Web analytics at quality alloys inc case solution

an executive summary, one to two pages in length. It should summarize results and provide recommendations to QA managers as to how they might best market their business with an aim towards improving sales. Your recommendations may rely on your knowledge and experience beyond the case, but your suggestions must be supported by the data and your analyses. (You may, and probably should, do additional analyses other than those required here. You should at least review all the data.) You can use the questions from the Company Background section of this document on page three as a guide for what your summary should cover. Finally, note that this is a “real-world” case; that is, depending on your analysis you may not have all the data you want. You may certainly include as part of your recommendations that additional data be collected.

Web Analytics
QA’s website developer utilized Google Analytics (http://www.google.com/analytics/), a free web analytics tool so that the site would track, and QA management would have access to, a wide variety of web metrics. Google Analytics is implemented by putting the appropriate code, provided by Google, on each web page. The data collected is sent to Google; users, like QA managers, access it by logging in to their Google Analytics account. Typical metrics include the number of visitors to a site, the amount of time they spent on the site, the number of pages viewed, etc.

Apart from Google Analytics, QA participated in Google’s AdWords program.5 AdWords ads are the “sponsored links” that appear next to, and sometimes above, Google search results. That is, QA paid to have these ads (with links to the QA website) appear on the Google search result page when relevant search terms (specified by QA) were used.

Website Visits
Figure 1 is a plot of the number of visits to the QA website per week over the period May 25, 2008–August 29, 2009. The start date was the first full week the website was available to visitors. The end date was selected as it coincided roughly with the launch of another QA website, which had the potential of affecting the data at the primary website. The time frame includes the direct mail brochure promotion sent during December 2008.

FIGURE 1. VISITS TO THE QA WEBSITE PER WEEK.

The entire time frame has been divided into four sections. The first comprises the “initial” or “break-in” period for the website. The second, established when visits appear to stabilize at a roughly constant level, is the “pre-promotion” interval. The “promotion” period begins

Page 3 | Web Analytics at Quality Alloys, Inc.

shortly after QA’s promotion took place and website visits dramatically increased. The final period, “post-promotion,” begins when visits appear to level off again. Two points are worth noting. First, it seems clear from both the data and feedback from QA management that this general partitioning makes sense. For example, website data through May 2010 (not provided here) indicate that visits remained approximately at the same level as the post- promotion period; it can be reasonably assumed therefore that the jump associated with the promotion period is not due to some seasonal variation or external economic factor. Second, while there is some arbitrariness about the exact cutoffs between periods, varying them in any reasonable way does not impact the analysis.