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?

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.

Since I started self-hosting this blog again on August 6 2008, I have been trying to find more ways to pull traffic toward the content that I put up. Like all bloggers, I feel that I have important things to say (at least in the area of Web performance), and ideas that should be read by as many people as possible.

As well, I have realized that if I invest some time and effort into this blog, it can be a small revenue source that could get me that much closer to my dream of a MacBook Pro.

The Analysis

In a post yesterday morning, Darren Rowse had some advice on when the best time to release new post is. Using his ideas as the framework, I pulled the data out of my own tracking database and came up with the chart below. This shows the page view data between September 1 2007 and September 15 2008 based on the day of the week vistors came to the site.

Using this data and the general framework that Darren subscribes to, I should be releasing my best and newest thoughts in a week on Monday and Tuesday (GMT).

After Wednesday, I should release only less in-depth articles, with a focus on commentary on news and events. And I must learn to breathe, as I suffer from an ailment all to common in bipolars: a lack of patience.

A new post doesn’t immediately find its target audience unless you have hundreds or thousands (Tens? Ones?) of readers who are influential. If you are luckyin this regard, then these folks will leave useful comments, and through their own attention, help gently show people that a new post is something they should devote their valuable attention towards.

It takes a while for any post to percolate through the intertubes. So patience you must have.

Front-loaded v Long-tailed

Unless, of course, your traffic model is completely different than a popular blogger.

The one issue that I had with Darren’s guidance is that it applies only to blogs that are front-loaded. A front-loaded blog is one that is incredibly popular, or has a devoted, active audience who help push page views toward the most recent 3-5 posts. Once the wave has crested, or the blogger has posted something new, the volume of traffic to older posts falls off exponentially, except in the few cases of profound or controversial topics.

When I analyzed my own traffic, I found that the most of my traffic volume was aimed toward posts from 2005 and 2006. In fact, more recent posts are nowhere near as popular as these older posts. In contrast to the front-loaded blog, mine is long-tailed.

There are a number of influential items in my blog which have proven staying power, which draw people from around the world. They have had deep penetration into search engines, and are relvant to some aspect of peoples’ lives that keeps pulling them back.

Summary

I would highly recommend analyzing your traffic to see it is front-loaded or long-tailed. I know that I wish that this blog  was more front-loaded, with an active community of readers and commentators. However, I am also happy to see that I have created a few sparks of content that keep people returning again and again. If your blog is  long-tailed, then when you post becomes far less relevant than ensuring the freshness and validity of those few popular posts. Ensure that these are maintained and current so that they remain relevant to as many people as possible.

Recently there was an outage at a hit-tracking vendor I was using to track the hits on my externally hosted blog, leaving me with a gap in my visitor data several hours long. While this was an inconvenience for me, I realized that this could be mission critical failure to an online business reliant on this data.

To resolve this, I used the PHP HTTP environment variables and the built-in function for converting IP addresses to IP numbers to create my own hit-tracker. It is a rudimentary tracking tool, but it provides me with the basic information I need to track visitors.

To begin, I wrote a simple PHP script to insert tracking data into a MySQL database. How do you do that? You use the gd features in PHP to draw an image, and insert the data into the database.

header ("Content-type: image/png");

include("dbconnect_logger.php");
$logtime = date("YmdHis");
$ipquery = sprintf("%u",ip2long($_SERVER['REMOTE_ADDR']));

        $query2 = "INSERT into logger.blog_log values \
               ($logtime,$ipquery,'$HTTP_USER_AGENT','$HTTP_REFERER')";
        mysql_query($query2) or die("Log Insert Failed");

mysql_close($link);

$im = @ImageCreate (1, 1)
or die ("Cannot Initialize new GD image stream");
$background_color = ImageColorAllocate ($im, 224, 234, 234);
$text_color = ImageColorAllocate ($im, 233, 14, 91);

