This thesis investigates the integration of AI-driven web scraping tools into the field of user experience (UX) research, with a focus on enhancing cultural insights and refining brand storytelling in cross-cultural design contexts. Using the "Food Map Project" from the Italian kitchen brand Val Cucina as a case study, this research explores the potential of AI to analyze large volumes of user-generated content across diverse digital platforms. The goal is to uncover valuable data on consumer behavior, preferences, and cultural perceptions, which can inform design strategies aimed at creating products that resonate more deeply with users. The methodology is multi-faceted, combining a comprehensive literature review, an examination of existing AI-driven web scraping tools, and the application of Benchmarking and User Studies that leverage web scraping techniques to derive actionable insights. The research begins with an in-depth investigation of the most widely used AI-driven web scraping tools available on the market, providing a summary of practical experiences and a detailed usability analysis. Following this, AI tools such as Browse AI and AIScraper were selected to conduct large-scale data scraping aligned with specific research questions. This approach revealed significant opportunities to enhance the user experience design by incorporating more refined brand storytelling that integrates cultural narratives, ultimately improving the emotional and cultural relevance of the brand's offerings. The results indicate that AI can greatly reduce research costs, expedite qualitative research, and offer broader, more nuanced cross-cultural insights that traditional research methods often fail to capture. By analyzing the cultural storytelling of established brands like Smeg, the study provides actionable recommendations for Val Cucina to strengthen its brand image and improve the user experience. This is achieved by embedding more profound Italian cultural elements into the brand's digital content, product offerings, and marketing strategies. Despite these advantages, the study also addresses several challenges, including issues of data consistency, privacy concerns, and the balancing act between AI automation and maintaining a human-centered design approach. In conclusion, this research offers a thorough analysis of how AI-driven web scraping tools can be effectively applied in UX research, proposing an AI Web Scraping Methodology that can guide future researchers and designers in leveraging these technologies. The study emphasizes the transformative potential of artificial intelligence in reshaping user experience research, urging designers to not only view AI tools as supportive automation tools but as strategic partners that can foster cultural resonance, enhance emotional connections, and drive user engagement across diverse markets.
Questa tesi indaga l’integrazione di strumenti di web scraping basati sull’intelligenza artificiale (AI) nella ricerca sull’esperienza utente (UX), con particolare attenzione al potenziamento degli insight culturali e al rafforzamento della narrazione del brand in contesti di progettazione interculturale. Prendendo come caso di studio il “Food Map Project” del marchio italiano di cucine Val Cucina, la ricerca esplora il potenziale dell’AI nell’analizzare grandi volumi di contenuti generati dagli utenti su diverse piattaforme digitali. L’obiettivo è far emergere dati significativi su comportamenti, preferenze e percezioni culturali dei consumatori, in grado di orientare strategie di design volte a creare prodotti che risuonino più profondamente con gli utenti. La metodologia è articolata e combina una rassegna esaustiva della letteratura, un esame degli strumenti esistenti di web scraping guidati dall’AI e l’applicazione di attività di benchmarking e studi con gli utenti (User Studies) che impiegano tecniche di web scraping per ricavare insight azionabili. La ricerca si apre con un’indagine approfondita dei principali strumenti di web scraping basati sull’AI disponibili sul mercato, offrendo una sintesi delle esperienze d’uso e un’analisi dettagliata della loro usabilità. Successivamente, sono stati selezionati strumenti di AI come Browse AI e AIScraper per effettuare attività di scraping su larga scala allineate a specifici quesiti di ricerca. Questo approccio ha messo in luce importanti opportunità per migliorare il design dell’esperienza utente attraverso una narrazione del brand più raffinata e integrata con narrazioni culturali, aumentando in ultima analisi la rilevanza emotiva e culturale dell’offerta del marchio. I risultati indicano che l’AI può ridurre sensibilmente i costi di ricerca, accelerare le indagini qualitative e offrire insight interculturali più ampi e sfumati che i metodi tradizionali spesso non colgono. Analizzando la narrazione culturale di marchi affermati come Smeg, lo studio fornisce raccomandazioni operative per Val Cucina al fine di rafforzarne l’immagine di marca e migliorare l’esperienza utente. Ciò avviene attraverso l’integrazione di elementi culturali italiani più profondi nei contenuti digitali del marchio, nell’offerta di prodotto e nelle strategie di marketing. Nonostante tali vantaggi, lo studio affronta anche diverse sfide, tra cui problemi di coerenza dei dati, questioni di privacy e il delicato equilibrio tra automazione basata sull’AI e mantenimento di un approccio progettuale centrato sulla persona. In conclusione, la ricerca offre un’analisi approfondita delle modalità con cui gli strumenti di web scraping basati sull’AI possono essere applicati efficacemente alla ricerca UX, proponendo una metodologia di AI Web Scraping in grado di guidare futuri ricercatori e designer nell’impiego di tali tecnologie. Lo studio sottolinea il potenziale trasformativo dell’intelligenza artificiale nel ridefinire la ricerca sull’esperienza utente, invitando i designer a considerare gli strumenti di AI non solo come supporti di automazione, ma come partner strategici in grado di favorire risonanza culturale, rafforzare le connessioni emotive e stimolare il coinvolgimento degli utenti in mercati eterogenei.
AI-driven design research : optimization of brand culture and user experience of an italian kitchen brand in the U.S. market
Ran, Yaxin
2024/2025
Abstract
This thesis investigates the integration of AI-driven web scraping tools into the field of user experience (UX) research, with a focus on enhancing cultural insights and refining brand storytelling in cross-cultural design contexts. Using the "Food Map Project" from the Italian kitchen brand Val Cucina as a case study, this research explores the potential of AI to analyze large volumes of user-generated content across diverse digital platforms. The goal is to uncover valuable data on consumer behavior, preferences, and cultural perceptions, which can inform design strategies aimed at creating products that resonate more deeply with users. The methodology is multi-faceted, combining a comprehensive literature review, an examination of existing AI-driven web scraping tools, and the application of Benchmarking and User Studies that leverage web scraping techniques to derive actionable insights. The research begins with an in-depth investigation of the most widely used AI-driven web scraping tools available on the market, providing a summary of practical experiences and a detailed usability analysis. Following this, AI tools such as Browse AI and AIScraper were selected to conduct large-scale data scraping aligned with specific research questions. This approach revealed significant opportunities to enhance the user experience design by incorporating more refined brand storytelling that integrates cultural narratives, ultimately improving the emotional and cultural relevance of the brand's offerings. The results indicate that AI can greatly reduce research costs, expedite qualitative research, and offer broader, more nuanced cross-cultural insights that traditional research methods often fail to capture. By analyzing the cultural storytelling of established brands like Smeg, the study provides actionable recommendations for Val Cucina to strengthen its brand image and improve the user experience. This is achieved by embedding more profound Italian cultural elements into the brand's digital content, product offerings, and marketing strategies. Despite these advantages, the study also addresses several challenges, including issues of data consistency, privacy concerns, and the balancing act between AI automation and maintaining a human-centered design approach. In conclusion, this research offers a thorough analysis of how AI-driven web scraping tools can be effectively applied in UX research, proposing an AI Web Scraping Methodology that can guide future researchers and designers in leveraging these technologies. The study emphasizes the transformative potential of artificial intelligence in reshaping user experience research, urging designers to not only view AI tools as supportive automation tools but as strategic partners that can foster cultural resonance, enhance emotional connections, and drive user engagement across diverse markets.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/242940