How Google PageSpeed Works: Improve Your Score and Search Engine Ranking

This article, courtesy of my friend Ben from Calibre (a website performance monitoring tool we use at CSS-Tricks), delves into the workings of Google PageSpeed's critical speed score. Given Google's use of page speed as a ranking factor, optimizing performance is paramount for revenue and user retention.

Google's 2023 algorithm updates significantly impacted SEO: mobile-first indexing (March) and the inclusion of page speed as a ranking factor for both mobile and ads (July). This underscores two key points: mobile site speed directly impacts SEO, and slow loading times increase ad costs. Google itself highlights the link between faster sites, improved user experience, and reduced operating costs.

PageSpeed 5.0, powered by Lighthouse and CrUX (Chrome User Experience Report), represents a major shift from previous versions. Its new scoring algorithm makes achieving high scores more challenging.

PageSpeed 5.0: A Paradigm Shift

Prior to version 5.0, PageSpeed relied on heuristics (e.g., suggesting image compression for large, uncompressed images). These were guidelines, not analyses of real-user loading and rendering experiences.

PageSpeed 5.0 utilizes Lighthouse to load pages in a controlled Chrome browser, recording metrics and applying a scoring model. Improvement suggestions are based on specific metric scores. Crucially, PageSpeed's score now directly mirrors Lighthouse's Performance score.

Understanding Google Lighthouse

Lighthouse, an open-source Google Chrome project, is a leading free performance analysis tool. It leverages Chrome's Remote Debugging Protocol to gather data on network requests, JavaScript performance, accessibility, and user-centric timing metrics (First Contentful Paint, Time to Interactive, Speed Index, etc.).

Deconstructing Lighthouse's Performance Score

Lighthouse uses six metrics to calculate the overall performance score:

• Time to Interactive (TTI)
• Speed Index
• First Contentful Paint (FCP)
• First CPU Idle
• First Meaningful Paint (FMP)
• Estimated Input Latency

Each metric receives a 0-100 score based on mobile 75th and 95th percentile data from the HTTP Archive and a log-normal function. Weightings are then applied to reflect their impact on mobile user experience:

Metric	Weighting
Time to Interactive (TTI)	5
Speed Index	4
First Contentful Paint	3
First CPU Idle	2
First Meaningful Paint	1
Estimated Input Latency	0

A provided Google Spreadsheet calculator illustrates how these weightings affect the overall score. The example shows that TTI significantly impacts the final score.

Optimizing Time to Interactive (TTI)

TTI is heavily influenced by JavaScript delivery and execution time on the main thread. Key strategies for improvement include:

• Reducing JavaScript: Remove unused code, replace large libraries with smaller alternatives, and use code splitting (breaking large applications into smaller bundles).
• Leveraging Service Workers: Cache compiled scripts to mitigate repeated parse and compilation costs.

Regular monitoring using a performance monitoring system (like Calibre) across various devices is crucial for identifying and addressing performance bottlenecks. Thorough JavaScript profiling, ideally using real or emulated low-end mobile devices, is recommended.

Beyond TTI: Other Key Metrics

Speed Index, FCP, and FMP are browser-rendering metrics. Improving these often involves optimizing critical requests and preloading fonts.

Continuous Monitoring: The Key to Success

While tools like Google Search Console, Lighthouse, and PageSpeed Insights offer valuable insights, continuous monitoring is essential for sustained performance improvements and the immediate detection of regressions. This is where dedicated performance monitoring platforms excel. The need for speed is paramount in today's mobile-first world, impacting SEO and user experience significantly.

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