A swift-loading website not only enhances user experience but also boosts conversion rates. Recently, Google affirmed that Core Web Vitals impact its ranking algorithms.
Are you eager to optimize your website’s speed? Here are seven tips to help you evaluate your site’s speed and pinpoint potential enhancements.
Deciphering Network Request Waterfall for Website Analysis
Understanding a network request waterfall provides a comprehensive insight into your website’s loading process. This visualization reveals crucial details such as:
- Which resources are being downloaded?
- When do these resources commence loading, and what is the duration of each request?
- How does this align with the user’s perception as the website loads?
This data serves as the foundation for pinpointing impactful optimizations. You can generate a waterfall view for your website by conducting a free page speed test.
While request waterfalls may seem complex, let’s simplify what you should focus on. To interpret a waterfall effectively, pay attention to three key milestones:
- Time to First Byte (TTFB): Indicates the duration for the website server to return the HTML document.
- First Contentful Paint (FCP): When the initial page content becomes visible.
- Largest Contentful Paint (LCP): Identifies when the most significant content element becomes visible.
The HTML document is typically the first request, preceding the TTFB milestone. Before this point, no other resources can commence loading, and no content becomes visible. Therefore, the server’s TTFB sets a baseline for the FCP and LCP scores.
Next, identify render-blocking requests—essential resources for displaying page content. For instance, in the waterfall view, render-blocking CSS stylesheet requests may delay content visibility. To optimize FCP:
- Consider removing render-blocking resources.
- Reduce CSS file sizes.
- Load render-blocking scripts asynchronously.
- Expedite resource requests.
For instance, a large CSS file like “app.css” can significantly prolong loading times, particularly on slower mobile connections.
Additionally, server connections in the waterfall should be examined to gauge loading efficiency. Each new domain for resource loading necessitates a new server connection, which incurs a time cost for establishment.
Lastly, scrutinize the LCP milestone, especially if the largest content element is an image. You can quickly identify this by the “LCP” badge in the waterfall view. After downloading the LCP image, the browser promptly updates the page, with the LCP metric indicated by a red line in the waterfall.
Understanding and optimizing these elements in the network request waterfall can substantially enhance your website’s speed and user experience.
Prioritize Critical Content for Swift Website Loading
When loading a website, allocating bandwidth efficiently ensures that less critical content does not impede more crucial requests.
In the example, lazy loading is implemented for the Largest Contentful Paint (LCP) image. This means that initially, the browser doesn’t prioritize this resource. However, as the page begins to render, the browser recognizes the importance of the image, and its request priority is adjusted accordingly.
Consequently, the image’s loading is delayed; at that point, other requests consume network bandwidth. This is evident from the dark blue lines within the waterfall visualization, indicating when response data is received for each request. To ensure timely prioritization of an LCP image:
- Avoid lazy-loading it.
- Utilize the fetch priority attribute to designate it as high importance.
- Consider employing a preload tag to facilitate early loading of the image.
Streamline Early Requests by Minimizing Download Sizes
In the quest for swift website loading, minimizing the download sizes of key early requests is crucial. Larger files tend to prolong download times due to bandwidth limitations, necessitating multiple network round trips between the client and server. To trim file sizes effectively, consider the following strategies:
- Embrace modern image formats such as WebP and Avif, which are known for their efficient compression techniques.
- Employ Brotli compression for text-based content, including HTML, CSS, and JavaScript, to reduce file sizes without compromising quality.
- Conduct a thorough analysis of your HTML or CSS code to identify embedded images, fonts, and excessive data, allowing for targeted optimization efforts.
Enhance Website Insights: Comparing Real User Data with Lab Results
To gain more insights into your website’s performance, it’s essential to compare actual user data provided by Google’s PageSpeed Insights tool with the outcomes of lab-based Lighthouse tests. This comparative analysis aids in understanding the actual user experience versus simulated scenarios.
Lab test results tend to exhibit inferior metrics compared to actual user data. This discrepancy arises because the Lighthouse test simulates conditions with a slower network connection and CPU, unlike the optimal setups most visitors encounter.
Two primary reasons why lab testing results may appear faster than accurate user data are:
- Unreliable Reporting: The PageSpeed Insights test may provide data that needs to reflect real-world user experiences accurately.
- Cached Responses: Lab tests might benefit from cached content, while real users often contend with sluggish server responses, leading to disparities in performance metrics.
By scrutinizing and comparing these datasets, website owners can comprehensively understand their site’s performance and make informed decisions to enhance user experience.
Monitor Website Performance Evolution: Tracking Changes Over Time
Google’s real user dataset, derived from the Chrome User Experience Report (CrUX), contains historical data that must be explicitly presented in PageSpeed Insights. Harnessing this historical data enables you to track the evolution of your website’s performance, pinpointing the introduction of issues and uncovering their underlying causes.
Implement Ongoing Website Speed Surveillance
Establishing continuous page speed monitoring for your website is essential to promptly detect regressions—instances where changes adversely affect website speed.
Enabling monitoring for your website ensures immediate alerts in the event of regressions. Subsequently, it facilitates comparative analysis of data before and after the regression occurrence, aiding in identifying underlying causes for the slowdown.
Expanding Metrics Beyond Initial Load Time
Website performance encompasses more than the initial loading speed, as gauged by metrics like Largest Contentful Paint (LCP). Google now also evaluates how swiftly a website responds to user interactions, as quantified by the Interaction to Next Paint (INP) metric, which attained Core Web Vital status on March 12.
While LCP primarily hinges on network-loaded content, INP delves into CPU processing, assessing the time required for the page to process user interactions and update the UI for subsequent actions.
Measuring INP necessitates user engagement, posing challenges for lab testing environments. While there are lab-based INP testing tools like the INP Debugger, they may only capture some potential user interactions or identify the most frequently interacted elements. Real user monitoring (RUM) data is indispensable to enhance Interaction with Next Paint. This data empowers you to:
- Identify pages exhibiting sluggish INP.
- Pinpoint elements most frequently interacted with by users.
- Identify scripts contributing to performance delays.
Enhancing Website Speed: A Path Forward
Improving your website speed begins with a clear understanding of its bottlenecks. Utilizing a website monitoring tool enables ongoing tracking of Core Web Vitals, ensuring timely detection of regressions. However, if navigating this process feels overwhelming, consider exploring our monthly SEO packages. Our team of experts stands ready to lend a hand and optimize your website’s performance.
