Recommender System for Improving Customer Loyalty

Recommender System for Improving Customer Loyalty

por Katarzyna Tarnowska , Zbigniew W. Raś , Lynn Daniel
Aún sin calificaciones
Romance Science & Technology Business & Economics
Formato Kindle
Páginas 182
Idioma Inglés
Publicado Jan 1, 2019
Editorial Springer
Edición 1st ed. 2020
ISBN-10 3030134385
ISBN-13 9783030134389
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Descripción

In a rapidly evolving marketplace, retaining customer loyalty has become a paramount challenge for businesses. This insightful exploration delves into the complex world of recommender systems, showcasing their significant role in enhancing customer engagement and retention. Through a collection of research and practical insights, the authors illuminate how personalized recommendations can transform the customer experience and foster long-lasting relationships with brands.

The text synthesizes theoretical foundations with real-world applications, offering a comprehensive overview of the mechanics behind effective recommender systems. By drawing on cutting-edge technologies and analytics, the authors highlight how companies can leverage data to anticipate customer needs and preferences, thereby increasing satisfaction and loyalty.

Moreover, the book emphasizes the importance of trust and transparency in recommendation processes, addressing potential pitfalls and ethical considerations. It serves as a vital resource for researchers, practitioners, and anyone interested in understanding the intricate dynamics between technology, consumer behavior, and loyalty in today’s digital landscape.

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