Uppsats

AI-Driven Personalization and Customer Loyalty in Swedish E-Commerce - Exploring the Effectiveness of AI as a Strategic CRM Practice

Master-uppsats

Göteborgs universitet/Graduate School

Publicerad: 2025-08-05

Språk: Engelska

Sammanfattning

The digital landscape is evolving rapidly, where Artificial Intelligence (AI) emerges as a key driver in the development of technological applications aiming to facilitate personalized content. This technological shift not only fosters the adoption of more innovative approaches, but also fundamentally redefines the ways in which organizations engage with customers. This thesis investigates how personalization driven by AI impacts customer loyalty, also addressing challenges associated with its implementation. With the purpose of exploring how different industries within the Swedish e-commerce value chain perceive the relationship between AI-driven personalization and customer loyalty, a multiple case study has been conducted. Through interviews with industry professionals from ten large companies operating in the Swedish e-commerce value chain, the study provides a comprehensive analysis that contextualizes the phenomenon within specific sector and market dynamics. The empirical findings reveal that there is no definite positive relationship between AI-driven personalization and customer loyalty. Concerns regarding inadequate personalization, transparency, and effectively scaling AI strategies, present challenges affecting organization’s ability to increase customer loyalty through personalization efforts. Though the lasting effectiveness of customer loyalty is challenged by these concerns, AI-driven personalization still holds potential in increasing loyalty through highly accurate personalized content that exceeds customer expectations. Through the adoption of a customer-centric approach, which prioritizes relevance, openness, and value-creation, AI-driven personalization could realize this potential.

Information

Författare
Edberg, Axelina
Lärosäte / institution
Göteborgs universitet/Graduate School
Publiceringsdatum
2025-08-05
Uppsatstyp
Master-uppsats
Språk
Engelska

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