AmaiaSalazarOchoadeOcariz.pdf | 1,15 MB | Adobe PDF | View/Open |
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