This is reprint of an article I wrote last month for www.journalism.co.uk .
It came about from a discussion of what is the most accurate method for measuring visitor activity.

Content: This is a multi-page post. You are on Page: 1 2 3

  1. Page 1: Summary – there is no accuracy debate!
  2. Page 1: Introduction – why most of the web is junk and what role web analytics plays
  3. Page 2: On-site versus Off-site web analytics tools and how they work
  4. Page 3: Discrepancies – what’s accurate and how can accuracy be improved

3. How off-site web analytics works
Off-site web analytics tools measure your potential website audience. They are the macro tools that allow you to see the bigger picture of how your website compares to others.

There are two types of techniques that achieve this – using panel data or Internet Service Provider (ISP) data.

Companies such as comScore and Nielsen Netratings use the panel method by recruiting participants using a combination of their website and the calling of prospective panellists.

Their technique is to have monitoring software installed on users’ computers to measure their web activity. Panel sizes vary, but range from tens to hundreds of thousands of participants, with the majority of these based in the US. For example, comScore reports 2 million participants worldwide with over 50 per cent of these based in the US.

Most panel participants are home users, as these are not restricted by IT policies when it comes to installing tracking software (public access is screened out from comScore data). Similar to election polling, panel data is extrapolated (multiplied up) to provide an estimate of the behaviour for total web population.

An important advantage of panel data is that the analytics vendor knows who its panellists are. Demographic information such as age, gender, income bracket etc, are available, though these are inferred in the extrapolated data set.

The caveat to this method, is that websites you wish to measure must have sufficient visitors to show up above the ‘noise’ threshold and mitigate sampling errors. Think of this in terms of having a high signal to noise ratio. The threshold will vary depending on where most of your visitors connect from, as the sample size of panellists varies from country to country.

Alternatively, companies such as Hitwise (now part of Experian), collect off-site visitor information by aggregating anonymous data provided by ISPs. This has the potential to offer much larger sample sizes than panels (Hitwise reports 25 million people worldwide, 40 per cent based in the US) and therefore a lesser degree of extrapolation is required, potentially resulting in greater accuracy.

Because this type of off-site tracking happens at the ISP/network level, all visitor types are represented, including home, work, mobile, educational and public access. The trade off is that this data is anonymous. Therefore demographic data is not available.

How on-site web analytics works
On-site web analytics tools measure the actual visitor traffic arriving on your website. They are capable of tracking the engagements and interactions your visitors have, for example, whether they convert to a customer or lead or not, how they got to that point or where they dropped out of the process altogether.

Although there are several techniques to measure visitors on your site, the method used by the vast majority of vendors is the so-called ‘page tagging’ technique.

This requires the placement of a small snippet (aka ‘tag’) of java script code on your webpages that act as a beacon – capturing visitor information in their browser, storing these as cookies, then broadcasting this to a data collection server in real-time.

A key difference between on-site and off-site web analytics tools is that on-site visitor data is only available to the website owner and the people he/she grants access to, such as a third-party marketing agency.

Conversely off-site web analytics data can be obtained for any website – including your competitors and partners, provided there is sufficient visit data.

This is a multi-page post. You are on Page: 1 2 3

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Possible related posts (auto generated):
  1. Why counting uniques is meaningless
  2. Accuracy Whitepaper for web analytics
  3. Google is Like a Bank
  4. What is ABCE?
  5. Should you focus on website visitors as individuals?

This is a multi-page post
Page: 1 2 3