A lot of people ask us – where do we start when it comes to web analytics. What’s the first thing to do? What tool to buy? Seems like a good post to initiate a discussion.

Well, the easiest thing to do would be to contact us! No, just joking… I would suggest some reading to start with (That would also give me some time to write the other posts). We would highly recommend the following resources:

Eric Peterson’s Yahoo group:

This is where the action is. You can listen to a lot of wise and bright people. Some of the things might be completely confusing, but don’t give up hope. There is a lot to learn from this group.

Eric Peterson’s book: Web Analytics Demystified

This is an excellent book on anyone new to web analytics. It covers the basic and is quite easy to follow. I must also add here that Eric was kind enough to send us free copies of his book to a bunch of us here in Bangalore. Thanks Eric.

Hurol Inan’s website:

A lot of interesting articles as well as links to other resources.

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Almost about a year back, blogger, consultant and Web Analyst Avinash Kaushik, in his Occam’s Razor wrote about a very interesting and informative topic on identifying a great Web Analyst. It was a very well composed writing in which he had narrowed down his experience down to a check list of 10+1 points pinpointing out the virtues of this breed. He also speaks about a 10/90 rule which is on the same line as the 80/20 rule much spoken of with regard to McKinsey’ites. Along with his insights, there are also the comments which tries to fill in any thing which he might have missed or his readers felt should have been there in the check list. Though the article was posted way back in June ‘06, its still effective and good to read. Surely among the entries in his check list one can find mentions about Web Analytics tools used, technical know-how’s and the Yahoo! Web Analytics group but there’s more to it that deserves a read and thats why I consider it as a winner.

In the end, it lets one know where he or she fits in and what are the possible areas one needs to look out for more perfection. So get the article scanned by your eyes and show the Signs of a Great Web Analyst.

Technorati Tags: Web Analyst, Great, 90/10, 80/20, Top 10, Great Web Analyst, Identifying the Great Web Analyst, Occam’s Razor, Avinash Kaushik

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Thats what it often feels like when we try to imagine who these people are visiting our websites.

So, the next time you’re pondering over the same question, why don’t you head over to Microsoft’s adCenter Labs. They have a range of demos, but what caught my eye was their Demographics Prediction demo.

Admittedly, the amount of information they provide at the moment is a little on sparse side, breaking down your visitors into male/female and into different age groups. But this is something with potential. And in the future research like this will be more closely tied into web analytics. And one of the biggest benefits I can see, in this age of ad-saturation, is that it will make for more effective, less intrusive marketing. The days of carpet bombing ads aren’t over. But the beginning of the end is in sight.

Or maybe I’m just being too optimistic

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A spreadsheet is often a very handy tool for analysis and reporting. With MS Excel, there are loads of cool features and still newer ones being added on with newer versions of it. But imagine the plight of having to do an analysis and there is a data overload in that Excel workbook. Ok, you played with some of the possibilities in MS Excel, discovered few techniques of “doing that in a smarter way” and later on while making the presentation, someone (or you yourself) discovers some faulty data. First thing that comes to your mind is “Oh no, I’ve to do that again?”. Well with massive data crunching, there often comes situations like these.

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“What is it?” This question often finds its way ‘wherever’ there is mention of Web Anlaytics. A novice would ask being inquisitive, while the average to the very-pro geeks on the other end, will look towards bringing up this phrase in some context (or another) and themselves attempt at answering it. By ‘wherever’, I am pointing at both the real world as well as the loads of formatted pages in the world wide web - better called the virtual world. The latter one is logically obvious. Without the three W’s, where will the essence of Web Analytics lie?

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