Designing Personalized Coffee Experiences in Modern E-commerce for Enhanced User Engagement and Sales

Abstract

The growing demand for personalized user experiences in e-commerce has driven companies to explore behaviour-based design strategies to increase user engagement, trust, and conversions. This research was conducted to investigate how personalization techniques can be implemented in a coffee webshop to enhance user experience and improve sales performance. The research focuses on the design of features such as product recommendations, interactive quizzes, filtering systems, and storytelling elements. The scope is limited to the digital layer of the webshop and excludes backend development, logistics, or broader marketing strategy.

The theoretical framework includes theories from behavioural science, including the Fogg Be-haviour Model, Flow Theory, Nudge Theory, and the Elaboration Likelihood Model. A mixed-methods research approach was applied, consisting of user surveys (n=239), seven interviews, and five prototype testing. The study was implemented over several phases: research, prototype design, user testing, and final evaluation.

Results demonstrated that well-implemented personalization features led to a 20% increase in engagement rate and a 10.5% increase in purchase intent. Dynamic filters, context-aware suggestions, and interactive quizzes were particularly effective in improving user satisfaction. Ethical design considerations, including transparency, preference control, and value-based recommendations, were also found to influence user trust and loyalty. Although challenges such as filter complexity and the “cold start” problem were identified, the use of feedback loops and adaptive design addressed these limitations. The research concludes that behaviourally informed personalization strategies can transform coffee webshops into emotionally engaging and commercially scalable platforms.