Before assessing user engagement on your hotel website, it’s critical to ensure they can access your content.
NB: This is an article from Direct Your Bookings
The correlation between a user opening a website and viewing its content seems straightforward, yet discrepancies frequently occur. The primary reason for this gap? Page load time. If a page takes too long to load, users often leave before the page fully loads – a phenomenon known as ‘bouncing’.
Subscribe to our weekly newsletter and stay up to date
The Importance of Tracking Page Load Time
Google Analytics 4 (GA4) automatically collects an event called page_view
when a user tries to open a new page. Conversely, the page_load_time
event is not automatic and requires customization.
Tracking page_load_time
provides insights beyond the average load time for a page – it indicates the total event count between people who try to open a page versus those who wait until it’s fully loaded.
Discrepancies in Page Load Time: A Case Study
Two hotel pages with the page_load_time
event installed serve as case studies.
On the first page, the total count of page_view
and page_load_time
events is nearly identical, suggesting an efficiently optimized, fast-loading website.
The other page, however, presents a stark contrast.
The page_load_time
events are 20% fewer than the page_view
events, implying that over 20% of users didn’t wait for the page to fully load before leaving, causing lost opportunities.
Tracking Events with Google Tag Manager
Using Google Tag Manager, you can monitor how these two events – page_view
and page_load_time
– occur.
During a page load, events occur in a specific order. A ‘container loaded’ event signifies the page_view
event, followed by a ‘window loaded’ event when the page is fully loaded.
Identifying Problematic Pages
The next step involves understanding which pages cause these issues. Often, the homepage bears the brunt of the impact, but how can you confirm this?
In GA4, you can generate a report to understand which pages are affected.
The report, segmented by page_view
and page_load_time
events, helps identify problematic pages. In this case, the homepage showed a difference of nearly 2,000 users—indicative of a significant issue.
Conclusion: Addressing Page Load Time
The discrepancy in page view and page load time presents a significant problem – lost traffic and revenue opportunities.
As such, addressing these issues promptly is paramount to the success of your hotel website.
By monitoring these metrics, you can optimize your website, improve user experience, and ultimately, increase your revenue.