The use of traditional business metrics vs AI: machine learning-the Ferragamo case
Landolfi, Stefano (A.A. 2024/2025) The use of traditional business metrics vs AI: machine learning-the Ferragamo case. Tesi di Laurea in Statistics for marketing, Luiss Guido Carli, relatore Francesco Salate Santone, pp. 148. [Master's Degree Thesis]
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Abstract/Index
Overview and reference context. Salvatore Ferragamo: company profile. The role of merchandise and planning. AI in fashion luxury and why it could prove important. Introduction to artificial intelligence in the context of fashion luxury. Problem analysis in fashion luxury. Market analysis and specific studies on the consumer. Data driven progress. The need being addressed: decision-making complexity and predictive opportunity in SKU distribution. Data description. Dataset description: structure, variables and preliminary choices. Data preprocessing and cleaning: initial issues found in the dataset. Predictive model. Introduction to the post-cleaning exploratory phase. Poisson regression model: preliminary analysis and diagnostics. Simulation on fictitious SKUs: a predictive model validation exercise. Final application on real Ferragamo data: Poisson prediction and binary classification of handbag SKUs. Context: towards a data-driven strategy in SKU selection.
References
Bibliografia: pp. 89-92.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Marketing (LM-77) |
| Chair: | Statistics for marketing |
| Thesis Supervisor: | Salate Santone, Francesco |
| Thesis Co-Supervisor: | Costabile, Michele |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 17 Mar 2026 10:50 |
| Last Modified: | 17 Mar 2026 10:50 |
| URI: | https://tesi.luiss.it/id/eprint/45124 |
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