Any data collection and analysis tool is just garbage in and garbage out if you are unable to convert the data into actionable insights. There are numerous ways through which you can convert your Google Analytics data into actionable insights. Some of these techniques may include exporting your Google Analytics data into statistical tools such as SPSS.
Since there are so many tools at your disposal, it is important to understand which tool to use in a given situation. In our Google Analytics Courses, we take practical examples and exercises that teach you how to leverage appropriate techniques, so you can dig deeper into your data. Regardless of the method you use to slice-and-dice your Google Analytics data, you will first need to understand how data is organized in Google Analytics. In this article, I will shed some light on how the basic report structure works in Google Analytics.
Metrics and Dimensions in Google Analytics:
A metric is defined as a numerical measure of the user interaction on your website. Metrics have the following characteristics:
Characteristics of Metrics
Metrics will always be expressed in form of a number.
Metrics are stand-alone entities. When you look at a metric in a stand-alone fashion it provides you with information about the site-wide performance.
Metrics will form the columns of a report structure in Google Analytics.
Some of the common metrics you will find in Google Analytics are visits, pageviews, bounce rate, etc.
Dimensions,on the other hand, have the following characteristics:
Characteristics of Dimensions
Dimensions are non-numerical data fields.
Unlike metrics, dimensions are not stand-alone entities, i.e., dimensions are not generally meaningful when viewed individually.
Dimensions, when coupled with metrics, provide meaningful context to the data.
Dimensions can be used to segment a metric.
The following example should help you understand the above concepts:
In the above screenshot, you can see that the stand-alone metrics allow you to compare their performance with overall site average. In the above example, I am sharing a screenshot from the Referring Sites report found in the Traffic Sources category in Google Analytics. In this case, the stand-alone metric, Visits, indicates that 655 visits are coming from different referring sites and constitute 9.53% of the overall traffic.
The above screenshot also highlights the default dimension in the report. In this case, the default dimension is called Source. As highlighted in the above screenshot, the dimensions are forming the rows of this report structure and the metrics are forming the columns.
A good grasp on how metrics and dimensions work in Google Analytics is essential, especially if you want to learn how to leverage Custom Advanced Segment and Custom Reports in Google Analtyics. We cover these topics in great detail in our Google Analytics Advanced Course.
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