What is stay time? Explanation of definitions and confirmation methods in Google Analytics

When you run an owned media, you may be wondering how long people are staying, not just PVs and sessions. It is not possible to say unconditionally that a long stay per user is good, and a short stay is bad, but it would be better to know the average stay time per page. You can check the length of stay using Google Analytics. However, it cannot be measured accurately, so care must be taken when analyzing.

In this article, we will explain the definition of “stay time” in Google Analytics and how to check it.

Google Analytics

Table of Contents

What is stay time?

What is stay time?

Dwell time is the amount of time a visitor spends on your website. Specifically, it is the time it takes for a user who has visited one website to leave another website or close the browser that is viewing the page.

In Google Analytics, dwell time is expressed as “session time” and “page dwell time”. However, it is not recommended to accept the stay time that can be confirmed by Google Analytics as it is.

This is because the mechanism of staying time measurement of Google Analytics cannot measure accurate time. Why is Google Analytics’ Time Spent mechanism not an accurate metric? I will explain this point from the two types of dwell time measurement methods of Google Analytics.

What is dwell time in Google Analytics?

In Google Analytics, there are two types of indicators that are categorized by dwell time:

  • session time
  • time on page

What is session time

Session time is the total amount of time a visitor spends on your website. In other words, it is the total amount of time spent navigating multiple pages within a single website.

Average session time refers to the average time spent on each website visit (per session).

You can check the average session time for the entire page by going to the “Summary” of the user category in Google Analytics.

If you want to check the average session time by channel, select “Channel” in “All Traffic” in the Attraction category. You can check how much the dwell time differs by inflow channel such as organic traffic, advertisement, and referral.

Also, if you want to check the average session time by page, select “Landing page” in “Site content” in the behavior category.

As mentioned earlier, the average session time does not measure the time spent on the last page viewed. As a result, the numbers measured by Average Session Duration will not be accurate. This is because the length of time a page is viewed before leaving a website has a large impact on the average time.

What is time on page?

Time spent on page is the time spent on each page calculated by the session time on one website. Time spent on a page is measured by the difference between the time the user starts browsing the page and the time the user starts browsing the next page.

For example, let’s say that the time you started browsing the page is “20:00” and the time you started browsing the next page is “20:10”. In this case, the difference in page stay time is “10 minutes”.

The average time spent on a page displayed in Google Analytics is the time measured on average for each page.

You can see the overall page average by going to the overview of the “Users” category in Google Analytics.

Of course, the average page stay time is not measured on the last page visited.

In particular, be careful that the session time and page stay time represented by the average time will deviate from the actual page stay time.

In some cases, the average stay time is 0 seconds

Google Analytics cannot measure the time spent on the last viewed page for each session (time spent on site), so there are cases where the average time spent on the site is 0 seconds.

For example, if a user leaves the website after only one page, the dwell time is measured as 0 seconds.

Based on the above, it is important to understand that the mechanism for measuring the dwell time of Google Analytics will be 0 seconds if the site visitor bounces on the first page .

How is stay time measured?

From here, let’s check how the stay time is measured in Google Analytics with a table.

Table: A

BROWSING START TIME LEAVING TIME CORRESPONDING BROWSING PAGE
20:10 20:14 Article page A
20:14 20:18 Article page B
20:18 20:30 Top page
(leaving after viewing the page)

Table A shows that a user who visits one website moves 3 pages and finally leaves. In fact, the exact time spent on the site is from the start of browsing the site from “article page A” to the end of moving to the top page and leaving.

However, in the mechanism of Google Analytics, the stay time “12 minutes” of the last viewed top page is not measured. Therefore, even if the actual total time spent is “20 minutes”, Google Analytics will measure “8 minutes”.

Based on the mechanism of Google Analytics, the dwell time is calculated from Table A as follows.

