[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128786-en":3,"doc-seo-128786-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128786,1099523885336,"Violet","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Enhancing Product Recategorization in the Toys Industry - A Comprehensive Approach Integrating Classification Machine Learning Model and Industry Trend Analysis","Business analytics work project focused on retail toys product recategorization in an e-commerce environment. It builds a machine learning classification model to assign toys items into eleven predefined categories, addressing missing coverage for roughly one million unique products outside the standard taxonomy. It also conducts multi-granularity industry trend analysis to capture weekly movements in pricing, availability, selection, and search behavior, using SQL/Python data extraction and data visualization to support actionable decisions and KPI accuracy.","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.  \nENHANCING PRODUCT RECATEGORIZATION IN THE TOYS INDUSTRY: A COMPREHENSIVE APPROACH INTEGRATING CLASSIFICATION MACHINE LEARNING MODEL AND INDUSTRY TREND ANALYSIS  \nAMAIA SALAZAR OCHOA DE  \nOCARIZ  \nWork project carried out under the supervision of:  \nRodrigo Belo  \n11/01/2024  \nAbstract  \nThis 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.  \nKeywords  \n• DRI – Directed Research Internship  \n• KPI – Key Performance Indicator  \n• EAN – European Article Number  \n• ML – Machine Learning  \n• MP – Marketplace  \n• OPS – Order Product Sales  \n• TTM – Trailing Twelve Months  \n• AWS – Amazon Web Services  \nThis work used infrastructure and resources funded by Fundação para a Ciência e a Tecnologia (UID/ECO/00124/2013, UID/ECO/00124/2019 and Social Sciences DataLab, Project 22209), POR Lisboa (LISBOA-01-0145-FEDER-007722 and Social Sciences DataLab, Project 22209) and POR Norte (Social Sciences DataLab, Project 22209).  \n1. Introduction  \nThis thesis presents the culmination of my Directed Research Internship (DRI) undertaken in pursuit of the master's degree in Business Analytics at Nova School of Business and Economics. This internship was conducted at an e-commerce tech company in Madrid’s branch within the Toys Retail Department, where I assumed the role of Product Manager Intern for a duration of 6 months.  \nThe internship consisted of two phases or subprojects namely: (i) toys items classification into product categories with a machine learning model and (ii) toys industry trends analysis through a weekly newsletter.  \nThe challenge that the development of this project aims to tackle consists of addressing the lack of an appropriate categorization model that could recategorize, in an automatic way, the extensive inventory of items in the toys retailing department. This deficiency leads to a consequential issue: the inability to provide precise Key Performance Indicators (KPIs) that reflect the accurate performance of the entire product line within the company.  \n1.1.Objective of the project  \nThe main goal of this project is (i) to correctly categorize items that were not yet in the toy’s main categories, with the aim of tracking more accurately the performance of the distinct categories of the toy’s group line. Due to the standardization of the eleven main categories, around one million unique items fell outside them, and the performance of those was not being properly accounted for. Outside the main eleven categories, there are approximately 2,400 other categories that are deprecated and should be in disuse.  \nOnce achieved this reclassification, the second objective is to (ii) provide the toys team with weekly updates on actionable opportunities related to concrete items, providers, and product categories. This was accomplished through the creation of a newsletter and a report that trackshow the trends in the toys industry are evolving week over week. The focus is on four major  \npillars: pricing, availability, selection, and search trends.  \nThe integration of these two project components will support the team and enhance their negotiating with pro","cbCaigcHWWC468G7","https://ap.wps.com/l/cbCaigcHWWC468G7","pdf",1174394,2,1,35,"English","en",105,"# Introduction\n## Objective of the project\n# Literature review\n## AutoML for structured data\n## E-commerce product categorization via Machine Translation","[{\"question\":\"What problem does the project aim to solve in toys retailing?\",\"answer\":\"It targets the lack of an appropriate automatic recategorization model for the department’s extensive inventory, which prevents accurate KPI tracking across the product line.\"},{\"question\":\"How does the project categorize toys products?\",\"answer\":\"It develops a machine learning model that assigns toys items into eleven predefined categories, enabling recategorization of items previously outside the main taxonomy.\"},{\"question\":\"Which industry trend pillars are analyzed for weekly updates?\",\"answer\":\"The project analyzes pricing, availability, selection, and search trends, delivered through a newsletter and supporting reporting.\"}]","Enhancing Product Recategorization in the Toys Industry - A Comprehensive Approach Integrating Classification Machine Learning Model and Industry Trend Analysis | PDF",1786003437,88,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"enhancing-product-recategorization-in-the-toys-industry-a-comprehensive-approach-integrating-classification-machine-learning-model-and-industry-trend-analysis","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/enhancing-product-recategorization-in-the-toys-industry-a-comprehensive-approach-integrating-classification-machine-learning-model-and-industry-trend-analysis/128786/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-06",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the project aim to solve in toys retailing?","Question",{"text":76,"@type":77},"It targets the lack of an appropriate automatic recategorization model for the department’s extensive inventory, which prevents accurate KPI tracking across the product line.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does the project categorize toys products?",{"text":81,"@type":77},"It develops a machine learning model that assigns toys items into eleven predefined categories, enabling recategorization of items previously outside the main taxonomy.",{"name":83,"@type":74,"acceptedAnswer":84},"Which industry trend pillars are analyzed for weekly updates?",{"text":85,"@type":77},"The project analyzes pricing, availability, selection, and search trends, delivered through a newsletter and supporting reporting.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]