Goals, Filters, Funnels in Google Analytics

Every website on the World Wide Web is comprised of a series of single pages that all together form a series of steps. During a customer’s online journey, an individual typically navigates through a hierarchical structure of page views. Web Developers refer to a websites entire page-listing directory as a site map.

Without a clearly defined site map, navigation between pages would most likely be misunderstood and broken, which could result in a negative customer experience.

Depending on the website type, a customers action steps might vary. For a web analyst of an e-commerce site, conversion would be a metric goal worth analyzing. For a non-e-commerce site, such as my blog, data collection and site visits would be other metrics of concern.

By establishing goals, funnels, and filters using the tools in the Google Analytics platform, a web analyst, or a novice like myself, would be able to offer key stakeholders transparent metrics about what is and what is not working within the site map of a website. 

Goals

Forrester Research describes socially inclined consumers as the Groundswell, and understanding the impression a website has on these forward thinkers is vitally important to a brand now more than ever (Forrester, 2012).

In the case of web analytics, a goal is defined as a setting that counts each completion of a specific task on a website (Emerson, 2011).  Every task counted indicates how well a website is contributing to the overall company bottom line. Determining what tasks are desired and the action steps required by customers should be considered before any goals are established in Google Analytics (Emerson, 2011).

Once a decision has been made on the key performance indicators (goals), a Web Analyst would be able to define the following goals: URL Destination, Average Time on Site, Pages/Visit, and Event Goals. The maximum amount of goals per profile is twenty (4 goal sets, and 5 goals per set) (Gabe, 2012).

In the case of my school SEO/Web Analytics blog, I established three conversion goals types that included: Pages/Visit, URL Destination, and Pages Per Visit.

Pages/Visit is an engagement goal type that triggers a conversion when a user visits a certain number of pages (Gabe, 2012). This goal can be set to greater than, equal to, or less than a number of pages, based on what needs to be tracked (Gabe, 2012).

URL Destination is another engagement goal that tracks if a user visits a certain page on a website after completing an action (Gabe, 2012).

In an effort to increase referring traffic to my blog, I wrote a post for the WVU Student Blog with a call to action back to my personal blog. Based on that prompt, I noticed an up-tick in my goal completions for both URL Destination and Page/Visit.

One other area for my to leverage in Google Analytics is the event tool. By establishing an event on my blog would be a powerful way for me to holistically identify a specific visitors actions. The actions of an event could include the following: downloads, video views, clicks on specific links, button clicks, etc (Gabe, 2012).

Based upon the metrics pictured above, I need to continue to look for other opportunities to increase my referral traffic. One way to visualize the referral traffic coming from goals is by implementing funnels within Google Analytics.

Funnels

Funnels and goals can happen in tandem during the goal implementation process. “Funnels will restrict the amount of completed goals to only those who follow through the entire pathway”(Rocheleau, 2012). The benefit of adding funnels will provide much more purpose if chosen goals require a set of intended paths (Rocheleau, 2012).

In addition,“Another option for viewing funnel data is the Goal Flow report, which is in some ways similar to the Funnel Visualization” (Kissmetrics, 2012).

“Goal Flow is somewhat more flexible and detailed and does allow Advanced Segments, but it does not calculate a single funnel conversion rate metric and generally requires a bit more interpretation” (Kissmetrics, 2012).

Based on the image detailing my current goal flow, I am able to discern that I have successfully captured one visit by the blogger.com referrer. The next step of measuring success on my blog is by establishing filters.

Filters

In order to capture web metrics on a webpage, it is necessary to filter out any bias from the subsequent reporting data. By leveraging, Google Analytics filters, a web analyst could include or exclude the following:  a network, pay per click traffic, organic traffic, or sub domain traffic (Overland, 2009).

Google frowns upon setting up more than one filter because, “Adding more than one Include filter to a profile can cause data to not appear in your reports. To allow data to populate your reports again, Google recommends assigning a maximum of one Include filter to each of your profiles” (Alexander, 2011).

Best practices indicate that filters should not be applied to existing profiles. Instead, a new profile should be created in order to ensure that the proper data is captured (Alexander, 2011).

In the case of my Web Analytics/SEO blog, I setup a filter during week six that now filters out my personal network IP address.  If this filter had been established when I paired the Google Analytics tracking code to my blog I would have now be looking at unbiased metrics.

By leveraging the filtering data tool, I am now able to segment and manipulate any future data streams coming into my GA account.

In addition to filters, an e-commerce web producer should perform housekeeping on the site map to ensure that individual pages are named appropriately; otherwise page names will be unrecognizable in a goals report, and any subsequent data would not provide full transparency on traffic patterns (Emerson, 2011).

Every website is a living canvas that can always be updated, tweaked and enhanced. With the tools available in Google Analytics such as filters, funnels and goals, a web team would be able to continue to improve the hierarchy structure defining their web presence.

Resources

Alexander, Dorcas. (2011). How to use more than one include filter (without losing data). Retrieved February 24, 2013

http://www.lunametrics.com/blog/2011/06/24/more-than-one-include-filter/

Gabe, Glenn. (2012). A beginner’s guide to conversion goals in google analytics.

Retrieved February 25, 2013

http://www.searchenginejournal.com/a-beginners-guide-to-conversion-goals-in-google-analytics/42558/

Overland, Helen. (2009). Google analytics filter best practices. Retrieved February 24, 2013

http://www.searchenginepeople.com/blog/google-analytics-filter-best-practices.html

Retrieved February 25, 2013

http://empowered.forrester.com/groundswell/book.html

Retrieved February 25, 2013
http://blog.kissmetrics.com/conversion-funnel-survival-guide/

Rocheleau, Jake. (2012). A guide to: goals and funnels in google analytics. Retrieved February 25, 2013

http://www.hongkiat.com/blog/google-analytics-goals-funnels-tips/