Diving into Google Analytics

About one week ago, I successfully installed Google Analytics on my blog and have approached promoting it in two ways:

1. I directly asked friends to visit the site by sharing the link with them over the chatting service Google Hangouts.

2. I posted a link on my Facebook page requesting friends to visit the site.

Given my two promotional efforts, the data generated by my analytics was not surprising. I explored a number of areas, but in this post I will cover Traffic Sources, Demographics, Technology, and Visitors Flow.

Traffic Sources:

Google Analytics tracks what sources are driving traffic to a specific website. In the case of my website, I can see that Facebook was the largest source of traffic; direct traffic was the second largest; Blogger referrals were the third largest and mobile Facebook referrals were the fourth largest source. The results were not surprising as they more or less mirrored my promotional efforts.

In addition to just basic information on where the visitors came from, Google Analytics also provides information on pages viewed per visit as well as the average visit duration, percentage of new visits, and the bounce rate. The metrics show me that for the people who visited from Facebook, they almost all left immediately; this was probably because I posted, along with the link, that I only needed friends to visit the site for traffic purposes. It would have been a better tactic to arouse interest in the site on Facebook by providing information about the site and subsequently attracting readers who would be interested in the content of the blog. The direct traffic average visit time was longer, but overall, hardly anyone spent any time on the site at all.

In a professional setting, the information provided in the Traffic Sources section can be extremely valuable. The source visits help marketing managers identify what communication campaigns are working and what campaigns are less effective. The overall number of visitors compared with the average visit duration and bounce rate can confirm or raise questions on the quality of the traffic. For example, if a source referred a lot of visitors but none of them stayed for long, then that source is obviously attracting the wrong type of visitor to the site.

Demographics: Location

Another web metric that I found particularly interesting is the location data under the demographics section. Google Analytics provides location data that can be broken down into four dimensions: Country/Territory, City, Continent, and Sub-Continent Region. While I was familiar with Google’s ability to provide data on country (I was familiar with this by exploring the analytics section of YouTube on my channel page) I did not know that GA also provides information broken down by city.

The business application of knowing where website visitors are coming from can be helpful for a number of reasons. To start, it provides a big picture overview of where visitors are coming from. This data could help drive investments decisions on whether to invest in local language versions of a website for countries that are large sources of traffic. The ability to break down the data by city can measure the effectiveness of marketing efforts in certain areas. To give an example, a company could measure the results of a one-time marketing campaign at a large event in New York City.

At the top of the page, there is a tab to switch between site usage and ecommerce. By switching to ecommerce, the map will provide information on how the website’s ecommerce activity is divided up by location. Depending on a company’s objectives for being on the web (i.e. informational vs. commercial), knowing how each geographic area contributes from a financial standpoint is likely more important than just knowing the web usage statistics.

Technology

Google Analytics provides statistics on various metrics of the technology used to access a site. To start, GA gives a breakdown of the different operating systems used by visitors. The browser data can be used to decide where to allocate resources for web browser optimization. If, for example, the majority of web activity is coming from Chrome, Chrome optimization will be of high-priority in the update and testing cycle.  

In addition to browser information, GA provides statistics on the visitors’ operating system, screen resolution, screen colors, Flash version, and Java Support. These statistics are useful for similar reasons as the knowing what browser visitors are using to arrive at a site: they should be taken into considering when optimizing the site to make sure it accessible to all visitors. In particular, the Flash version would be important to know for each visitor, as efforts should be made to have Flash content be accessible to the largest group of people possible (if it is crucial to the webpage experience).  

Visitors Flow

The Visitor Flow metric was not particularly interesting for my website, as the website is rather simplistic in nature and the engagement of my visitors to date has been extremely low. However, for more complex sites with clear conversion goals, I see this metric and visual overview as being both interesting and helpful.

The Visitor Flow provides a visual overview of exactly how visitors are engaging with the site by providing marked drop points and visual paths showing where visitors are going on the site. The paths can be broken down by country, browser, traffic source, and just about any other metric.

An application of Visitor Flow is that it can allow insight in to how or why visitors are not converting in a desired manner. For example, it is possible to break down the Visitor Flow to show paid search traffic, by social media sites, by just advertising, by landing pages, and more (Kerschbaum, 2013). By examining how visitors from certain metrics flow through the site, managers have better insight on why the visitors are or are not doing what they are supposed to be doing. Additionally, Visitor Flow can reveal that different sources bring different types of traffic. For example, a visitor from a mobile device might interact with the site different than a visitor from a desktop device. Additionally, a visitor from a pay per click ad might interact with the site differently than a visitor who arrived at the site through a social media link.