Once, in elementary school, one of my teachers gave a very popular lesson on graphs using candy. She gave groups of us students bags of skittles and asked us to count how many of each color of skittle we had in our packets. On the chalkboard was a big empty X-Y axis. On the X axis was a list of all of the colors possible in a bag of skittles. We then had to mark an X above each color label on a plot for every skittle we had that matched that color label.
The X-axis, or the color of the skittle, was the dimension of the data – the attribute by which the teacher had us sort the “data” – i.e., skittles. The number of skittles of each color – that’s the metric.
All of the reports you make in Google Analytics can be thought of in this same dimension vs. metric framework. You can save yourself a lot of trouble with imprecise reports by remembering to ask yourself what dimension and metric you’re interested in, and whether the metric makes sense for that dimension.
Let me show you some examples
Take a look at the default reports in Analytics. See if you can identify both the dimension and the metric.
Here’s the audience overview report – probably one of the most familiar reports in Analytics.
The metric is obvious – visits – but what’s the dimension? Time! Specifically, in this graph, the dimension is “day”. Although in dashboards you can change some graph orientations, by default, graphs in Analytics have the dimensions on the horizontal axis and the metric on the vertical axis.
Let’s look at something a bit more complicated. This is a source report.
You can see the dimension on the left hand column of the table – the visit source. But what’s the metric? In this report there are actually multiple metrics. All of the columns besides the left hand column are metrics. This layout is also pretty consistent across Analytics – the dimension is in the left column, and any metrics are to the right.
- Unique Visitors
- Goal Conversions
- Geography (City, Metro, Region, Country)
- Browser and Operating System
- Source and Medium
MacGyvering dimensions with advanced segments
If you haven’t checked out advanced segments yet, then oh my goodness, you really, really should. They’re awesome. I think my mind was kind of blown when I first discovered them. I basically thought they were the answer to everything. It turns out that they’re not (more on that in a future post), but they are pretty darn powerful.
So what are they? They’re basically a way to look at a specific subset of your data identified via certain criteria that you specify – across all of your reports. So you can say, “I want to look at all of the paid search visits in California that landed on this landing page”, and then look at that same group of visits across all of your reports and dashboards. But there’s something else that makes advanced segments even cooler – and relevant to this article.
You can look at multiple advanced segments at once – side by side! This means that you can set up your own “custom dimension” using advanced segments. There is a drawback though – Google Analytics only allows you to look at up to four advanced segments at once. I know, it’s a bummer.
Variations on Metrics – Calculated Metrics
A metric like “visits”, is simply a count that applies to a particular set of data. However, some metrics are more complicated than simple counts. Some metrics available in Google Analytics are calculated in order to show relationships between different metrics.
Average time on site, exit rate, conversion rate, bounce rate – all of these are examples of calculated metrics. Average time on site shows the relationship between the total amount of time spent on site and the total number of visits.
Sometimes calculated metrics go both ways
Although most attributes in Google Analytics are treated exclusively as either a dimension or a metric, some attributes may be metrics in some contexts, and dimensions in others. In every example I can think of, these are all calculated metrics (if you can think of a counter-example, go ahead and prove me wrong!)
Pageviews per Visit, Visits per Visitor and Average time on Site can all be metrics (for dimensions such as source, geography, medium and device). However, you can also bucket visits, visitors and other metrics based upon the value of a different metric, as in the following chart which shows a volume of visits based upon the bucket of elapsed days since previous visit.