Objective

Purpose

For customers, shopping through online platforms brings a quick, comfortable experience with no time limit, no restrictions on space or geographical distance, and diversification of choices. However, the current online shopping experience in general is lacking and fail to satisfy customers. Customers cannot feel or examine the product in advance, they cannot receive advice or interaction from sales staff and they lack intuitive interactions while choosing and sorting purchases like traditional shopping. This remains a concerning limitation for online shopping platforms.

For sellers, e-commerce platforms are limited in their ability to provide store personalization and to let sellers know about key intel, like customer behavior, the level of interaction between customers and the store, personalized business forecasts for the store.

Influence and significance of the topic

Today, with the expansion of digitized business activities, data is a valuable source of information that needs to be exploited for both customers and businesses. The application of Machine Learning and GenAI to the e-commerce platform not only brings a smart and convenient experience to buyers but also brings long-term optimal business efficiency to businesses big or small. This is an important step to promote sustainable development of online shopping, so it can have an innovative approach to optimizing business activities and stay in trend of the times by using Machine Learning and GenAI.

The expected result of the project is a smart system capable of personalizing user experience, supporting users in the purchasing process and supporting sellers in business management. The results will provide strong evidence of Machine Learning - GenAI's effectiveness and enhance their value in online business.