A What-Not-To-Do Case Study

Our assignment this week asked us to research a company and report of their analytics efforts. I am choosing to keep the organization I researched private, but will report my findings nonetheless.

The organization I chose has no brick-and-mortar presence, but sells a wealth of products online via its website. The company uses two different tools for website analytics: Webtrends and Google Analytics. Webtrends was implemented by the IT department as the primary analytics tool. Ownership of the website resides in the sales department and focuses on business goals at the 30,000-foot perspective. Below are two examples of the monthly Webtrends reports that the website owner submits to executive management to illustrate website success.

This report focuses on very basic website statistics such as visits, page views, visit duration, bounce rate, visitor location (domestic or international) and new or returning visitors. It highlights three months of statistics.  This report does not provide information about website sales, traffic patterns, popular pages, or referral traffic.

This second report focuses on website traffic by region.  Unfortunately, it does not delve into the behaviors, purchase or traffic patterns, or additional demographic or psychographics of these visitors.

These reports appear to have been developed using Webtrends by the website owner, but offer little in terms of actionable data.  Below is another example of a customized Webtrends report developed by the website owner. This report shows one of the sales funnels, which have been set up for some of the business lines (books, collections, membership, paid video, papers, standards, and training/education). At first glance, these reports appear to have the potential to be very useful. Until you look closer. Notice that the number goes UP between the third and fourth steps of the funnel.  Clearly, these funnels are not set up properly, or there are issues with the purchase path itself. If this could be remedied, these sales funnels would allow SAE to determine where people are abandoning the purchase process and evaluate those steps/pages and make adjustments to improve conversions.  However, there is one additional issues with the way these funnels are set up. There is no way to determine where traffic originates from, so even if the funnel and/or purchase path issue were to be resolved, this data would still be lacking some key information.

So, Google Analytics was implemented at the request of the marketing department in an effort to better capture data related to marketing efforts. With Google Analytics, traffic from online advertising campaigns can be tracked. 

There are a number of ways that this organization could improve website analytics efforts. Correcting the Webtrends sales funnel reports would be a significant improvement, which would allow the organization to evaluate where and why people are abandoning their purchase part way through the process and make adjustments.

Another big improvement would be to add options for segmentation of sales funnel conversions. Segmenting by referral traffic would provide an opportunity to evaluate each traffic source separately and determine which channels are converting to sales, and which are not. Segmenting by location would allow the organization to evaluate the effectiveness of regional promotional efforts related to organizational goals.

It would be helpful to produce reports detailing sales and other conversions from the website so that executives, and the rest of the staff, can see how marketing and sales efforts are converting month-over-month, and year-over-year.

Finally, it would be useful to set up conversion tracking, via Google Analytics and/or Webtrends, to understand customer engagement beyond the exchange of money. Since many products this organization sells have high price tags and require commitment at the enterprise level, it would be very useful to track other conversions that can ultimately lead to an eventual sale.