This paper introduces the utilization of data originated in the web user ocular movement to improve the methodology for identifying Website Keyobjects that was designed by Velasquez and Dujovne through the use of eye tracking tools. Given a website, this methodology takes as input the request register (Web log) of the website, the pages that compose it and the interest of users in the web objects of each page, which is quantified using a survey. Subsequently, the data is transformed and preprocessed before finally applying Web mining algorithms that allow the extraction of the Website Keyobjects. In this paper, a novel application of the eye tracking technology is proposed, in order to dispense with the survey, that is to say, using a more precise tool to achieve an improvement in the classification of the Website Keyobjects. It was concluded that eye tracking technology is useful and accurate when it comes to knowing what a user looks at and therefore, what attracts their attention the most. Finally, it was established that there is an improvement of between 15% and 16% when using the information generated by the eye tracker.