AI Chatbots in the FMCG Industry: A Strategic Analysis of Consumer–Brand Interaction for Dove in Europe

Búvár Anna Mária (2025) AI Chatbots in the FMCG Industry: A Strategic Analysis of Consumer–Brand Interaction for Dove in Europe. ['eprint_fieldopt_faculty_mük' not defined].

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Absztrakt (kivonat)

This thesis explores the strategic feasibility of introducing an AI-powered chatbot for Unilever’s Dove brand in the European fast-moving consumer goods (FMCG) market to strengthen consumer–brand relationships. The research combines secondary analysis of industry trends and theoretical frameworks—such as the Technology Acceptance Model and Diffusion of Innovation—with primary data from expert interviews and a consumer survey conducted in Hungary and Germany. Findings reveal that AI-driven personalization is increasingly critical in FMCG marketing, offering opportunities to overcome retail limitations and enhance consumer engagement. Competitor benchmarking against L’Oréal’s Beauty Genius highlights the need for broader product scope and interactive features. Survey results indicate high consumer familiarity with AI tools, strong interest in personalized recommendations, and generational differences in trust and adoption. While technical feasibility is supported by Unilever’s existing AI infrastructure, challenges include portfolio adaptation and compliance with EU regulations. The study concludes that a phased rollout targeting tech-savvy female consumers aged 18–34 in urban areas is strategically viable. Recommendations emphasize transparent data practices, intuitive design, and integration across digital touchpoints. This research contributes to academic discourse on AI adoption in FMCG and offers actionable insights for industry implementation.

Intézmény

Budapesti Gazdasági Egyetem

Kar

['eprint_fieldopt_faculty_mük' not defined]

Tudományterület/tudományág

NEM RÉSZLETEZETT

Szak

Kereskedelem és marketing

Mű típusa:	diplomadolgozat (NEM RÉSZLETEZETT)
Kulcsszavak:	AI, artificial intelligence, Dove, fmcg, marketing
SWORD Depositor:	User Archive
Felhasználói azonosító szám (ID):	User Archive
Rekord készítés dátuma:	2026. Júl. 09. 11:48
Utolsó módosítás:	2026. Júl. 09. 11:48

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