AI-Driven Customer Personalization in E-Commerce

Maksat Temirkhan

Bakalářská práce

Abstract:

The primary objective of the thesis "AI-Driven Customer Personalization in E-Commerce" is to explore how artificial intelligence (AI) can enhance the online shopping experience by tailoring product recommendations based on customer shopping behavior. Specifically, the study aims to: 1. Analyze customer purchasing behavior using AI techniques to understand key shopping patterns. 2. Enhance product recommendation accuracy by applying collaborative filtering, content-based filtering, and hybrid approaches. 3. Develop and test a user-friendly recommendation interface with usability testing and A/B testing.

Keywords

E-commerce, Machine learning, Usability testing, Customer behavior analysis, AI-driven personalization, Recommendation system, Collaborative filtering, Content-based filtering, Hybrid models, A/B testing, User experience improvement, Advanced algorithms, Data-driven marketing, Online retail, Streamlit interface

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 26. 3. 2025

Obhajoba závěrečné práce

• Vedoucí: Ing. Jakub Konopásek, Ph.D.
• Oponent: Martin Čejka, Ing.

Česká zemědělská univerzita v Praze

Provozně ekonomická fakulta

Bakalářský studijní program:
Informatics