Tag Archives: analytics

Why don't analytics PageSpeed numbers match PageSpeed scores?

Why don't analytics PageSpeed scores match the PageSpeed tool?

According to Google Analytics, the PageSpeed score for the page above is 88/100 but, in reality PageSpeed for this page is 64/100 for mobile users and 77/100 for desktop users. Don't be a sucker for analytics data dung! The only source for accurate up-to-date PageSpeed data is Google's NEW AND IMPROVED PageSpeed Insights tool. PageSpeed data from analytics and other sources is not always accurate or updated.

How fast should pages load?

As Matt Cutts recently pointed out, websites perform differently in different parts of the world. Ideally pages should load faster than the median load time in the country or region they target.

Where do I find the median page load time for my country or region of the world?

2013 Median Page Load Times: North America
- US 2.4 seconds desktop / 2.6 seconds mobile
- Canada 2.4 seconds desktop / 3.6 seconds mobile
- Mexico 3.8 seconds desktop / 4.5 seconds mobile
- Cuba 17.5 seconds desktop / 4.5 seconds mobile
- Bahamas 3.3 seconds desktop / 4.5 seconds mobile

2013 Median Page Load Times: Europe
- Czech Republic 1.6 seconds desktop / 3.4 seconds mobile
- Netherlands 1.8 seconds desktop / 3.1 seconds mobile
- Sweden 1.8 seconds desktop / 3.2 seconds mobile
- Russia 2.4 seconds desktop / 4.8 seconds mobile
- Germany 2.5 seconds desktop / 3.0 seconds mobile
- UK 2.5 seconds desktop / 3.6 seconds mobile
- Poland 2.7 seconds desktop / 4.7 seconds mobile
- Italy 3.3 seconds desktop / 5 seconds mobile
- Spain 3.2 seconds desktop / 5.3 seconds mobile

2013 Median Page Load Times: Asia
- South Korea 1.4 seconds desktop / 1.7 seconds mobile
- Japan 1.8 seconds desktop / 3.0 seconds mobile
- Russia 2.4 seconds desktop / 4.8 seconds mobile
- China 2.5 seconds desktop / 3.7 seconds mobile
- Viet Nam 2.5 seconds desktop /4.5 seconds mobile
- Thailand 3.7 seconds desktop / 5.8 seconds mobile
- Indonesia 7.4 seconds desktop / 5.1 seconds mobile
- India 5.1 seconds desktop / 5.8 seconds mobile
- Saudi Arabia 4.0 seconds desktop / 6.7 seconds mobile
- Pakistan 6.4 seconds desktop / 8.0 seconds mobile
- Iraq 5.5 seconds desktop / 5.9 seconds mobile
- Iran 6.1 seconds desktop / 9.5 seconds mobile
- Syria 8.1 seconds desktop / 9.1 seconds mobile

2013 Median Page Load Times: South America
- Chile 4.0 seconds desktop / 5.5 seconds mobile
- Brazil 4.7 seconds desktop / 7.7 seconds mobile
- Peru 4.3 seconds desktop / 8.5 seconds mobile
- Argentina 5.3 seconds desktop / 7.3 seconds mobile

2013 Median Page Load Times: Australia
- Australia 3.5 seconds desktop / 4.4 seconds mobile

2013 Median Page Load Times: Africa
- Morocco 3.5 seconds desktop / 5.0 seconds mobile
- South Africa 4.8 seconds desktop / 5.3 seconds mobile
- Algeria 5.1 seconds desktop / 7.8 seconds mobile
- Egypt 5.9 seconds desktop / 7.7 seconds mobile
- Kenya 7.7 seconds desktop / 11.4 seconds mobile

The list above provides the most recent median page load times as of 2013 from Google.

How do I compare pages with the same PageSpeed score to see which loads faster?

PageSpeed Insights is a great general purpose litmus test for improving PageSpeed but it only considers the network-independent aspects of page performance. To get down and dirty with respect to network performance and other speed related issues, you need to experience load times from the user perspective. To actually time pages via different browsers from various locations, use tools like WebPageTest.org or Pingdom. For instance, let's compare real load times, PageSpeed and speed index numbers for pages with Google Analytics, an optimized version of Google Analtyics and Google Tag Manager.

Load Time / Speed Index / PageSpeed
- empty page .461 seconds / 400 / 100/100
- custom analytics .619 seconds / 600 / 100/100
- standard analytics .808 seconds / 800 / 100/100
- tag manager .881 seconds / 900 / 100/100

Result: All of the URLs tested above have the same PageSpeed score of 100/100. However, from a user perspective the empty page has the best Speed Index score and loaded fastest.

