Web Analytics and Broader Applications
In this week's lectures we discussed both web analytics in general and the google analytics platform specifically.
In Lecture 9 we define web analytics as the analysis of data obtained through a website. This data is usually collected via cookies which record a visitor's activity as they access, navigate through, interact with, and eventually leave an organization's website. Once collected, we can use the Web Analytics Cycle to process and analyze the collected data. This includes setting goals for the organization, determining if those goals are being met, gathering reports on the collected web data, analyzing those reports, and making recommendations to improve the organization's website/s to meet those goals. We utilize the 5 "w's" in analyzing web data: who, what, when, where, and why (we also capture how, which has some uses I will discuss later).
In Lecture 10 we walk through the Google Analytics platform. Google Analytics is a free web analytics package used to track web data and provide pre-built and custom reporting on the collected data. There's a metric ton of reporting available through Google Analytics; you can view exit and bounce rates, examine the actual page flow of visors to the site, view geographic information, see engagement based on how long users stay on various parts of the site, even view where traffic is directed from with a view on search engine optimization.
We tend to think of application of web analytics in a commercial frame; how to drive traffic to a website, how to encourage users to stay longer, view more ads click on more monetized links. But there are far broader applications possible. Coming into this unit I was actually familiar with Google Analytics as my until last Friday employer used it extensively to monitor traffic to our web app. My former company wasn't commercial; we were an education technology company that provided a test and content delivery environment for students and metrics and reporting tools for teacher and administrators. How did Google Analytics help us as company? More importantly, how did Google Analytics help me as the Quality Assurance Associate?
By comparing the time users spent on certain pages, for example, we were able to better pinpoint areas that were affected by performance issues. We also used bounce and exit rates to confirm anecdotal reports from clients about usability. If the performance or UI of a page was sub-par, that reflected in the amount of time a user spent on that page. Let's say we received calls from a clients complaining about a feature' redesign. We could then look at our analytics and see that if the bounce rate for that age was high, or the time spent too low, that there was an actual issue with UI that needed to be addressed; it helped us weed out legitimate issues from complaints. Similarly when performance issues were reported, we could see our active users, helping us to establish a threshold for performance. We can also see how long they spent on each page, which help us gauge the extent of the issues.
As for my role in QA, Google Analytics helped me immensely in targeting my testing based on real world conditions. The company did not have user surveys, or any way for QA to ever discuss with clients the actual conditions within which they used the app, so Google Analytics was able to fill that role. At a glance I could tell for example, which browsers our clients used for what parts of the app, which assisted in targeting my testing. Over the past two years the share of individuals using Safari and IE dropped precipitously, so I was able to justify dropping those browsers from testing. The ability to see how users logged in was also essential. Because no two school districts use the same materials, the Google Analytics device data helped me pinpoint exactly what devices I would need in order to full test our features, and helped me defend resource allocation and new device acquisition. For example as our share of students logging in via Chromebooks increased I was able to defend a large purchase of various Chromebook devices for testing. Similarly when a number of new clients purchased multiple Kindle Fire tablets for testing, that data came in handy as I requisitioned the purchasing of Kindle Fires.
So as you can see, the real world applications of Google Analytics are very vast, and I promote these tools so much I should draw a paycheck from Google haha. What about you? Have you used Google Analytics before? What novel applications of the data did you find?
As for my role in QA, Google Analytics helped me immensely in targeting my testing based on real world conditions. The company did not have user surveys, or any way for QA to ever discuss with clients the actual conditions within which they used the app, so Google Analytics was able to fill that role. At a glance I could tell for example, which browsers our clients used for what parts of the app, which assisted in targeting my testing. Over the past two years the share of individuals using Safari and IE dropped precipitously, so I was able to justify dropping those browsers from testing. The ability to see how users logged in was also essential. Because no two school districts use the same materials, the Google Analytics device data helped me pinpoint exactly what devices I would need in order to full test our features, and helped me defend resource allocation and new device acquisition. For example as our share of students logging in via Chromebooks increased I was able to defend a large purchase of various Chromebook devices for testing. Similarly when a number of new clients purchased multiple Kindle Fire tablets for testing, that data came in handy as I requisitioned the purchasing of Kindle Fires.
So as you can see, the real world applications of Google Analytics are very vast, and I promote these tools so much I should draw a paycheck from Google haha. What about you? Have you used Google Analytics before? What novel applications of the data did you find?
Anson,
ReplyDeleteI have very much enjoyed your posts and articles and blogs up to this point! Thank you. With the flattery out of the way :) Appreciate you bringing the different perspective of the use of Google analytics. As a newbie and as you mentioned I thought of GA being used to track " how to drive traffic to a website, how to encourage users to stay longer, view more ads click on more monetized links." Your former employment has given you another example of how GA can be used effectively. Being a quality Assurance guy it sounds like that portion of GA was invaluable! I do a little of that work (jack of all trades). Your example of a customer complaining about an issue in a section is common in my area. Going off of "what he/she said" (not like in The Office :)
) is frustrating as I often roll my eyes and assume it is a user error because they didn't click the right series of buttons. Google Analytics gave you the ability to pinpoint that section and see where the customer was referencing, so cool! Although many of my programs are desktop applications, nice to hear you were able to benefit! I also like the piece of time saving which came from the internet browser frequency. What a time saver not having to test everything in two additional browsers! Thanks again for your perspective on this topic as well as your others.
I have a mantra I always reference: UI is like a joke. If you have to explain it, it's not very good.
DeleteIf the customer didn't hit the right sequence of clicks, the feature/website/etc isn't intuitive enough and should be reworked ;)
But that's why I do QA.