Web analytics

The user perception of clicking a link within a webpage is that the request resource is retrieved and displayed in their browser. What is less well known is that the web server - the computer upon which the resources reside - make a note of the request it has just processed. This happens for every single request to the server and each is recorded in a logfile - an archive of all of the requests that the server has had to process. Each entry in the logfile looks something like the following (Logfile formats will differ between servers, but all will have some standard fields within them):

Obviously, on first observation, this information looks somewhat technical and of little benefit in observing behaviour! However, within this string of technical information lie some very useful units:

• IP Address (81.215.192.241) – the first element within the line above (the four numbers separated by periods) provides the address of the computer requesting the information (the computer at which the user sits). The IP address is the core locating mechanism within the protocols that enable computers to talk to each other across the Internet. However, more importantly to our purposes, it identifies an individual request and its location. IP address ranges are assigned at a country and corporate level (for example, any computer within the University of Plymouth network will start 141.163….) and therefore can be used as a crude locating mechanism that works very well at a country level.
• Time and date of request (30/04/2004, 09:49:03)
• Name of the resource request (/pages/search/showresource.aspx)– the page or resource requested by the remote computer
• Request arguments (id=1177&lang=0) – a technical term meaning any parameters passed with the request. Generally these are values used by the server to further refine the request. For example, if we look at a website such as Google, all searches will request the http://www.google.com/search resource. However, the server needs further information to know what the specific request to process. So, once we add a search term to Google (in this case “analytics”), something like: http://www.google.co.uk/search?hl=en&q=analytics&meta= will appear in the address bar of the browser.

At a very basic level, the most fundamental metrics are those such as hits and page views. A hit is a single request entry in a log file, a page view is a request asking for a web page. Arguably, one can also identify session, or clickstream, information – the pages a single user views in a single web site visit, through an aggregation of all requests from a specific IP address over a single date within a finite timeframe. However, while these basic metrics have some use, it is when such information is combined with more site specific data that the information one can glean becomes more useful. For example, if we resolve the location of the IP address, we now have an approximately location of the user, and therefore their clickstream. And if we know the nature of the resource requested, and how the arguments passed modify the nature of the resource (for example, looking at a particular item within an oral history database), we start to build a far richer picture of online interests and behaviour.

CLOSE

The Mediterranean Voices project is an ongoing project, initially funded by the European Union, to collect an oral history of cultures in the southern Mediterranean. The histories were recorded using a number of different media (image, audio, video) and were coded according to location and “themes” – cross cutting definitions of common practices within cultures (work, play, worship, etc.). Each resource had additional textual commentary in both the local language and English added to it, and researchers also had the option to tag resources they considered related to the one they were currently coding. Once this coding was complete, these resources were stored in a web based archive. The project aimed to demonstrate cross cultural similarities within the region and encourage the exploration of resources outside of a specific location. For further information on locations, themes and aims of the project, visit http://www.med-voices.org.

The application of analytics to the study of user behaviour within the Med-Voices site combined data from web logs and the resource database to enable an examination of individual’s explorations of the archive. IP resolution software (i.e. a piece of code that takes an IP address and provides an approximate location) was also used to examine the regions that were interested in the project, and what they examined.

The logfile data used for the experiment examine 1231 unique visits to the site, comprising in total 4672 resources viewed. The first experiment combined the data sources to consider the proportion of resources viewed by users in each of the locations represented in the project to give an indication of the regions of interest from specific counties. This would hint at interests of individuals within these locations. It grouped clickstream information based upon IP address groups (to group IP addresses by country), and then decomposed the sessions through the identification of requests to the “showresource.aspx” page (the page that displayed a given archive resource) and the arguments passed to that request (which would allow us to discover the origin of the archive resource being viewed). Table 1 provides a summary of this experiment, showing that some locations were more insular than others. While the volume of sessions is such that this cannot be taken as authoritative without further investigation (for example, only a single session from Italy cannot be taken as a general view of the interests of visitors from Italy!) it does provide an interesting an example of what we can learn from analytics techniques.

A second experiment examined the preference for viewing resource descriptions either in the local language or English, compared to the location of the user. This was possible through the isolation of the argument in the request that stated the preferred language for the resource. The results displayed in Table 2 again show indicative results rather than definitive statements regarding regional interests in language.

Finally, we examined the use of themes as a technique for encouraging exploration across locations. For this examination, specific clickstreams were examined and the resource path exploration was followed. A number of sample clickstreams are illustrated in Figure 2 below, showing the number of resources viewed within a specific location and theme, and the route traveled from each location:

CLOSE