This week marks a momentous time in the history of the Internet. In the United States, StatCounter reports that for the first three days of the work week (Monday – Friday), Internet Explorer 8 usage is equal to Internet Explorer 6 usage.

Tie this to the trend of decreasing Internet Explorer usage noted late last week and the release of Firefox 3.5 RC1 and Safari 4.0 and Opera 10 in the last few weeks, and it appears that the balance of browser usage on the Internet is becoming more fluid.

Does this mean that standards will become more relevant? Can you truly count on limiting customers to one browser?

Will browser lock-in for certain applications continue to be considered acceptable?

I have been monitoring this trend for a couple of weeks to see if it remained constant, and it appears to be a real thing. Since the end of May 2009, Internet Explorer 7’s browser share in the US has collapsed, with a requisite increase in the use of Firefox 3.0.

This is a staggering change. Either this is an artifact of the way that StatCounter is capturing browser data or a very large organization(s) suddenly switched the default browser that it allowed its customers to use.

Does anyone have any insight into why this may have occurred?

While I was performing my standard Windows Update on my work virtual machine this morning, I wondered if the promised Internet Explorer 8.0 release to Windows Update had been dropped.

I switched to my test-bed, vanilla Windows XP virtual machine, ran Windows Update, and PING! Up it came. The masses of people who blindly do what Windows Update tells them to do will now be installing Internet Explorer 8 on their machines.

The interesting thing is that the only piece of software that Windows Update said was a critical Update was Internet Explorer 8.0. Given that it would be replacing Internet Explorer 7.0 on my virtual machine, how bad was Internet Explorer 7? Are they trying to push MSIE6 and MSIE7 out of the way ASAP?

Today should see a large number of new installs of Internet Explorer 8, either on purpose or inadvertently by those folks who install everything that Microsoft tells them to. I will be monitoring StatCounter’s GlobalStats over the next few days to see if there is a spike in, most notably, US installs of Internet Explorer 8.

Just as a sidebar, Internet Explorer 8, without the support of Windows Update, has increased from 3.5% to 6.28% of the browser share in the US (3.33% to 6.2% in North America; 2.65% to 4.4% Worldwide) in the April 1-28 2009 period. [Stats courtesy of StatCounter GlobalStats]

I can’t make a lot of comments about the quality of browsing experience in one version of Internet Explorer over another; I have been a dedicated Firefox user on Mac, and a Safari user on Windows (yes, that is weird) for a while. But the desire to move as many people as quickly as possible to a new browser speaks volumes to where Microsoft thinks the Web is going. And they realize that it is not going in the direction that its older browsers had been taking it.

Further Updates will follow.

UPDATE: A colleague forwarded me this article on the release of Internet Explorer 8 to Windows Update. Effectively, you still have to go through the Web interface and agree to download the new browser. It’s not being pushed down onto Windows users through the automatic update built into the OS, no doubt to placate the glacially-slow IT departments I mentioned here.

A comment on my Hit Tracking with PHP and MySQL post raised some interesting questions about what a consumer of Web analytics data needs to consider when selecting providers for their sites.

Most folks are familiar with the model of Web analytics vendors: You place their JS tag on your page which makes a call back to their centralized system with all of the data that can be collected about the visitor who has just come to your site.

There are three items that you, the consumer of this third-party service, need to get straight answers about.

Performance of the Tag

Visitors to your site do not know which components you are responsible for and which you have farmed out to vendors and services. In their mind, all content is your content. This means that the performance of the Web analytics tag, which if not placed correctly on the page can affect the rendering of the content, is a critical factor in selecting a vendor.

To my knowledge, none of the Web analytics vendors used by most people blog and social media firms (StatCounter, GetClicky, Google Analytics, Omniture, etc.) freely share response time and error rate metrics of their tag infrastructure with the world as measured by a third party.

Is the tag delivered from a central location, or does the provider use a CDN? Is the data delivered asynchronously or synchronously?

