Google PageSpeed testing tool.
Update: The Google PageSpeed checker is now running of the latest Google API, enhancing the power of the Chrome User Experience Report and data from Google Lighthouse.
This Page Speed tool is designed to let you check any given webpage and see how well it’s optimized for speed. To provide you with actionable and useful insights, this tool is running on the official Google PageSpeed API. Run the page speed test and use the suggestions and feedback to make your site even faster.
The insights you can expect to get from this tool:
- Mobile & Desktop PageSpeed score (0 – 100 scale)
- Device specific suggestions, to help you improving your page speed score.
- Device specific feedback, to show you which parts of your website successfully passed the test.
- Google Lighthouse lab data.
- Chrome User Experience Report.
Chrome User Experience
The Chrome User Experience data is collected by real-world chrome users.
- First Contentful Paint (Chrome)
- First Input Delay (Chrome UX report)
More information about Chrome User Experience data: https://developers.google.com/web/tools/chrome-user-experience-report
- First Contentful Paint
- First Meaningful Paint
- Speed Index
- Time To Interactive
- Total Blocking Time
Why is page speed important?
Page speed is important because a fast loading website improves the general user experience, decreases bounce rate and improves conversion rate. For those reasons Google also decided to make page speed part of their ranking algorithm. Back in 2010 Google officially announced page speed as a SEO ranking factor.
What is a good Google PageSpeed score?
A good Google PageSpeed score is considered to be a score of 90 or higher. An page speed score between 89 and 50 gets qualified as Needs work and a score below 49 gets the label Poor returned the Google pages speed insights tool and API. These scores are pretty stable because of the methodology used by Google to calculate these numbers.
How to improve your website load time?
- Eliminate render-blocking resources.
- Use browser caching.
- Improve server response time.
- Serve images in next-gen formats.
- Properly size images.
- Defer offscreen images / lazy-loading offscreen images.
- Use video formats for animated content.
- Enable compression.
- Minimize third-party usage.
- Keep request counts low and transfer sizes small.
- Avoid multiple page redirects.
- Minimize main-thread work.
- Avoid an excessive DOM size.
- Use caching, so you’re able to limit the number of browser requests.
- Optimize images for the web, reduce size and keep the quality.
Google PageSpeed score explained
The Google PageSpeed score is kind off unique because of the way Google calculates this score. Most tools look at the total load time of a webpage and because of the fluctuations and number of external factors involved this will only give you a time specific snapshot. When measuring site speed with essential tools like WebPagetest and Pingdom you’ll see a different load time almost every time you perform a test.
On one hand this is caused by fluctuations like for example time specific traffic load and on the other hand external factors like user connection speed, browser type and physical location influence these numbers.
The Google PageSpeed tool has removed almost all dynamic variables from the equation and instead focusses on the technical static components of your website. With Server response time being the exception here.
An overview of the Google page speed rules:
- Avoid landing page redirect
- Enable compression
- Improve server response time
- Leverage browser caching
- Minify resources
- Optimize images
- Optimize CSS Delivery
- Prioritize visible content
- Use asynchronous scripts
- Google developer guide – https://developers.google.com/web/fundamentals/performance/rail
- Google announcement: page speed is a SEO ranking factor – https://webmasters.googleblog.com/2010/04/using-site-speed-in-web-search-ranking.html
- Google research: Mobile page speed benchmark – https://think.storage.googleapis.com/docs/mobile-page-speed-new-industry-benchmarks.pdf
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