ANALYSIS SYSTEM OF UKRAINIAN CONSUMER PREFERENCES WITH ARTIFICIAL INTELLIGENCE ELEMENTS AND AN INTEGRATED PERSONAL ASSISTANT

Abstract

The article discusses a system for analyzing the preferences of Ukrainian consumers, which uses elements of artificial intelligence and an integrated personal assistant to improve the personalization process in e-commerce. The main functional and non-functional requirements for such a system are defined, ensuring it provides users with an intuitive interface, fast processing of requests, and effective product recommendation personalization. An important feature of the system is the use of the GPT-4o-mini language model to create an integrated personal assistant capable of recognizing user needs and suggesting relevant products based on their preferences and previous purchases.

The development process of the system included two main stages: creating a data analysis system for buyers and developing a personal assistant. A dataset was used for analyzing consumer preferences, including parameters such as age, gender, product category, purchase quantity, unit price, payment method, and other characteristics. Using this data, several graphs were built to reflect consumer behavior trends, which allows for more accurate predictions of future purchases.

At the same time, the system was equipped with the ability to predict future purchases based on neural networks, enabling the prediction of upcoming purchases using machine learning algorithms. The development of this part of the system ensured prediction accuracy and minimized losses during the model training phase. The created neural network showed effectiveness in predicting user behavior, contributing to an enhanced level of personalization and ease of shopping for each user.

The article also analyzes existing solutions in the field of artificial intelligence and personalized recommendation systems used in e-commerce. This analysis helps to identify the strengths and weaknesses of such systems and find ways to improve them for implementation in the Ukrainian market. Furthermore, the proposed solutions combine advanced technologies and user-friendliness, ensuring the system’s successful adaptation to the needs of Ukrainian consumers.