When I first saw the title of this course, Web Metrics and SEO, I was intimidated to say the least. I didn’t even know that SEO was short for search engine optimization, nor did I really know what Web metrics meant except something to do with math. I think such lack of knowledge among marketers and public relations practitioners like me is more the rule than the exception and contributes to Web analytics failures. While I would not suggest that every marketer and public relations practitioner should be experts in Web metrics, a solid understanding is necessary in today’s Internet-based world.
In my very elementary understanding of the issue, many analytical applications fail because they assume users know precisely what they need before the analysis begins (Gemignani, Z., 2008). Often times, marketers and public relations professionals depend upon a tool to track an answer with only a vague idea where to start. Zack Gemignani with Juice Analytics said (2008) that “the exploratory analysis that follows can feel like swimming upstream when the application isn’t designed to facilitate the journey.”
As any good public relations practitioner or marketer will tell you, research is a key factor in any successful campaign. But measuring for the sake of measuring without a goal is pointless. Mark Twain once said, “People commonly use statistics like a drunk uses a lamp post; for support rather than illumination.”
Many a campaign has failed because no one really looked at what the statistics were saying. The reality is numbers don’t always tell the whole story. We must not make such assumptions if we hope our Web analytics efforts to be successful.
For example, Gerry McGovern in the Marketing Profs Daily Fix (2006) said just because someone is a repeat visitor to your site does not mean they are a satisfied customer. He cites multiple personal visits to the Cruise America site. After his first visit, he left frustrated, confused and annoyed because he could not get the quote function to work properly. A second try had equally frustrating results. Yet the numbers would make McGovern appear to be a satisfied, repeat customer (McGovern, G, 2006).
Similarly, a study by Jared Spool of User Interface Engineering comparing Gap.com with Newport-News.com further illustrates how measuring volume alone contributes to failure. The study found that Gap's site outperformed Newport News by a factor of 10. While the overall Web site design is credited for Gap's success, the study also found that the average purchase on the Gap site took 12 pages, whereas the average purchase on Newport News took 51 pages. The more pages people looked at, the less likely they were to buy (McGovern, 2006).
The lesson for both CruiseAmerica and Newport News is that volume is not sufficient to determine if a Web site is successful because it can blur reality. The numbers could represent loyal, repeat customers. But they also could just as easily represent disgruntled shoppers who leave a site without spending a penny. Better to also look at how long it takes a Web site visitor to complete a task than visits alone.
References:
Gemignani, Z. (2008, July 7). Why analytical Applications Fail. Retrieved January 21, 2010, from http://www.juiceanalytics.com/writing/why-analytical-applications-fail.
McGovern, G. (2006, May 19). Are You Measuring Failure? Marketing Profs Daily Fix blog. Retrieved January 21, 2010, from http://www.mpdailyfix.com/2006/05/are_you_measuring_failure.html.
Phillips, J. (2009, April 9). Why Web Analytics Tools Fail. Online Metrics Insider. Media Post Blogs. Retrieved January 21, 2010, from http://www.mediapost.com/publications/?fa=Articles.showArticle&art_aid=103844.
Twain, M. (undated). Quotes from Famous People. Retrieved January 21, 2010, from http://www.myeyez.net/famous-quotes.shtml.
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