The download performance of the tag is not the only concern. Ask them to provide data on the average processing time that they see when a client parses and processes the code. How does this processing time vary from browser to browser, between OSs? What steps are they taking to ensure that the tag does not affect the perceived performance of your page?

Ask for this data. Ask that the measurement data be collected by an impartial third party. Demand that this data be freely available to you before you make a decision on purchasing their service.

Size of the Tag

All of these services rely on a JS tag to collect and deliver the data to their data warehouse. Ask the provider to tell you how large this tag is, and what steps they have taken to reduce its size so that it has a limited effect on the download of your content.

Have they minified the tag? Is it delivered using HTTP compression to further reduce the size? Are ways to reduce the size of the tag always under considerations?

Data Storage

Analyzing data takes a couple of forms: daily operational views to spot changes or issues; and long-term trending to find larger patterns and major shifts in your visitors. As a result, data needs to be available with a substantial degree of detail while still providing aggregated data that allows larger patterns to be easily discovered.

How long does your provider store detailed data? What is the data expiry policy? Can you extract the data and import it into your own database?

Summary

Web analytics is key to determining what works and doesn’t work on your site. It tells who, where and how people are accessing your content. But without a Web analytics partner/vendor that provides performance and support, you may be left more in the cold than if you were just looking at your raw Web logs.

DNS hijacking is an occurrence that sends fear into the hearts of man and beast. It takes a perfectly harmless (yet critical) process and turns it into a weapon for chaos and mayhem.

This tool, however, does not simply reside in the hands of people looking to maliciously redirect traffic for purposes I can’t quite fathom – I’ll admit, there is still some simple naivete in my Canadian mind.

Legitimate companies, ISPs, service providers also have this tool at their disposal for their own purposes. An useful and accepted version of this exists already in the form of content delivery networks (CDNs) and other third-parties who take a portion of a companies domain name space and use it to deliver distributed edge content and computing, web analytics, or advertising services.

But let’s move this inside the firewall or into the consumer ISP space. These companies provide DNS for millions of customers. As a result, they could easily re-write DNS entries to reflect their own needs rather than those of the consumer.

In the case of corporate IT networks, there is not much that can be done – they own the wire, hardware and software being used, so they will claim it’s part of the corporate IT policy that all employees sign and that will be that.

Consumers, on the other hand, should expect free and unencumbered access to the worldwide DNS network, without being intercepted or redirected by their own ISPs. And there is frankly no way to verify that this is not happening unless you run your own caching BIND server on your home network.

The alternate is to use one of the external third-party services (OpenDNS or DNS Advantage). But these services also provide Phishing and Filtering services, which means that they can easily modify and redirect an incoming request using the most basic and critical service on the Internet.

While this may sound like the rant of a paranoid, it is a concept that has practical consequences. As an organization, how do you know that you aren’t on the DNS filter list of these providers, or the ISPs? If they can filter and redirect DNS requests, what else are they doing with the information? Are they providing open and trusted access to the core DNS services of the Internet?

Stepping back as far as you can into the process of going to your favorite pages, you will find that you can’t get there without DNS. And if DNS can no longer be trusted, even from legitimate providers, the entire basis of the Internet dissolves.

The Web analytics firm StatCounter has released a set of metrics that mines their entire dataset to provide worldwide metrics on browsers, searches, and operating systems.

This is the kind of data that everyone should be interested in. And it’s free. Check it out at StatCounter GlobalStats.

In the Customer Generation and Customer Retention articles of this series, the focus was on Web performance measurements designed to serve an audience outside of your organization. Starting with Business Operations, the focus shifts toward the use of Web performance measurements inside your organization.

Why Business Operations?

When I was initially developing these ideas with my colleague Jean Campbell, the idea was to call this section Reporting and Quality of Service. What we found was that this didn’t completely encompass all of the ideas that fall under these measurements. The question became: which part of the organization do reporting and QoS measurements serve?

