What Does Average Time On Page Mean For My UX?

Supermarkets are really clever in how they position things. Have you ever noticed that essentials like milk, meat and eggs are sometimes placed towards the back of the store? Forcing you to walk through isle after isle, traversing discounts and other items before you get to what you planned on visiting for.

And after all that, you’ll probably end up buying more than you intended. Why does this happen? The BBC and Time magazine say it could be down to a particular reason, increased time in-store.

But it’s not on the physical sale space that benefits from increased visitor time, the same can be said for digital experiences. Time is considered a great indicator of interest and intention to purchase. For example, someone closer to purchasing may spend more time reading copy on your landing page or look at taking next steps through on-page activity. In short, time on a page can be a great evaluator of a potential customer’s interest.

But that’s not the whole story, at least not all the time. Average Time On Page can be a telling factor (in some instances as we’ll see) on a number of UX related health metrics for your website, from interest in your copy to how parts of your funnel are performing.

Read on to find out how ‘Average Time On Page’ fits in as a metric in your UX arsenal.

What is ‘Average Time on Page’?

Average Time On Page is a web analytics metric that records the amount of time spent on a specific web page by visitors and creates an average based on all visits.

What is crucial to remember however is that ‘Average Time On Page’ only covers non-bounces, hence for time to be attributed to this metric, the page will need to have been part of an overall session which included multiple pages AND not be the last page visited. This a commonly missed factor when looking at landing page metrics, causing site owners to panic seeing the dreaded ’00:00:00′ Average Time On Page.

What does ‘Average Time On Page’ mean for  my UX?

Both long and short ‘Average Time On Page’ metrics are not perfect indicators of a good or bad UX on their own. That much is clear looking at ContentSquare’s Digital Analytics Benchmarks report, which states 54 seconds is the average across industries, though this varies by sector and the page type, e.g. blog, home, product etc.

Remembering that Average Time On Page only covers non-bounces and non-exit’s only, this metric isn’t always helpful with determining how good your content is in terms of time on page (this is where screen recording can come in handy, allowing you to create a sample and average from that. Find out more below in our section on analytics you should pair with time on page).

In terms of best use for ‘Average Time On Page’, the metric can excel in determining how well designed your funnel is. As it’s based on traversing the site to different pages, you can inform how long visitors stay at certain points based on your Average Time On Page, helping assign value to stages. For example, you may find that visitors spend more time on the product page ahead of heading towards a conversion goal like filling in a form on a separate page.

If certain pages are taking longer than expected, this metrics opens the door to investigate recordings, other clicks on the page that are attached to analytics, and other events to see if there’s confusion in the funnel or if streamlining is necessary due to drop off prior to conversion stages.

With this in mind, let’s look at the scenarios you could have:

If Average Time On Page is Low

As mentioned, if a page has 00:00:00 but multiple visits, it could indicate that the person has bounced without taking a further action. Teams may then ask why customer are not reading your content, not scrolling down the page, leaving instantly or even timing out (based on inactivity after 30 mins). This can be a red flag, however, it doesn’t paint the full picture in many cases. Imagine someone has visited your FAQs or a blog page via a referral from social media. That FAQ or blog page may not pick up any time at all, even if it’s read cover to cover, if the user then subsequently closes the browser with no other interaction or page visit, though they may leave having fulfilled their objective. That’s not necessarily bad.

If you do have metrics recorded for your visits, low time on page can be a worry, though this is dependent on how crucial the page is to your user journey. If the journey typically starts with the home page, they may quickly navigate away if they know where they need to get to, which is in itself a sign of good UX. Shorter durations are good if they inform you that navigation, content, and layout are all positively received by the visitor. They primarily become an issue on areas like long copy pages or video pages, where it may allude that they are skipping content because they don’t find it relevant or like the format.

If Average Time On Page is High

The longer your customers spend on your site the better right? Not exactly.

Analytics platforms can monitor the time on page, but the metric fails to monitor inactivity. Users could be spending 5 of the 10 minute duration inactive or in another tab, extending your Average Time On Page if they continue their journey later. This raises questions like, are my users confused, is there a clear step to progress to, is my content too long to digest, when really, that may not be entirely representative of what the metric means.

The alternative to that may be that users are genuinely struggling on your pages. This could be because of difficulty finding what they’re looking for, e.g. contact information, demo forms, issues with navigation, or even broken links. This makes high Average Time On Page informative for diagnosing problems on your site, especially considering it’s an average which could mean widespread impact on users, and as a result, your UX.

On a separate note, you should take Average Time On Page across the who site with a pinch of salt. Some pages may be designed to have longer durations (long sales pages) while others may be shorter on purpose (short blog posts), skewing this metric across the board. This is where expectation setting based on the type of page and its content comes in handy, ensuring you can understand the analytics in context.

Analytics to pair with Average Time on Page for more UX insights:

Landing Page: Critical when analysing time on page. Landing page allows you to dive into specific cases of suspicious time on page. As mentioned earlier, bear in mind the content on the page. Video embedded pages may yield higher time on page if users commit to watching the content.

Screen Recording: A long stay on a page is not indicative that the visitor enjoyed the content. To find out exactly what’s going on during each session beyond analytics, you could opt to use screen recording. This means you can monitor engagement in sessions that run through a specific page, see if there’s inactivity or confusion and set out a plan to correct it.

Bounce Rates: If Average Time On Page values are low, checking bounce rates can indicate if this is from users leaving the page without any further interaction or from timing out. This is a backup metric you can use to support why metrics might be low or at 0.

Exit %: Exit % can tell your analytics team if this is a stage people often close the tab or browser on. By pairing this metric with Average Time On Page and even bounce rates, you can see if your on-page UX is causing people to leave and allow it to inform you of problems in your funnel if it’s at a stage that shouldn’t be exited at.

Behaviour Flow: Behaviour Flow allows teams to see how journeys through your website progress, listing the pages they visit, the drop off and where users typically go next. Using this in conjunction with Average Time On Page can help identify the ideal user journey and helps you investigate drop off further.

Conclusion

Average Time On Page can be a telling factor for identifying how customers navigate your site and flow through your funnel, giving you good insights into possible issues and how the site could be designed to create the optimum user experience.

The best time on page varies by industry, but noting your sector and the type of page (and it’s content) before coming to conclusions on whether the metric is good or bad is vital for understanding the data.

Average Time On Page however has drawbacks, with an inability to measure every visit. However, this can be improved by pairing it with other analytics and screen recordings to offer the best picture of your user’s journey.

Useful Resources on Average Time On Page

1. Databox’s 20 Ways To Improve The Average Time On Page For Your Blog Posts
2. HotJar’s Difference Between Session Duration and Average Time 
3. Optinmonster’s What Is Average Time On Page and How To Increase It

To see how other metrics fit into your UX toolkit, check out our separate post in the series on what Bounce Rates mean for your user experience below.

Looking to investigate the impact of your Average Time On Page?

PixelTree offer in-depth UX audits, taking analytics like your Average Time On Page and pairing them with UX best practice to get to the root of your user experience issues.

Check out our UX Audit page for a breakdown of our audit packages.

Need a quick expert opinion? We also offer a FREE no obligation 1 hour UX audit to deliver actionable insights fast.