## 3 Results
### Eye-Tracking Results  
The experiment was conducted using the Tobii Pro Nano device and the iMotions Lab software (version 9.4) [11]. iMotions provides the option to define areas of interest (APIs) based on the object we want to study. In our case, the defined areas of interest included the advertisements. Thus, we could extract information concerning these specific areas. The AOIs in our research were renamed based on the type of advertisement for better representation in the statistical analysis of the data. The following metrics were used for analyzing the effectiveness of each online ad technique as an attractive visual stimulus (measured values per metric are depicted in Table 5):  
* Time To First Fixation: Average time that passed until the first fixation was detected inside an active AOI (relative to AOI onset). It indicates the amount of time that it takes a respondent (or all respondents on average) to look at a specific AOI from stimulus onset. * Fixation Duration: Average duration of all fixations/visits detected inside an active AOI. A visit is defined as the time interval between the first fixation on the active AOI and the end of the last fixation within the same active AOI where there have been no fixations outside the AOI. * Revisit Count: Average of how often the respondents looked back at the AOI after the first dwell. * Dwell Time: Average of how long the respondents fixated on the AOI in relation to the time during which the AOI was active. * Fixation count: Average amount of fixations/visits detected inside an active area Of interest (AOI). Each of the advertisements displayed on our experiment's website was fully functional, meaning the user, by clicking on each link, navigated to a separate functional page. Thus, we extracted the data in such a way to examine where and for how long users looked when they entered the pages containing the advertisements. The first advertisement was placed on the homepage and was of the right rail type. The data from the eye-tracking device showed that 48 out of 51 individuals saw the advertisement. Next, the nonmodal advertisement was seen by 33 out of the 51 individuals. Regarding the modal advertisement, 48 out of 51 individuals focused their attention on it. Additionally, 47 out of the 51 individuals looked at the intraconent without content reorganization advertisement, and 46 out of the 51 looked at the banner. For the intraconent with content reorganization advertisement, the results showed that 46 individuals looked at the advertisement, and finally, although there was movement in the animated right rail, only 20 individuals focused their attention on it. The above results emerged from the respondent count metric, which presented the number of participants who looked at a specific area of interest, which in our case was the advertisement on each page. The following table presents the results that emerged from the tracker software after analyzing the experimental process for each type of advertisement we placed on the website. The first metric presented in the table is Time to First Fixation. Thus, we see that for the first advertisement, which was the right rail advertisement, the average time to first fixation was 3172.73 ms. Converting this time to seconds, we observe that it took participants just 3.172 s to focus their gaze on this particular type of advertisement. The results for the metric in seconds are presented below for better understanding. The next advertisement was the nonmodal, for which it took participants an average of 2.097 s to look at. This was followed by the modal advertisement with a time of 0.41 s. For the intraconent without content reorganization, the TTFF was 1.124 s; for the banner advertisement, the TTFF was 1.427 s; for the intraconent with content reorganization, it was 0.566 s; and finally, for the animated right rail, this time was 3.247 s. According to this metric, the advertisements that initially attracted users' attention were the modal and intraconent with content reorganization forms.