Search Engines & SEO

Page Speed

Definition

Speed is measured two ways and the difference matters. Lab data comes from a simulated load in a tool such as Lighthouse: repeatable, good for debugging, and not what any of your visitors experienced. Field data comes from real Chrome users and is what Google uses for ranking, through the Core Web Vitals thresholds. The headline measures are Largest Contentful Paint for when the main content appears, Interaction to Next Paint for how quickly the page answers a tap, and Cumulative Layout Shift for things moving under the reader's thumb. A PageSpeed Insights score out of 100 is a weighted summary of lab metrics only — a page can score 68 and still pass every field threshold, or score 95 and fail them.

Why It Matters

Speed changes behaviour long before it changes rankings. Google's own field studies show abandonment rising sharply as load time passes three seconds, and the effect compounds on a mobile connection. As a ranking factor it is real but modest: it separates pages that are otherwise close, and no amount of speed rescues a page that does not answer the query. The honest framing is that speed is a tax on everything else you do — a page that ranks well and loads slowly still loses most of the visitors it earned.

How It Works

Most delay comes from bytes and blocking. The browser requests the HTML, parses it, and discovers the stylesheets and scripts it needs on the way through; a render-blocking stylesheet in the head stops painting until it arrives, and a synchronous script stops parsing altogether. Images are usually the single largest cost, so serving a correctly sized WebP instead of a camera original often saves more than every other change put together. Compression and caching handle the rest: Brotli on text assets typically saves 15 to 20 per cent over gzip, and a long Cache-Control max-age means repeat visitors download nothing at all. Serving from an edge network shortens the round trip, which shows up as a lower Time to First Byte. What counts as good — the actual thresholds and how the field data is collected — belongs on the Core Web Vitals page rather than here.

Real-World Example

A consultancy publishes a report site to 99helpers with six photographs on the front page, all straight out of a DSLR. The homepage weighs 41 MB and takes over nine seconds to show its main image on a phone. Resizing the photographs to 1600 pixels and exporting them as WebP takes the page to 1.4 MB and the main image to about 1.6 seconds. Nothing else changed — no build step, no framework, just smaller files uploaded to the same address.

Common Mistakes

  • Optimising for the Lighthouse score rather than the field data — the score is a lab summary, and ranking uses what real visitors actually experienced
  • Testing on a laptop on office wifi — the median visitor is on a mid-range phone on a patchy connection, which is what the field data reflects
  • Adding third-party scripts for analytics, chat and fonts and then wondering where the seconds went — each one is a connection, a download and work on the main thread

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