Website Speed Test
Analyze website performance and Core Web Vitals
Calculator
Educational Tool
This tool provides example performance metrics to help you understand website speed optimization. For actual measurements, use real testing tools like Google PageSpeed Insights or GTmetrix (linked below).
Real Testing Tools
About Core Web Vitals
Core Web Vitals are a set of metrics that Google uses to measure user experience. They are critical for SEO and directly impact your search rankings.
Quick Optimization Tips
- Use WebP/AVIF formats
- Implement lazy loading
- Compress images
- Use responsive images
- Set cache headers
- Use browser caching
- Implement CDN
- Cache API responses
- Minify CSS/JS/HTML
- Remove unused code
- Use code splitting
- Defer non-critical JS
- Use Gzip/Brotli
- Optimize database
- Use HTTP/2 or HTTP/3
- Reduce TTFB
How to Use
Test website loading speed and performance
Enter URL
Type the full website URL to test (including https://)
Run speed test
Click test to analyze the website performance
Review metrics
Examine load times, Core Web Vitals, and improvement suggestions
Frequently Asked Questions
The speed test measures key performance indicators including Time to First Byte (TTFB), First Contentful Paint (FCP), Largest Contentful Paint (LCP), Total Blocking Time (TBT), Cumulative Layout Shift (CLS), page load time, and total page size with request counts.
Website speed directly impacts user experience, conversion rates, bounce rates, and SEO rankings. Google uses Core Web Vitals as ranking factors. Studies show a 1-second delay can reduce conversions by 7% and page views by 11%. Fast sites retain more visitors.
Ideal load times are under 2-3 seconds. Google recommends LCP under 2.5 seconds, FID under 100ms, and CLS under 0.1 for good Core Web Vitals scores. Mobile users expect even faster experiences, especially on slower connections.
Common optimizations include image compression, browser caching, minifying CSS/JavaScript, using a CDN, reducing server response time, lazy loading images, eliminating render-blocking resources, and optimizing web fonts. The test results provide specific recommendations.
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