Karine Joly began the Web Analytics Revolution over the summer with her initial request for baseline information. She presented a quick analysis of her finding in August and Shelby Thayer added more insightful information in her post.
Today I want to focus on one of Karine’s key finding: there appears to be lack of dominant use of web analytics for decision-making. Only 53% use the data primarily to improve their site. In other words, barely 1/2 of institutions use analytics to improve the user experience on their website. Yikes.
I’ve spent the better part of my professional career in higher ed implementing, analyzing and responding to web analytical data. I’ve worked with many institutions across the country to better situate their web analytics strategy. Through my trials, I’ve come to find a few misconceptions about web analytics that I believe hinder a much needed wider adoption.
Misconception 1: Web Analytics will Solve World Peace
For some reason, the promise of data to many indicates a clear-cut analysis of what to do (or not to do). As I explain to clients, web analytics will tell you what happened, when it happened, from where it happened, how it began and who consumed the content, but it will never tell you why the content was approached — and this is the fundamental question many use when approaching web analytical data. When this can’t be found in the pretty charts and graphs, the strategy is abandoned.
Web analytics are a tool in your toolbox. They have specific purposes (who, what, when, where and how), but they won’t assemble the entire project. Use web analytics to answer the questions for which it is built, and provide a foundation for exploring the unknown through other research mechanisms (usability analysis, focus groups, surveys, etc…).
Misconception 2: Web Analytics Provides too Much Data
I often receive this complaint from someone who has been tasked with evaluating a completed marketing/content strategy. A request was likely brought up in a meeting by a middle-manager who asked “Can we get some data on how well our strategy performed?” (see Misconception 1). So our support staff member logs into analytics and is immediately overwhelmed by the numbers, options and terminology.
Web analytics is not for the faint-hearted. While products like Google Analytics have made it much easier to get data and present it in a more user-friendly way, they still require synthesizing. This is where training and time are required. I truly believe anyone with a bit of desire can quickly get the basics, but it does require some understanding and knowledge filtering. Keep checking this blog, we’ll help you out.
Misconception 3: Web Analytics Provides Conflicting Data
Usually, this concern comes from someone in IT who compares data from the server-side log analysis software with a client-side tracking tool like Google Analytics. When the numbers don’t match exactly, our IT person assumes the client-side tool is corrupt and unreliable.
My response to this is: “Remove the IT department from the web analytics review.” The purpose of web analytics is supporting and fostering improvements to the user experience — which lands in the marketing department’s wheelhouse.
Furthermore, server-side and client-side tracking are fundamentally different. The tracking process is done in a different way, each giving greater emphasis to different stats. Both have their pros and cons.
Let’s Revolutionize Web Analytics
We need to break down these misconception barriers as part of this Web Analytics Revolution. Web analytics is not difficult, it just requires the correct mindset, a strategic goal, and an understanding of how the translate data. Examples of these are vast across the web; we’ll try to help you put the higher ed shine on your approach.Tags: opportunities, revolution