[Calculation formula for average time spent on page (Table A)]
(Article A page 4 minutes + Article B page 4 minutes) ÷ 2 pages = Average time spent on page 4 minutes

So what is the result of the average time on page in Table B below?

Table: B

BROWSING START TIME LEAVING TIME CORRESPONDING BROWSING PAGE
20:10 20:14 Article page A
20:14 20:24 Article page B
20:18 20:30 Top page
(leaving after viewing the page)

The page viewing order and the actual time spent (20 minutes) remained the same, the time spent on the second page increased, and the time spent on the last viewed page decreased. The dwell time calculated for the case in Table B is:

[Calculation formula for average time spent on page (Table B)]
(Article A page 4 minutes + Article B page 10 minutes) ÷ 2 pages = Average time spent on page 7 minutes

The formula in Table B resulted in a 3 minute difference in average time on page even though the actual session time was the same. It’s important to understand that these discrepancies in averages do happen in Google Analytics.

Average session time is the average number of page dwell times calculated for each session. Average session time is calculated differently than average time on page. Please refer to Table C below.

Table: C

TIME SPENT IN SESSION TOTAL TIME SPENT IN ALL SESSIONS AVERAGE SESSION TIME
Session A 8 minutes 12 minutes 4 minutes
session B 4 minutes
Session C 0 seconds

From the table above, we can calculate the average session time as follows:

[Average session time calculation formula]
All sessions (A: 8 minutes + B: 4 minutes + C: 0 seconds) Total stay time = 12 minutes Total stay time for
all sessions 12 minutes ÷ Number of sessions 3 = Average session time 4 minutes

In the case of average session time, the calculation method is different from average page stay time in that sessions of 0 seconds are also measured. If there are many 0 second sessions in all sessions, it will greatly affect the average session time. In other words, if there are many sessions with an average session time of 0 seconds, the measurement result will be less than the actual stay time.

See comparisons and transitions with multiple pages rather than the number of stay times themselves

Since there is a discrepancy in the average stay time due to the mechanism of Google Analytics, rather than the measured value itself, looking at the comparison of multiple pages and the transition of a single page, “Which page tends to be read frequently? It would be rational to use it by going to get information that can be used as a reference for improvement measures, such as “Is there a change in the time spent on this page after improving the contents of this page?”

When analyzing dwell time, keep the purpose of your website in mind.

Relationship between dwell time and UX

Relationship between dwell time and UX

In improving a website, it is important to bring it closer to the optimal UX (user experience) for your target users rather than focusing on “extending” the length of stay.

Depending on the purpose of the site, the way of perceiving the time spent on site changes

Consider what the ideal UX looks like for a real estate portal site.

The purpose of real estate portals is to allow users to compare multiple properties and find properties that meet their criteria. As a conversion point, it is easy to understand the application for viewing from the property page.

When thinking about the ideal UX of a real estate portal, how should we perceive the length of stay? How should each indicator be interpreted?

“I want to make a decision after comparing as many properties as possible”, “The first property I browsed just happened to match the conditions”, etc. Since each user has different tendencies until they apply for a preview, the length of time they stay Longer is better and shorter is better. What is more important is whether or not you find a property that you like and jump to the application page (click-through rate of the preview application button). )

But what about corporate recruiting sites? If you post a lot of content for applicants such as company service introductions, welfare programs, employee interviews, etc., the company should be thinking, “I want you to apply based on that information as much as possible.” . If you apply after touching various information, you can reduce the probability of mismatches, so it will be a great advantage for both the company side and the applicant side. In these cases, you should check how many pages they read and how long they stayed.

Think of it as one indicator for improving the user experience

In this article, I explained two points: that the dwell time in Google Analytics is only a reference value and should not be followed strictly, and that the way of perceiving the dwell time should be changed depending on the purpose.

Every metric, not just dwell time, should be looked at to improve the user experience. Of course, it is important to have a firm grasp of each data in Google Analytics, but it is also important to try to understand what kind of needs they have by actually communicating with them.

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