Module 2 Blog Post

 Hello and thank you in advance for reading my blog post on Module 2. In Module 2, we covered web analytics and Google Analytics. I found these topics to be fascinating and benefitted from the Sun Microsystems reading on web metrics, the web analytics definitions reading, the Google Analytics tutorial reading, and the 19 differences reading. It was really interesting to start with the Sun Microsystems reading on web metrics showing all the different ways to configure your analytics tracking and then I capped the week off with completing Assignment III using Google Analytics where there are many default metrics already in place for off the shelf capabilities. In the Sun Microsystems reading, the author/presenter, Paul Strupp Ph.D, breaks down the different cost structures for monitoring web metrics at the time. I'm not positive of the date of the presentation but I'm assuming it's pre-Google Analytics. I wonder what the true cost of using Google Analytics truly is. I understand it is free to use and has enterprise level to entry level use availability and application. However, I wonder what Google gets out of it long term. 

There could be multiple long term benefits such as brand loyalty or even a switch in the future to a pay for use structure. Nevertheless, I found the Google Analytics (GA) website to be intuitive, easy to use, fast, and I was impressed with the default measurements/comparisons/reports already in place. Granted, I was using GA to review the Google Merchandise Store and Google uses both the store and the GA of the store as a teaching mechanism and showcase of GA. I wonder how GA would work with setting it up for a website for the first time and what kind of learning curve is associated with it. 

I agree with Dr. Ram in that the web analytics cycle seems to be very similar to the Business Intelligence life cycle. Web analytics follows the process of setting goals, determining how to measure the goals, measuring progress, reported on the measurements, analyzing and then optimizing. Rinse and Repeat. Web analytics relies on a plethora of web metrics, which can be counts, ratios, aggregates, or individual points. Web analytics can be used to measure direct traffic, organic traffic, referrals, or paid traffic. By the way, I thought it was interesting that Google Analytics grouped social media referrals and web referrals in separate categories. 

The assignment, readings, and lecture served to allow me to think deeper about web analytics and ideas such as unique user/returning user/new user in ways that I only scratched the surface on previously. I would like to explore different web analytic tools that exist to compare them with Google Analytics. I would love to deeper into the subject in this class or in the future as well!

Sincerely, 

Josh Edwards

Comments

  1. AnonymousOctober 3, 2023 at 7:39 AM

    Hi Josh,

    Like you, I felt this was an enlightening week. I only had an elementary idea of web analytics and was interesting to learn how in-depth and data-rich web analytics is. I found an example where the results of web analytics were put into a predictive model to generate even more insights. A company used web analytics to extract user behavior and used a predictive model to formulate personalized marketing (Widen, 2020). This is just another example of how web analytics is used for short and long-term goal planning (Widen, 2020).

    Widen, S. (2020). “Predictive Web Analytics in Marketing.” Forbes.com. https://www.forbes.com/sites/forbesagencycouncil/2020/02/10/predictive-web-analytics-in-marketing/?sh=7d83f31810f4.

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  2. AnonymousOctober 3, 2023 at 8:18 PM

    Hello Josh, I liked the question you raised about how the cost may have changed from the time when Paul Stupp Ph.D created his introduction to web metrics. Technology has vastly changed and there are tools like Google Analytics that can be easily used. Using Google I found the publication date to be 2005, cited below. Knowing this, I think the cost has vastly changed and companies can utilize tools that have been created instead of having to take in the metrics and analyze them on their own. I agree with you that the Google Analytics website is intuitive, easy to use, and fast to learn. I think when businesses implement this they can utilize the easy-to-learn platform quickly and not have to extensively train their employees. I believe that when a website starts to use Google Analytics it takes time to gather information because it will not start tracking until Google Analytics is implemented for the customer's website. This raises the question for me if Google keeps the data they have gathered if a contract ends or if the web data is deleted if a customer stops tracking their website. The web analytics cycle and Business Intelligence life cycle are very similar and they both seem to focus on continual improvement as they are continuous cycles. I think in future years web referrals and social media referrals will be separated out to provide the most information to the users analyzing the website. As many companies are spending vast amounts of money on promoting through social media, it is important for them to understand what their return on investment is. I agree with you that this week we only scratched the surface of the vast information about website analytics and how the metrics can be used. It would be interesting to understand what Google Analytics' top competitor is because when researching website analytics Google Analytics is a very popular option to be presented in numerous articles, and blogs.

    Paul G. Strupp, Presentation, ARL Web Analytics Workshop (Webmetrics), 2005 ALA Annual Conference, Chicago, IL, June 23-29, 2005

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  3. AnonymousOctober 7, 2023 at 6:39 PM

    Hello! I thoroughly enjoyed reading your blog post on Module 2 and appreciate your insights on web analytics and Google Analytics. I agree that the readings, especially the Sun Microsystems piece, provided valuable perspectives on web metrics, and it's intriguing to consider the evolving landscape of analytics, especially in comparison to the more established Google Analytics platform. Your curiosity about the true long-term cost of using Google Analytics is a valid point, and I share your wonder about what Google's future plans might be. The Business Intelligence Lifecycle and the web analytics cycle are very similar. They share the want for continuous improvement. I'm also eager to explore other web analytic tools and deepen our understanding of the subject in this class or beyond. Great post!

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