What was clear was these were the metrics that reported on the health of the Web service to management and the company as a whole. This was the measurement data that the line of business tied to revenue and analytics data to get a true picture of the health of the online business.

What are you measuring?

Measurements for business operations need to capture the key metrics that are critical for making informed business decisions.

• How do we compare to our competitors?
• Are we close to breaching our SLAs?
• Are the third-parties we use close to breaching their SLAs?
• What parts of the site affect performance / user experience the most so we can set priorities?
• How does Web performance correlate with all the other data we use in our online business?

Every company will use different measures to capture this information, and correlate the data in different ways. The key is that you do use it to understand how Web performance ties into the line of business.

How often do I look at it?

Well, honestly, most people who work in business operations only need to examine Web performance once a day in a summary business KPI report (your company has a useful daily KPI report that everyone understands and uses, right?), and in greater detail at weekly and monthly management meetings.

The goal of the people examining business operations data is not to solve the technical problems that are being encountered, but to understand how the performance of their site affects the general business health of the company, and how it plays in the competitive marketplace.

What metrics do I need?

Business operations teams need to understand

• End-to-end response time for measured business processes
• Page-level response times for measured business processes
• Success rate of the transaction during the measurement period
• How third-parties are affecting performance
• How Web analytics and Web performance relate
• How different regions are affected by performance
• How does performance look from the customer ISPs and desktops

Detailed technical data is lost on these people. It is their role to take all of the data they have, and present a picture of the application as it affects the business, and discuss challenges that they face at a technical level in terms of how they affect the business.

Summary

For people who work at an extremely detailed level with Web measurement data (the topic for the next part of this series), Business Operations metrics seem light, fluffy, and often meaningless. But these metrics serve a distinct audience: the people who run the company. Frankly, if the senior business leaders at an organization are worried on a daily basis about the minute technical details taht go into troubleshooting and diagnosing performance issues, I would be concerned.

The objective of Business Operations measurements is to convey the health of the Web systems that support the business, and correlate that health with other KPIs used by the management team.

This week, I have been discussing the different approaches to blog analytics that can be used to determine what posts from a blog’s archive are most popular, and whether a blog is front-loaded or long-tailed. The thesis is that it’s not always what the words in the blog are that are important.

In a guest post this morning at ProBlogger, Skellie discusses how the value of social media visitors is different and inherently more complex than the value of visitors generated from traditional methods, such as search and feedreaders. Her eight points further support my ideas that the old advertising models are not the best suited for the new blogging world.

Stepping away from the existing advertising models that have been used since blogging popularity exploded in 2005 and 2006, it is clear that the new, interactive social web model requires an advertising approach that centers on community and conversation, rather than the older idea of context and aggregated readership.

The Current Model

Current blog advertising falls into two categories:

1. Contextual Ads. This is the Google model, and is based on the ad network auctioning off keywords and phrases to advertisers for the privilege of seeing their ad links or images appear on pages that contain those words or phrases.
2. Sponsored Ads. Once a blog is popular enough and can prove a well-developed audience, the blogger can offer to sell space on his blog to advertisers who wish to have their products, offerings or companies presented to the target audience.

In my opinion, these two approaches fail blog owners.

Contextual ads understand the content of the page, but do not understand the popularity of the page, or its relationship to the popularity of other pages in the archive.Contextual ads lack a sense of community, a sense of conversation. While the model has proven successful, it does not maximize the reach that a blog has with its own audience.

Sponsored ads understand the audience that the blog reaches, but do not account for posts that draw the readers’ attention for the longest time, both in terms of time spent reading and thinking about the post as well as over time in an historical sense. The sponsored ad model assumes that all posts get equal attention, or drive community and conversation to the same degree.

The New Model

In the new model, more effective use of visitor analytics is vital to shaping the type and value of the ads sold. Studying the visitor statistics of a blog will allow the owners to see whether the blog is, in general, front-loaded or long-tailed.

