Page Load Time in GA4: Do Users Even See Your Hotel Website?

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Understanding User Engagement on Your Hotel Website

Before assessing user engagement on your hotel website, it’s critical to ensure they can access your content.

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’.

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.

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Digital Strategy & E-commerce Expert for Independent Hotels.


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