Web Data Analytics: Some Problems

There are two major problems with Web presence analytics; they're either non-existent or too complicated. Many people may be against using web analytics because it not only measures success it also measures failure. Someone in charge of marketing might be afraid to use web analytics because it would prove the failure scientifically. Avoiding web analytics because it shows failure is the wrong attitude. We learn from our failures and we must welcome the opportunity to gain knowledge of them.

There is a lack of skilled employees required to manage, distribute and analyze Web analytics. Historically, web analytics was developed by IT for IT. The people using them were comfortable with dealing with raw data. Web analytics tools have been designed to be interpreted by technical personnel. There was little regard for people without technical skills. As a result, the rest of the organization has become alienated from analytics. A good web analytics solution has to be easy to understand for any member of the organization. One of the biggest misconceptions of web analytics is that it needs to be complex.

Often, web analytics generate a huge amount of data. The end result is data overload that lacks actionable information. Frequently, insignificant data becomes the noise around actionable data. The noise makes the process overwhelming. Instead of providing answers, web analytics can create more questions. Meaningful interpretation of data has created a hostile attitude toward web analytics among the non-technical people of the organization.

Web analytics is not easy by any stretch of the imagination. Web analytics tools provide data not information or insight. We need the tools to provide us with the raw data, but it's up to us to make sense of it all.

Web sites are no longer just online catalogs with a shopping cart. They are becoming complex applications with high levels of interactivity. Today, a highly usable site is also highly interactive. If the on site search is not working properly, you have a web site that lack interactivity. Therefore, it scores low in the usability scale. If the site navigation is counter intuitive, it will result in low usability score. All of the above will result in lower conversion therefore lower revenue. According to studies, many online shoppers give up and abandon the shopping process due to usability issues.

Web analytics must be viewed as an activity directly tied to revenue. It is indeed a revenue generating process. The absence of web analytics can result in loss of revenue, and the presence of it will almost certainly result in increased revenue.