Publicação
Predictive Modelling of Merchandising Sales in a Football Club
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | Albuquerque, Carina Isabel Andrade | |
| dc.contributor.author | Carneiro, Marta Francisco da Cunha Mendes | |
| dc.date.accessioned | 2025-11-19T09:37:48Z | |
| dc.date.available | 2025-11-19T09:37:48Z | |
| dc.date.issued | 2025-10-30 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Data Science for Marketing | pt_PT |
| dc.description.abstract | This project develops a weekly merchandising sales forecasting model for a professional football club with the goals of maximizing order quantity from suppliers, avoiding stockouts, and reducing overstock. Based on the CRISP-DM process, historical sales, performance of the club, and weather information were collected, cleaned, and analysed. The extracted variables were used to depict product launches and promotions,so that the last dataset could be weekly aggregated and employed to train and compare the various forecasting models: SARIMAX, XGBoost, LightGBM, and Random Forest. XGBoost performed better than the other models, exhibiting the following performance, RMSE of 84.221, MAE of 46010.88 and an adjusted R² of 0.846, being superior in detecting non-linear relationships and intricate patterns in the data. This study demonstrates how machine learning methodology can become a major value driver of operational efficiency, enabling inventory management and creation of more strategic marketing campaigns, in addition to maximizing fan experience through access to most desirable products. | pt_PT |
| dc.identifier.tid | 204070880 | |
| dc.identifier.uri | http://hdl.handle.net/10362/191018 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Machine Learning | pt_PT |
| dc.subject | Forecasting Demand | pt_PT |
| dc.subject | Time series | pt_PT |
| dc.subject | ARIMA | pt_PT |
| dc.subject | XGBoost | pt_PT |
| dc.subject | Random Forest | pt_PT |
| dc.subject | LightGBM | pt_PT |
| dc.subject | SDG 8 - Decent work and economic growth | pt_PT |
| dc.subject | SDG 9 - Industry, innovation and infrastructure | pt_PT |
| dc.subject | SDG 12 - Responsible production and consumption | pt_PT |
| dc.subject | SDG 17 - Partnerships for the goals | pt_PT |
| dc.title | Predictive Modelling of Merchandising Sales in a Football Club | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Marketing Analítico, especialização em Data Science for Marketing | pt_PT |