This book focuses on the personalisation of the user interface in e-commerce based on collected data on customer behaviour. While product recommendation systems are widely used for this purpose today, they do not allow for a comprehensive adaptation of the layout to different user groups. The proposed approach is based on the conclusion that since e-commerce customers are different, the user interface should also be different. To make this possible, several components need to be combined, which together allow the design of the online shop to be automatically or expertly adapted to the customer's choices and behaviour. It presents and discusses a framework that allows data to be collected, processed and used to optimise UI variants for generated customer segments. The proposed approach has been verified in practice and further developed on this basis, so that the reader is presented with a solution that is not riddled with 'baby age' problems, and the limitations and challenges identified are described and commented on in detail. Typical e-commerce systems currently have a single UI for all customers. The implementation of multi-variant UIs therefore represents an opportunity for companies to create a marketing advantage by addressing the personalisation trends in e-commerce.

The book is intended for those responsible for developing e-commerce platform and user interfaces for web-based systems, as well as individuals interested in practical applications of machine learning in business.

Autorentext

Adam Wasilewski has obtained a PhD in Economics in the field of management from the Wroclaw University of Science and Technology, Poland, where he has been working for 25 years. His research focuses on management information systems, business process management, and e-commerce systems. Since 2012, he has been involved in projects as an integration solution architect and R&D project manager at an e-commerce software house.