// imageline ($im,$x1,$y1,$x2,$y2,$text_color);
imageline ($im,0,0,1,2,$text_color);
imageline ($im,1,0,0,2,$text_color);

ImagePng ($im);
?>

DROP TABLE IF EXISTS `blog_log`;
CREATE TABLE `blog_log` (
  `date` timestamp NOT NULL default '0000-00-00 00:00:00',
  `ip_num` double NOT NULL default '0',
  `uagent` varchar(200) default NULL,
  `visited_page` varchar(200) NOT NULL default '',
  UNIQUE KEY `date` (`date`,`ip_num`,`visited_page`)
) ENGINE=MyISAM DEFAULT CHARSET=latin1;

Data should begin flowing to your database immediately. This sample snippet of code will allow you to pull data for a selected day and list each individual hit.

$query1 = "SELECT
                bl.ip_num,
                DATE_FORMAT(bl.date,'%d/%b/%Y %H:%i:%s') AS NEW_DATE,
                bl.uagent,
                bl.visited_page
        FROM blog_log bl
        WHERE
                DATE_FORMAT(bl.date,'%Y%m%d') ='$YMD'
		and uagent not REGEXP '(.*bot.*|.*crawl.*|.*spider.*|^-$|.*slurp.*|.*walker.*|.*lwp.*|.*teoma.*|.*aggregator.*|.*reader.*|.*libwww.*)'
        ORDER BY bl.date ASC";

print "<table border=\"1\">\n";
print "<tr><td>IP</td><td>DATE</td><td>USER-AGENT</td><td>PAGE VIEWED</td></tr>";
while ($row = mysql_fetch_array($result1)) {
        $visitor = long2ip($row[ip_num]);
        print "<tr><td>$visitor</td><td nowrap>$row[NEW_DATE]</td><td nowrap>$row[uagent]</td><td>";

	if ($row[visited_page] == ""){
    	    print " --- </td></tr>\n";
	} else {
    	    print "<a href=\"$row[visited_page]\" target=\_blank\">$row[visited_page]</a></td></tr>\n";
	}

}

mysql_close($link);

For my own purposes, this is an extension of the Geographic IP database I created a number of years ago. This application extracts IP address information from the five IP registrars, and inserts it into a database. Using the log data collected by the tracking bug above and the lookup capabilities of the Geographic IP database, I can quickly track which countries and ISP drive the most visitors to my site, and use this for general interest purposes, as well as the ability to isolate any malicious visitors to the site.

I got a comment from someone yesterday saying that they couldn’t get to their Statcounter Web site stats. I thought it was an issue on the user end and he reported that he finally got in with another browser.

Well, I just tried with all three of my browsers and I can’t get to the Statcounter stats that I pay for. This is somewhat distressing to me.

And it appears to be some form of DNS issue.

I have submitted an email to the Statcounter team and I hope to hear from them soon.

Not a good start to my Wednesday.

Technorati Tags: Statcounter, analytics, DNS

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

I have now launched the GrabPERF Site Statistics Index. The current members are:

• StatCounter
• SiteMeter
• ShinyStats
• OneStat

If you know of or represent a firm that I have missed, please drop me an email or a comment.

Technorati Tags: GrabPERF, Web performance, StatCounter, SiteMeter, OneStat, ShinyStats, Site Statistics, Web Analytics, performance index

You’ll notice that I have added the SiteMeter and StatCounter logos to the sidebar. Yes, I am a stats freak, but I also wanted to monitor how quickly each of these two services can deliver a page of basic stats to someone who clicks on the links.

So far, you can see the performance difference here.

I know that there are other services out there, and if you can think of one you use that i have forgotten, drop an e-mail or a comment. I want to create a site analytics benchmark, and also do some analysis of the differences in values captured by each of the services.

UPDATE [17:31 GMT]: I added OneStat to the list. New graph is here.

UPDATE [18:01 GMT]: I added ShinyStat to the list. New graph is here.

Technorati Tags: Web analytics, hit tracking, visitor tracking