Visitor site retention time and page stay time of the implementation of the program _ related skills

Site stay Time (Times on site, hereinafter referred to as TS) and page stay Time (Times on page, hereinafter referred to as TP) is an important indicator of user experience analysis and flow quality control. But very few people know how the average time of a site visit (Average times on site) is calculated. Whether using competitive intelligence analysis tools or some kind of web analytics solution (data obtained from the weblog or JavaScript tags in the Web analytics solution, few people know how the average time of the site visit is calculated).

So, to write this article is to explainhow TP and TS are calculated .

Case 1:

Someone has visited your website's homepage, and your web analytics tool has started to count 1 sessions for this visitor. The visitor then browses to the other two pages and then leaves your site (either by closing the browser or by typing a different URL in the address bar, or by clicking on a link on your site that links to other sites ...). For simplicity, we take this process as a session.

What we want to know is as follows:

Tp = User's stay on one page (time spent on a page);

Ts = Total user stay on the entire site (time spent on the website).

Suppose this session starts from 9 o'clock:

At present, all web analytics tools are able to pinpoint the time that a page access request takes place, but that's not enough to explain how much TP and TS are, because we need more information:

Users do not bounce (jump), click on the homepage of a link to jump to the page 2, the current web analytics tool can also get the page 2 open time, but also know that the same user, so can easily calculate first photocopy page TP:

Tp (Home) = 9:05–9:00 = 5 minutes.

Some of the content on page 2 attracted the user, so the user continued to visit Page 3

From the image above, see:

Tp (page 2) = 9:30–9:05 = 25 minutes.

The user exits from Page 3 and ends the session:

So, how long does this user stay on page 3? The problem arises because none of the Web analytics tools currently have a "timestamp" that crawls the user away from Page 3 o'clock, so that we cannot calculate how long the user has stayed on page 3! So:

Tp (Page 3) = 0 minutes.

Because the request time for the next page is not available! Web analytics Tools do not know how long the user stays on the last page of the session, which is true for most web analytics tools.

Let's use the figure below to represent the duration of the site Analysis tool statistics for each page:

Tp (Home) = 5 minutes

Tp (page 2) = 25 minutes

Tp (Page 3) = 0 minutes

So what's the duration of the session's visit to the entire site?

Ts = 30 minutes

Is it reasonable?

I think it may not be reasonable because you don't know how much time visitors spend on the last page, so the time statistics that the Web Analytics tool gives you are generally less than the amount of time the user actually spends on the site.

Case 2:

How do I calculate time on site and times on page when browsing the Web using a Tabbed (tab page) browser?

Firefox has earned a reputation for its multiple-label page browsing, but this is a hassle for computing time on page and time on site. When the user opens a link to the same Web site on another tab page, that is, when the same site is browsed through two tabs, what does time on page and on site calculate?

This situation is confusing the web analytics tool to calculate the time.

The image below is a popular user browsing site scene where we can understand the impact of multiple tabbed page browsing ...

A user comes to the front page of the map, and then opens a link on the page in a new tab, at which point the home page occupies a tab page, and clicking on the link's newly opened page 4 occupies another tab page. This time, the user browsing page 4 did not close the page 4, back to the Home page tab to continue browsing the home page. In the process of browsing the homepage, the user clicked on another link on the first page, and jumped to the page 2, but no new tab is open. Then, the user switches to Page 4 tab, click the link to enter page 5, on page 5, close the current tab. Then again, the user clicks on page 2 to link to Page 3, of course, or the same tab. Finally, this tab is closed on page 3, and the session ends.

How do I calculate time on site in this case? Different Web analytics tools have two ways of calculating this "multiple tab" browsing behavior.

Mode one:

Web Analytics tool will be the above tab browsing situation by the different tab, each record, that is, the following calculation occurs:

Statistical results output: 2 access procedures (that is, 2 sessions), each session corresponds to a tab.

Session1 (Home tab in the above image):

Tp (Home) = 5 minutes

Tp (page 2) = 25 minutes

Tp (Page 3) = 0 minutes

Ts (entire access length of the same tab) = 30 minutes

Session2 (tab in page 4 above):

Tp (page 4) = 6 minutes

Tp (page 5) = 0 minutes

Ts (new Open tab's entire access length) = 6 minutes

In this case: 2 session,1 UV (Unique Visitor) will be recorded in the Web Analytics tool report.

Mode two:

Some Web analytics tools combine this multiple tab into the same access process to eliminate the effects of multiple tab tabs (tab pages).

Or the example above, but we're changing the way we do it--the following diagram shows the same process, and different colors represent different tabs.

Statistical results output: An access procedure (1 sessions), which includes two tab tabs during the access process. The entire access process is organized into the previous diagram through a "timestamp".

This session:

Tp (Home) = 1 minutes

Tp (page 4) = 4 minutes

Tp (page 2) = 2 minutes

Tp (page 5) = 23 minutes

Tp (Page 3) = 0 minutes

Ts = 30 minutes

Which kind of statistical method do you think is more reasonable and prefer?

Be sure to ask your web Analytics service provider which one of the two ways to compute the time and access process for multiple tab (tabbed pages) browsing.

Now more and more people are using the tab to browse, so the choice of ways will have a great impact on the final data output of your site analysis-there is no doubt that the final data of the two ways of statistics will be very obvious differences.

Solution:

Gets the page (tab) off time (the page closes either by closing the browser or tab, by typing a different URL in the address bar, or by clicking on a link to another site on your site ...). ）

by tribal State (Beijing) Science and Technology Limited liability company independent research and development of the latest User experience visual analysis tool "State analysis", get the page close time, through the calculation of the page open and close the time difference, you can easily and accurately get the page stay and session time.

This session:

Tp (Home) = 5 minutes

Tp (page 2) = 25 minutes

Tp (Page 3) = 1 minutes

Tp (page 4) = 6 minutes

Tp (page 5) = 3 minutes

Ts = 31 minutes

Page stay time is accurate acquisition, but the meaning of how much? Next article we will discuss in detail, please pay attention!