Measuring Success

The term ‘uniques’ is often used in web analytics as an abbreviation for unique web visitors (i.e. how many unique people visited my site). The problem is that counting unique visitors is fraught with problems that are so fundamental, it renders the term ‘uniques’ meaningless. Firstly, cookies get lost, blocked and deleted. Research has shown that after a period of four weeks, nearly one third of tracking cookies are missing, which means the visitor will be incorrectly considered a new unique visitor should they return to the same website (see Accuracy Whitepaper for further reading). The longer the time period, the greater the chance of this happening, which makes comparing year-on-year data invalid for example. In addition, browsers make it very easy these days for cookies to be removed – see the new ‘incognito’ features of the latest Firefox, Chrome and Internet Explorer browsers. However, the biggest issue for counting uniques [...]

          Last year I wrote an whitepaper on web analytics accuracy. The intention of this was to be a reference guide to all the accuracy issues that on-site web measurement tools face, and how you can mitigate the error bars. Apart from updating the article recently, I wanted to illustrate how close (or not) different vendor tools on the same website can be when it comes to counting the basics – visits, pageviews, time on site and visitors. To do this, I have looked at two very different web sites with two tools collecting web visitor data side by side: Site A – This blog, running Google Analytics and Yahoo Web Analytics. According to Google, there are 188 pages in the Google Index and traffic is approximately 10,000 visits/month Site B – A retail site that runs Nielsen SiteCensus and Google Analytics (site to remain anonymous). According to Google, [...]

I recently read an article by a friend of mine Neil Mason, called – Tackling the basics of web analytics: Getting the right numbers right . To summarize, Neil discusses how difficult it can be to install even the most simplest of tracking tags (data collector beacons) across an enterprise web site. That is, a site that is large (thousands if not hundreds of thousands of pages of content), uses multiple technologies and has multiple stakeholders – often in different countries and sometimes different companies. However, this fundamental step of getting the data in using page tags, is the key to everything else i.e. getting good, solid, accurate data in*. There simply is no point investing in analysis if the data is flawed. After all, garbage in = garbage out. And of course the web is ever changing, so maintaining data integrity is also key. Page tagging is therefore not [...]

I have heard the notion of Google being analogous to a bank for a number of years. Recently, Jim Sterne also referred to this bank analogy while we were discussing online privacy at the Orion Analytics panel of SES London . So I wanted share and expand upon this discussion. Please take a moment to read my disclaimer before continuing – that is, the views express on this site are entirely my own and do not represent those of my employer. Is Google entering into online banking? In this respect no (I am not considering Checkout here). What I mean by being analogous to a bank, is in the way that data itself has become "currency". Information has always been valuable – no one likes to be the last to know, and being the first to know gives you a competitive advantage. So whether online or not, the storage and [...]

This accuracy post is an extrapolation of a section in Chapter 2 of the book which has led to a separate PDF accuracy whitepaper available to download for free. [updated April 2010 - see new post] Why is this necessary? Well, the question of accuracy crops up all the time on numerous forums and at conferences. Essentially many practitioners of web analytics worry about accuracy. Some vendors even claim greater accuracy than others (though as I explain in the whitepaper this cannot be true), and there is the inter-industry debate about whether off-site analytics (for example, Hitwise, comScore, Neilsen//Netratings etc.), are better at predicting traffic levels than on-site analytics tools (such as Webtrends, Omniture, IndexTools, Google Analytics etc.). I won’t go into that debate here, except to schematically illustrate the two different web analytics approaches in Figure 1. Figure 1 : On-site v off-site web analytics The truth is, for [...]