Length of stay (Internet)
The average length of stay (also: visit duration, viewing time, visibility time) in the World Wide Web is the length of time that a visitor stays on a certain website or an entire website . As part of web analytics, the measurement of the length of stay is intended to provide the website operator with information about how intensively the website is of interest to the user and how user-friendly it is. For this purpose, the times between individual accesses to the website are measured during a visit. With the browsers available today (as of 2016) it is not possible to reliably measure the time spent on a website.
Over the course of time, the average length of stay can be used to determine whether the visitors stay longer or shorter and shorter on average.
Although statistics are available from almost every web hosting provider , which are supposed to provide information about the length of stay on a website, these are unreliable. In order to measure the length of stay, a statistics program decides when a visit is over. Since this is done differently depending on the software and user behavior, there are large differences in the individual measurements.
Some statistical programs also provide information about the length of time spent on individual websites . According to Nielsen NetRatings, this is around 40 seconds on average, but fluctuates greatly depending on the type of information presented. Depending on the content and function of a website, short or long dwell times are interpreted as positive.
Technical difficulty
When measuring the length of stay, websites are accessed , i. H. the server knows when it was accessed, but it cannot measure when the user has stopped viewing the page.
There are two approaches to reduce the problem: The first approach is to determine when the user is retrieving a new page from the server and using the difference between the times of retrieval as the dwell time. This method is highly inadequate, since the user can in the meantime devote himself to other websites or activities; it also fails completely when a visitor "leaves" the website. Another approach uses client- side script solutions such as JavaScript to measure the length of stay directly on the user's computer and periodically transfer it to the server. (The script cannot measure the total time and then transfer it because the JavaScript execution is aborted when the page is exited.) The latter method also has disadvantages: On the one hand, it means a significantly higher consumption of resources (computing power and bandwidth) for both the server and the Client. On the other hand, it is also unreliable, for example if the script does not work in all common browsers or if a visitor leaves a website open in the browser while he is devoting himself to completely different things.
Individual evidence
- ↑ a b c Claudia Hienerth: Key figure model for evaluating the success of e-commerce: Analysis using the example of a multi-channel retailer , Springer-Verlag, 2010, p. 74
- ↑ Marco Hassler: Web Analytics: Evaluate metrics, understand visitor behavior, optimize website , mitp Verlag , 2015, p. 231