Week 6 assignment: Traffic parameters

For this week’s assignment, I set up three goals on my blog. The first goal measured visitors to a specific page (last week’s post); second was visit duration over 30 seconds; and third was pages visited. My rationale for these goals stemmed from measuring the popularity of new content; whether that content was interesting enough for visitors to feel engaged; and whether the content interested visitors enough to visit other posts and read more.

For my new position at a community bank, I am interested in creating traffic parameters for an online banking page on our website, which is currently being built. To start off, I believe measuring URL destination and traffic sources will be most important for understanding the effectiveness of related marketing campaigns. Enlisting funnels will allow me to determine the success of the user experience through the process and filters will pinpoint if users are coming from the locations I would like or expect them to be coming from (Sparks, 2010).

Goals

The first goal will be to measure sign ups for the online banking service. Success will be measured by setting up a URL destination goal for the “confirmation” or “thank you” page, which users will be directed to after completing the signup process. An increased number of online banking signups will result in “sales” in the form of increased deposits and decreased printing and paper costs of statements formerly mailed to account holders. Ideally, enquiries from prospective clients will also be generated if users landed on the online banking page from an organic search or from an email marketing campaign. How current and prospective clients found the site can be tracked by setting up a funnel process in Google Analytics. If the minimum amount required to open an online account is a $15 deposit, I can enter $15 for the goal value to get an overall value. To measure the goal value of other pages like newsletter signups, I would need to evaluate how often the visitors who complete the Goal become customers (Google Analytics, 2013). If account managers can close 10% of people who sign up for a newsletter, and the average balance is $500, I would then assign $50 (i.e. 10% of $500) to the Newsletter sign-up Goal (Google Analytics, 2013).

Funnels

By knowing “which steps of the process woos customers” (Goals, 2013), I can understand where customers are entering and abandoning the signup process and create or tweak a more efficient process. For example, by analyzing the account opening funnel and removing some of the requirements fields (requesting the same information twice or including a captcha that is too difficult to complete (Ran, 2009), I can better understand where users are experiencing difficulty, which could lead to abandoning the process.

Goal funnels will only work if visitors are required to move through a series of pages. “Unless required, visitors seldom follow a clear path on your site and a goal funnel won’t help you make any sense of how your visitors move from page to page” Lofgren (2013).  Another useful tool is the Reverse Goal Path report, which indicates if visitors are reaching your goal page through a path that you did not anticipate (Lofgren, 2012).

Fortunately, an online account signup path is being constructed for the new website; however, if this were not the case, Google Analytics’ Visitors Flow report or another program such as Crazy Eggs’ Heat Map could track a user’s progress through the site.

While goals are important for understanding conversation, Funnels are “as essential” (Lofren, 2012), as they serve by themselves more as basic KPIs (key performance indicators) than as actionable starting points for conversion optimization.

Filters

Creating filters provide accurate reports that are not skewed by internal traffic or not relevant if coming from regions outside of the bank’s target area. For the online banking page, there are three necessary filters that should be created. The first would exclude internal traffic (employees and staff visiting the page); another would exclude traffic from regions and cities outside the bank’s target market; and yet another would be a Full Referral URL filter for affiliated sites that may provide multiple references and links to the bank’s website. Knowing which page visitors were linking from would show whether a storytelling content page from the affiliate site was more effective or if a URL link was providing the most traffic. Understanding which reference was more effective would be beneficial for tailoring future affiliate marketing initiatives. Including the “lowercase” filter is also important so that the reports are not perceived as two different unique views when in reality they are not (Nurelm, 2010).

Streiner (2012) suggests setting up a new profile or “at least one profile in your account that does not contain any filters” since Google Analytics does not provide a method to go back and track the data that was filtered out.  Creating a new profile each time a filter is added would provide better segmentation of results and allow for comparisons across filters or over time.

References

Goals in Google Analytics. (2013). Google Analytics IQ lessons. Retrieved February 23, 2013 from http://www.google.com/analytics/iq.html

Google Analytics. (2013). Conversions: About goals. Retrieved February 23, 2013 from http://support.google.com/analytics/bin/answer.py?hl=en&answer=1012040

Lofren, L. (2012). The Google Analytics Conversion Funnel Survival Guide. KISSMetrics. Retrieved February 23, 2013 from http://blog.kissmetrics.com/conversion-funnel-survival-guide/

Lofgren, L. (2013).  4 Google Analytics Goal Types That Are Critical To Your Business. KISSMetrics. Retrieved February 23, 2013 from http://blog.kissmetrics.com/critical-goal-types/

Nurelm. (2010, November 29). Four Google Analytics Filters You Should Be Using. Retrieved February 23, 2013 from http://www.nurelm.com/themanual/2010/11/29/four-google-analytics-filters-you-should-be-using/

PI Reed School of Journalism. (2013). Lesson 6: Successful approaches in Google Analytics. Retrieved February 23, 2013 from ecampus.wvu.edu

Ran. (2009, March 4). 10 must track Google Analytics goals. Web Analytics World. Retrieved February 23, 2013 from http://www.webanalyticsworld.net/2009/03/10-must-track-google-analytics-goals.html

Sparks, D. (2010, March 14). Google Analytics in depth: Funnels and Goals. Six Revisions. Retrieved February 23, 2013 from http://sixrevisions.com/tools/google-analytics-in-depth-goals-and-funnels/

Steiner, J. (2013, February 2). Google Analytics filters and filtering. More Visibility. Retrieved February 23, 2013 from http://www.morevisibility.com/analyticsblog/google-analytics-filters-filtering.html