## 2 Assumptions and Methodology  
The objective of our research was to compare the efficiency of horizontal and vertical recommending interface layouts with regard to attracting customer interest, from the perspective of user experience and business goals, basing only on implicit data collected for a few major e-commerce sites. Users are most interested in the main editorial content of a website, yet changing visual aspects of the recommendations in order to attract as much user attention as possible may well influence user's interest in offered products and achievement of business goals. Determining user's interest can be accomplished by asking them explicitly and in more detail through questionnaires or by asking them to rate products on a simple scale consisting of five stars. Unfortunately, asking questions in this way can disturb natural behavior while browsing the website and it is perceived as an unwanted obligation [27; 28; 29]. As an alternative to asking users explicitly, their preferences can be inferred implicitly by observing users' interactions with the website. These solutions allow the studied subjects to concentrate only on the main task, without extra cognitive load and the necessary willingness to explicitly rate or write reviews about displayed products and recommendations [30; 31]. Eye tracking may be utilized because eye movements tend to be connected with the cognitive process [32; 33]. Therefore, one approach is to depend on data from an eye tracker to determine web user attention, interest, and time spent on a certain area of a website, which may serve as indicators of attractiveness [34; 35; 36]. Eye tracking can also provide evidence data about cognitive process during performing various tasks e.g., debugging code and correcting errors [37] or efficiency in learning a new programming technology or language [38]. Another technique for implicitly monitoring user behavior on websitesis programmed solutions such as scripts or browser extensions that allow the logging of events which result from interactions with the webpage on the client's side. Thanks to this method, it is possible to discreetly observe user behavior without an additional cognitive burden [39] or the need for special equipment such as an eye-tracker. An e-commerce customer preference monitoring (ECPM) behavior-tracking tool was created to gather a spectrum of e-customer activity data [3]. Our monitoring tool has been programmed in the form of an extension of Mozilla Firefox and its installation is as simple as any other extension. The core monitoring code was developed in a way that allows for external use on any website. ECPM allows for the monitoring of human-computer interactions through the use of a DOM (document object model), which represents an HTML document as nodes and objects in the object oriented manner. When using a DOM of a HTML webpage and JavaScript language, ECPM registers various event handlers on objects in a page. Our tool silently collects data about viewed product pages together with user interactions. Parameters denoting physical page attributes, content attributes and recommendation interface attributes are registered during those interactions. Numerous parameters related to the recommendation interfaces include the times the cursor is located in recommendation areas, their physical size, and registered product interest. As shown by other studies the motion of the mouse cursor is correlated with eye motion and, thus, user interest [18; 40; 41; 42], and a number of behavior-related parameters can be deduced, similar to previous studies [43; 44]. It has been shown that mouse and keystroke tracking can definitely be used as a lower-quality yet even-less-intrusive alternative to gaze-tracking which can only be performed during a controlled study requiring additional equipment, its calibration, and supervision of a research worker.