Web site analysis average site stay time hidden trap

 

learned the concepts of PV, UV, Visit and so on, and knew how many visitors came to the site, and the next key indicator was "average site stay."".

The

index because it appears to be a very easy to understand the metrics (not that visitors in the browse this website when you spent much time, so many managers) especially other non professional sector managers may have a special love of the clock: visitors spend more time means our site is high viscosity on our site, our web site for visitors to provide content and services more valuable, we transformed visitors more opportunity value. These views do not sound like a big mistake at first, but there are many hidden pitfalls in the "average site stay".

what is the average site stay time,

?

when a visitor sends the first request to the Web server, a session is started for the visitor. From this point on, each request will be recorded in response to a request time during the client’s browsing of the site. For example:

click 1:index.html (time: 12:01)

click 2:member.html (time: 12:02)

click 3:product.html (time: 12:04)

then, usually the Web analysis tool calculates the time spent by a visitor on a page by calculating the difference between the time mark between a page and the next page. In the above example, the user spends 1 minutes (12:01 – 12:02) on the home page (index.html), and spends 2 minutes (-12:04 member.html) on the member page. Then on the product page (product.html) on the amount of time spent? Because the user leaves the website from this page, we do not know the user specific departure time, may be just open this page will be a phone call away from the computer, it may be the page too difficult to read for a long time did not lead to the user see directly shut down. As a result, the Web analysis tool typically defines the time spent by visitors on this page as 0 minutes.

that’s a big problem, and you’ll find a very large percentage of the pages in the web that visitors spend nearly 0 seconds. Take my blog, or a lot of news site pages, most of the blog are the most content directly on the home page, so most readers read the article content has not in-depth comments or replies, so this time they left.

at this point, the cup appears. In the Web analysis tool, this situation can only be counted as 0>