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Metrics vs Dimensions in Google Analytics

Post Overview

When you first start working with Google Analytics one of the tougher distinctions to wrap your head around is the difference between metrics and dimensions.

Metrics and dimensions are pretty much the most important concepts to understand since Google Analytics uses them pretty much everywhere. To use the tool effectively requires an understanding of how the two terms are used specifically to Google Analytics.

Google Analytics uses these two terms in a specific manner so if you have previous experience with these terms, the two words may not mean exactly what you are expecting.

First Steps

The first things to realize is that you are going to see metrics and dimensions everywhere in the program. You can’t hide from the two terms. So you need to just begin figuring out the best way to differentiate the two.

The place you will see the two terms most obviously is in the data tables that form the core basis of pretty much every report, so that is as good a place to start as any.

In the context of the data tables, an easy way to distinguish between the two terms is just to think about the them as they appear on the data table view in the various reports.

Dimensions are the rows.

Metrics are the columns.

A simplistic approach, yes, but one that works very well when you starting out with Google Analytics. Especially as you consider how the data table view is laid out, you can use that context to begin to internalize the difference. A simple question you can ask yourself is whether something would be a row or a column in the data table view.

The rows are descriptive characteristics of the data. They are a quality of the data. They are something that data contains.

The columns are the actual quantities of the data, how much and to what degree and how often, the totals and percentages associated with a particular characteristic. They can be broken down into discrete quantities.

Dimensions are the characteristics of the analysis.

Metrics are the most quantitative belonging to the characteristics.

The longer you work with these data tables, the more you will begin to internalize the differences.

Moving toward abstraction

As you begin to work with Google Analytics more and more, you will begin to internalize the concepts,and think of the differences between metric and dimensions in more abstract terms. Once you grasp the essential nature of a metric or a dimension and what defines one versus the other, you will begin to see the opportunities that exist in breaking apart the data and segmenting your visitor traffic in ways that are specific to your business goals and processes.

At this point you will have moved to the next level and will be leveraging the application in completely custom ways. Your understanding of the differences between metrics and dimensions will allow you to imagine new dimensions and metrics that have not been pre-created for you. Eventually you will know how implement those new metrics and dimensions as custom metrics and dimensions and use them in your own reports. At this point you are creating a truly custom analytics experience and will really begin leveraging your internal data.

On this abstract level you can think of dimensions as the big picture topics that you want to use as part of your data analysis. What characteristics of your web traffic is most important and helpful to your business.

Pre- created dimensions such as Country Traffic and Device type will always have value but the more specific ones you create will be based on your business needs and resonate much more powerfully within your organization.

In that context your metrics become the detailed occurrences about these big picture topics.

Scope

When talking about metrics and dimensions it is very important to consider the scope of each. Without understanding how scope works you will be very limited in your ability to take advantage of the tools provided by he application.

Scope is simply a fancy word for context and context is really just fancy word for container. Scope is the container in which something functions. It is the context in which something has meaning.

Both metrics and dimensions have specific scopes on which they have context. In order for one to be useful to the other both the metric and dimension must operate within the same scope.

To put it another way, if your metric has function in one.container and your dimensions has function in a different container then they will not be able to work very well together since they are isolated into their separate containers.

Therefore, to work together, your metrics and dimensions have to live within the same container.

In other words they have to belong to the same scope.

There are three types of scope for both metrics and dimensions:

Hit level

A hit level scope is a single action that results from a users interaction with the site. An example of a hit level scope is the loading of a page.

Session level

A session level scope is what occurs with the context of a users session.

User level

User level scope is something that is specific to a user independent of the site. So for example a users browser version would be considered part of the user level scope

Wrapping up

Hopefully this gives some sense not only of what constitutes a metric or a dimensions in Google Analytics but also why it matters. Once you understand metrics and dimensions you pretty much understand the application but in terms of how to lever late it’s prebuilt reporting capabilities but how to create your own as well.