Many companies’ sales teams are still buried under Excel spreadsheets and a maze of disconnected tools, wasting time, losing potential customers, and making it hard to base decisions on solid, reliable data. Smart Prospect aims to bring everything together in a single workspace that integrates the entire lead-generation and company-assessment cycle. This thesis documents the first concrete step toward that vision, developed in three key phases. First, a web-scraping module analyzes a company’s website and returns technical and visual assessments (SEO indicators, performance metrics, DOM quality, and a screenshot preview), allowing the salesperson to gauge the prospect’s digital maturity at a glance. Next comes the identification of decision makers: enriched external data let the system pinpoint key figures (CEO, CMO, IT managers, and others) and supply verified contact details, drastically shortening engagement times. Finally, a profiling module gathers and cross-references the main economic and organizational indicators (revenue, cost structure, headcount, ATECO code, and more), producing a detailed snapshot of the prospect that equips the sales team to make truly data-driven decisions. Together, these three phases mark an important step toward Smart Prospect’s ultimate goal: transforming a fragmented sales process into a single, continuous, and efficient workflow.
Il reparto vendite di molte aziende è ancora sommerso da fogli Excel e da una miriade di tool scollegati: così si spreca tempo, si perdono potenziali clienti e diventa difficile prendere decisioni su dati solidi e affidabili. Smart Prospect vuole riunire tutto in un unico spazio di lavoro in cui l’intero ciclo di lead generation e valutazione aziendale è integrato. Questa tesi documenta il primo passo concreto verso tale visione, articolato in tre fasi chiave. In primo luogo, attraverso Web scraping, il sistema analizza il sito di un’azienda e restituisce valutazioni tecniche e visive: indicatori SEO, performance, qualità del DOM e anteprima screenshot, così che il venditore colga subito la maturità digitale di un potenziale cliente. A questa analisi fa seguito l’individuazione dei decision maker: grazie all’arricchimento dati da fonti esterne, il sistema intercetta subito le figure chiave (CEO, CMO, responsabili IT...) e fornisce recapiti verificati, riducendo drasticamente i tempi di ingaggio. Infine, un modulo di profilazione raccoglie e incrocia i principali indicatori economico-aziendali, tra cui fatturato, costi vari sostenuti, numero dipendenti... Ne nasce una fotografia dettagliata del prospect che fornisce al reparto vendite una base solida per decisioni davvero data-driven. Insieme, queste tre fasi costituiscono un importante passo concreto verso l'obiettivo finale di Smart Prospect: trasformare un processo di vendita frammentato in un flusso unico, continuo ed efficiente.
Smart Prospect: Web Scraping, Individuazione Decision Maker e Indicatori Finanziari per la Valutazione Aziendale
SANTI, ANDREA
2024/2025
Abstract
Many companies’ sales teams are still buried under Excel spreadsheets and a maze of disconnected tools, wasting time, losing potential customers, and making it hard to base decisions on solid, reliable data. Smart Prospect aims to bring everything together in a single workspace that integrates the entire lead-generation and company-assessment cycle. This thesis documents the first concrete step toward that vision, developed in three key phases. First, a web-scraping module analyzes a company’s website and returns technical and visual assessments (SEO indicators, performance metrics, DOM quality, and a screenshot preview), allowing the salesperson to gauge the prospect’s digital maturity at a glance. Next comes the identification of decision makers: enriched external data let the system pinpoint key figures (CEO, CMO, IT managers, and others) and supply verified contact details, drastically shortening engagement times. Finally, a profiling module gathers and cross-references the main economic and organizational indicators (revenue, cost structure, headcount, ATECO code, and more), producing a detailed snapshot of the prospect that equips the sales team to make truly data-driven decisions. Together, these three phases mark an important step toward Smart Prospect’s ultimate goal: transforming a fragmented sales process into a single, continuous, and efficient workflow.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/93204