Web Analytics
Web Analytics (WA) refers to the assessment, compilation, review, and reporting of web-based data with the aim of better understanding and improving web use (Sleeper, Consolvo, & Staddon, 2014). For instance, we can use WA to track the number of visitors, where they came from, what section they visited, how much time they spent on the web, how far users navigated, where their visits ended, and where they went next (Clifton, 2012). Web analytics' strength lies in its ability to deliver unbiased results, overcoming the shortage of experts, being low cost, it does not get tired, and it evades inconsistency results from experts (Dingli and Misfud, 2011). Moreover, WA collects data from the user’s unobtrusiveness. By using WA, Researchers are able to gather data from users without interfering with their responses, i.e., in a non-reactive manner. As opposed to the obtrusive approach, where the participant is fully conscious that they are being observed, the participant's viewpoints and reactions will be affected (the Hawthorne effect). Studies have shown that the Hawthorne effect (HE) affects participants' responses and behavior in studies (McCarney et al., 2007). With WA, data collection happens invisibly to the users on the background, thus avoiding the Hawthorne effect (Lalmas et al., 2014).