Advancing eCommerce monitoring tools with AI: Development of a visual tracking system of the customer journey

The rise of AI has revolutionized eCommerce, creating a demand for innovative tools to monitor and understand customer journeys. This thesis introduces a cutting-edge software solution that leverages Computer Vision and Natural Language Processing to analyze user interactions through session recordings. By learning on user-side renderings, the software overcomes the variability of website structures, offering universal compatibility and a direct view into the customer journey without the need for manually rewatching session recordings. This approach enhances existing monitoring tools, enabling businesses to proactively identify and address barriers, thereby improving user experiences and protecting revenue in an increasingly competitive digital landscape.