Why are pages with asynchronous JavaScript slower than pages without JavaScript?

1. Not all browsers support asynchronous attributes.

2. When asynchronous scripts arrive during page load, browsers have to stop rendering the page in order to parse and execute scripts.

Even small things, like white space and HTML comments decrease page performance and increase load times. Scripts with ASYNC attributes like social media buttons and analytics tracking codes increase load times from a user perspective. It is always best to avoid including any unnecessary code or scripts even if they include the ASYNC attribute. Asynchronous scripts still impact performance.


It's becoming more and more clear that ranking reports are no longer reliable. Users are noticing personalized SERPs more and more and they're catching on to obvious inaccuracies generated by traditional ranking report software. These inaccuracies are caused by differences in query IP, query data, account status, web history, personalized settings, social graph and/or other. As a result, there is a growing shift away from rank report software to analytics for accurate SEO measurement.

Prior to personalized search results, SEO relied heavily on ranking reports in order to measure SEO campaign performance. SEOs create "ranking reports" with software that submits automated queries directly to search engines, a.k.a. "scrapes search engine results." Despite the fact that automated queries are against Google Webmaster Guidelines, waste energy and cost Google millions of dollars each year to process, scraping search engine results is still a popular practice. Obviously it’s in the engines best interest to take steps to prevent these queries.

Analytics software on the other hand is different, it works independently of search engines. Analytics relies heavily on code embedded within pages as well as human interpretation of data. Until recently, analytics software has been used only to “tell a story,” but not for the precise measurement SEO requires. Site analysis focuses on trending and establishing a “comfort level” with data determined to be "good enough" by the analytics specialist. Analytics platforms are designed for anyone to use, specialist and non-specialist alike. In many cases, analytics specialist themselves have little analytics experience, expertise, knowledge about how search engines work or an understanding of searcher intent. How can we expect anything different, when WAA itself still doesn’t teach things like transactional queries?

"To optimize scent trails, make sure that when the intent is transparent, the scent trail on any chosen term matches that intent. It doesn't matter if the trail starts with PPC (pay-per-click) or organic search. Prospects usually hope to find one of two things: the answer they seek or a link that takes them to the answer."

- The Web Analytics Association "Knowledge Required for Certification" (also available in non-www version)

Analytics tracking code is usually implemented by URL without consideration for user path, intent, source or origination. In most cases the implementation is performed by someone other than the analytics specialist interpreting the data. According to some estimates as many as 45% of pages implemented with Google Analytics contain errors. Conversions from organic SERPs are the most difficult to track back to the original referrer. To compound that problem, site issues often prevent even flawless analytics implementations from reporting. Analytics failures are costly, often go unnoticed and undetected because NOTHING is in place to report when analytics doesn't report.

Quick examples & thoughts:
- Even if Avinash himself, implements Omniture and Google Analytics tracking code on every page of your site, users entering from SERPs via 301 or 302 redirect won’t be attributed as “Organic.” According to Google, "If your site uses redirects, the redirecting page becomes the landing page's referrer. For example, if a user searches for a specific keyword, such as 'used books' on Google, there will not be any referring data showing that this keyword was searched on Google. Instead, the referral will be shown as the redirecting page."

- High traffic major converters or blank pages that send users to a competitor? Either way, nobody will ever know because these pages lack analytics tracking code. URL naming conventions for most sites follow a specific pattern. Use the site operator to quickly spot check for URLs that seem out of the ordinary to be certain they include analytics tracking code implementation and aren't redirected. It's pretty common to find legacy pages from older versions of sites indexed.

SEO Analytics

- If these folks are quick evaluators, analytics tracking code might not execute before a new page loads and this SEO conversion might be credited somewhere else. Analytics won't measure landing page load time even though it's a highly important metric for users. Flash or otherwise, pages like these always have issues when it comes to tracking organic conversions.

SEO Analytics

- If your site goes down chances are you'll never know because analytics reporting goes down as well. Using a website monitoring service is always a good idea, just to be sure that conversions really are down and not your entire site.

Takeaways, until SEO expectations are more clear to the analytics community, SEOs should insist on performing SEO analytics audits as usual. When hiring analytics specialists, look for applicants who are willing to address websites from the user perspective and outside of analytics. Folks willing to question data accuracy and those able to identify analytics obstacles are highly desired. Key being, SEO is as concerned with what analytics is tracking as it is about what analytics should be tracking.