Web analytics practitioners, myself included, often express site behavior in terms of the number of unique visitors to a site.  Statements such as “we had 14,000 unique visitors to our site between the 1^st and the 15^th of February 2010” are quite common and, on the face of it, impressive.  After all, if unique visitor volume, in the lingua franca of web analytics, is considered a proxy for site popularity – why not use it?

However, the concept of a “unique” visitor gets confusing.  The more I think about it, the more I wonder if this concept is accurate. For example, if I go to the espn.com site from my desktop in the morning and then read a story in the afternoon from my mobile device, and return to buy merchandise late in the evening from my laptop – can I really be considered as three different individuals? Or should I be considered as one person making three visits in the course of a day?

In the absence of any reliable way to connect my identity across three independent visits to the espn.com site, a unique visitor count of three is wrong.  Second, even when repeat visits are from the same device, the counting of unique visitors becomes problematic given that cookies may get blocked or deleted.  Web analytics experts estimate that after about four weeks, about a third of cookies are missing (see http://www.advanced-web-metrics.com/accuracy-whitepaper).  This implies that when a visitor returns to a site from the same device after four weeks she is accounted for as another unique visitor. That’s bizarre, but true.

So, what is an analyst to do? The simple solution is to forget the unique visitor metric and simply use the visit count. In most cases, for sites that do not invite individual visitors to self identify simply doing away with the unique visitor count and using the visit metric allows the site owners to take the same business decisions.  For sites that do invite self identification a solution would be to take the ratio of logged in visits to the total visit volume among that group and apply the same split to the non-identified visitors to estimate an overall visitor volume. The overall point, however, is still the same.  Most decisions in today’s business environment that leverage web analytics data are not likely to be negatively impacted simply because we choose to substitute unique visitor data with visit information.

This entry was posted on Friday, March 19th, 2010 at 6:04 pm and is filed under Web Analytics. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.