Methodology for Collecting Behavioral and Search Preferences for the Purpose of Subsequently Adapting the Recommended Site Content

Abstract

This diploma thesis deals with the analysis of possible solutions to record customer behaviour on a website and the implementation of a solution to process and visualize data according to behavioural patterns. The theoretical part focuses on the description of the most popular analytical tools to gather individual inputs and their comparison in the field of technical background, price and overall usability. The practical part utilizes the information gathered from the theoretical part. Informa- tion gathered using Google Analytics was analysed and inserted into an internal database. Based on gathered information, the operations are created to process customers’ behavioural patterns. If the customer is recognized, it analyses its previous behaviour on the website and determines recommended products. If the customer is not recognized, the functionality, given the time pe- riod, generates the general overview of customers’ behaviour. According to that functionality, the products and product segments for the recommendation are provided. Finally, all of the resulting information is presented on a web application interface, which is built on modern technologies and designed to provide possible future scalability. The resulting web application can then serve the marketing specialists or business owners to make business decisions.