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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09262024-130340


Tipo di tesi
Tesi di laurea magistrale
Autore
PICCHIANTI, VALERIA
URN
etd-09262024-130340
Titolo
Spatial variable modelling for sales estimation of retail stores
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Prof. Pappalardo, Luca
tutor Dott. Strano, Emanuele
Parole chiave
  • geospatial intelligence
  • retail performance
  • sales estimation
  • spatial modelling
  • untapped sales potential
Data inizio appello
11/10/2024
Consultabilità
Non consultabile
Data di rilascio
11/10/2094
Riassunto
This thesis introduces a geospatial-driven framework to estimate the untapped sales potential of retail stores, moving beyond traditional sellout prediction models. While conventional approaches often rely on historical sales data only, they overlook spatial and environmental variables that may reveal hidden growth opportunities. Current marketing strategies tend to focus on top-performing stores, reinforcing success at the expense of underperforming stores, which often have unexpressed potential.
The proposed approach integrates a diverse range of geospatial and socio-demographic data, including Points of Interest (POIs), mobility patterns, land use data, and additional territorial variables. The core of this research lies in creating descriptive vectors for each retail store, encapsulating its unique spatial context, and estimating its unexpressed sales potential.
The research was conducted using data from Lombardy, Italy, encompassing over 3000 retail stores, with detailed spatial information.
Results demonstrate that many retail stores have potential for growth, with some stores capable of increasing their sales performance by up to +33%.
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