If the blog has a front-loaded audience, the most recent posts are of higher value and could be auctioned of at higher prices. In order for this to work, both the ad-hoster and the advertiser would have to agree to the value of the most recent posts using a proven and open statistical analysis methodology. In the case of front-loaded blogs, this analysis methodology would have to demonstrate that there is a higher traffic volume for posts that are between 0-3 days old (setting a hypothetical boundary on front-loading).

For blogs that are long-tailed, those posts that continue to draw consistent traffic would be valued far more highly than those that fall out into the general ebb and flow of a bloggers traffic. These posts have proven historically that they appear highly in search results and are visited often.

In addition to the posts themselves, the comment stream has to be considered. Posts that generate an active conversation are farmore valuable those that don’t. Again, showing the value of the conversation is reliant of the ability to track the numbers of people in the conversation (through Disqus or some other commenting system).

This model can be further augmented by using a tool like Lookery that helps to clearly establish the demographics of the blog audience. Being able to pinpoint not only where on a blog to advertise but also who the visitors are who view those page, provides a further selling point for this new model and helps build faith in the virtues of a blog that sells space using this new, more effectively targeted advertising pricing structure.

Now, I separate the front-loaded and long-tailed blogs as if they are distinct. Obviously these categories apply to nearly every blog as there are new posts that suddenly capture the imagination of an audience, and there are older posts that continue to provide specific information that draws a steady stream of traffic to them.

Summary

This is a very early stage idea, one that has no code or methodology to support it. However, I believe that the current contextual advertising model, one based solely on the content of the post, is not allowing the content creators and blog entities to take advantage of their most valuable resource – their own posts and the conversations that they create.

I also believe that blog owners are not taking advantage of their own best resource, Web analytics, to help determine the price for advertising of their site. Not all blog posts are created or read equally. Being able to very clearly show what drives the most eyeballs to your site is a selling point that can be used in a variable-price advertising model.

By providing tools to blog owners that intimately link the analytics they already gather and the advertising space they have to sell, a new advertising model can arise, one that is uniquely suited to the new Web. This advertising model will be founded in the concepts of conversation and community, providing more discretely targeted eyeballs to advertisers, and higher ad revenues to blog owners and content creators.

UPDATES

Appears that BuzzLogic has already started down this path. VentureBeat has commentary here.

This afternoon, StatCounter showed a marked increase in performance.

Normally I wouldn’t highlight an issue that only lasted an hour, but this appears to have been a very unusual issue that saw the page size decrease to nearly nothing, and performance shoot up to around 45 seconds. This combination usually indicates a back-end application timeout which then presents users with an error message.

StatCounter is in the GrabPERF Site Statistics Index.

Technorati Tags: StatCounter, Web Performance, GrabPERF, Web Metrics, Web Analytics

The Site Statistics | Web Analytics Index measurements have been running now for about 2.5 days, and I wanted to make some general comments on what I am seeing.

The methodolgy for testing is straightforward. I chose sites | services that allowed you to create a free (if limited) account to track your Web visitors, and allowed you to make these statistics available to for anyone to look at. Using this this, a measurement was established against the landing page that visitors would see if they chose to look at these publicly available statistics.

I am using this blog as the placeholder for the tracking “bugs”  used in this index (see the right-hand column).

From the graph above, it is clear that ShinyStat is the performance leader in this space. They have the smallest overall page size as well as the fastest and most reliable performance.

It is important to note that services such as WebTrends, Omniture, WebSideStory and Coremetrics are not included, as they are beyond the reach of most bloggers, and do not provide a public side to their data. Also, Google Analytics is not included, as they do not provide public access to the collected data.

The collected data is available in GrabPERF as both the Site Statistics Index, and as individual measurements.

Technorati Tags: Web analytics, web metrics, shinystat, onestat, statcounter, sitemeter, GrabPERF, Web Performance