Web analytics is the practice of analyzing data on how websites are used in order to improve how the resource performs. After studying this topic in a two day course, I am much better informed about the tools, methods and resources that make analytics worthwhile. The course was oriented mainly toward commercial needs, but the ideas presented can be applied to a variety of contexts. Computers can automatically track a great deal of information which can be a mixed blessing. The course helped me to think through the right questions to ask so that that mass of data can be analyzed and then put to use to improve operations. To sort through the data, it is best to clarify what one’s goals are.
Let’s say you want users to use a resource that you have designed (an internal website, a catalogue or something similar). You can use analytic tools to measure what proportion of your visitors use the feature (this would be your “conversion rate” – conventionally, conversion refers to the portion of website visitors who continue on to make a purchase, but I am using it to mean “portion of users who take a desired action”). Further, you can also see how many times the function is used and if people are turning up empty search results. What is the value of doing this? You can learn learn some sense of how much time people spend using a tool, how much it fails and identify areas for improvement. Much of this can be accomplished through skillful use of a free tool like Google Analytics, but it is not the only (nor necessarily most powerful) game in town.
Web analytics can also be used to determine how people come to your information service. Do users entering the website through a URL (i.e. typing it in or through a bookmark) behave differently from those arriving from a search engine? If the library is embedded in a larger organization (e.g. KM unit in a firm’s intranet, public library in the city’s website, academic library in the university’s website), that usage can be tracked as well. Analysis of these kinds of data can assist in refining the website design, eliminate problems and evaluate marketing campaigns. If users arriving from the Internet are “bouncing” (i.e. leaving after accessing a single page), then this may indicate a need to better explain the services.
For those looking to learn more about web analytics, there is a wealth of information available to help you get started. There are a number of good books out there including: Web Metrics: Proven Methods for Measuring Web Site Success by Jim Sterne, Competing on Analytics by Thomas H. Davenport and Jeanne G. Harris (I gather that is a more general work; not focused on web analytics only) and Web Analytics: An Hour a Day by Avinash Kaushik. And here are two blogs to consider: Web Analytics Demystified and Occam’s Razer (OR is written by Avinash Kaushik). Most of these resources come to web analytics from a marketing and/or business perspective. These insights can be applied to other contexts with some effort and care.
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