More than ever, marketers need to determine content marketing ROI.
Google Analytics (GA) is an ideal place to start. Setting up GA to track goals is an important first step to measuring content marketing effectiveness. By defining and tracking conversions on your blog, you’ll gain powerful insights into how your content is driving visitors to take actions that matter to your business.
In my previous post on this topic, we went through how to set up conversion goals in GA. This ensures that you’re recording clean data.
If you’ve done that and are ready to gain deeper insights, then look no further. In this post, we’ll go through a few examples of reporting and analysis that will help you to act on the conversion goals you’ve set in your GA instance. (If you’d like to dig even deeper into this topic and see live examples of everything in this post, check out our recent webinar.)
Quick Overview of Google Analytics Reporting Categories
If you’re not the primary user of GA, it’s important to understand the basic ways in which GA views and reports on data. While there are many ways to look at data, GA reports on four major buckets:
- Audience: This is the ‘who’ of GA, covering all the information about people who visit your hub, from geographic locations, demographic categories, and even what devices they’re using.
- Acquisition: Here, we learn how people got to your site via different channels, social networks, and referral sources.
- Behavior: This category covers everything visitors do when they get to your site; this includes pages visited, what types of content they viewed, time on site, paths taken, and much more.
- Conversions: This is where all the goal conversion data in GA lives. Much of the information that we’ll be looking at today comes from this area, where we’ve set up custom goals.
With that covered, let’s dig into the actual data to discover some insights that will help inform and shape your content marketing strategy.
Google Analytics provides lots of data that can be segmented and viewed in a nearly infinite number of ways. If you’re already using a content marketing platform or marketing automation software platform, you may occasionally feel analysis paralysis. Because you have so much data at your disposal, it’s critical that your analytics are actionable.
So what exactly does that mean?
Valuable analytics means that you can easily understand your data, articulate it to others, and take action.
This is the core of what we’re looking at today. Everything in this article is designed to help you understand your audience better, and use that data to inform your strategy and spend.
If you’re just recording the goals that are being completed on your hub, you’re gaining valuable insight into whether things are working. But it doesn’t give you much that you can alter or test to improve these metrics. This is why GA allows you to overlay goal completions on top of the Audience, Acquisition, and Behavior views. Seeing goals completed isolated into these views allows you to look at your audience through a very specific lens and determine: What it is about your traffic that converts into goals?
For each of the first three major GA buckets above, there are some key metrics that you should be viewing your goals against, and we’ll dig into a few of these specifically later. Depending on your business model there may be others, but the below will start you off with a good core group to keep as your reference points when you audit your content performance:
To show the value of GA goal comparisons, we’re going to dig into one example. Here, you’ll see how you can parse through audience conversion data to gain better insights on your customers.
Viewing Location Conversion Data in GA
Looking at the Audience traffic by location as an example (Audience > Geo > Location) the data table can be amended to show how a goal performed against it. This is the critical component that allows us to not only see how visitors got to the site, but also how each location performed against a goal independently.
On the far right of your default table, you’ll see an option to change the conversion. For this example, we’ll use the Purchase Completed goal that comes from the dummy data account from Google. As you’ll see, the overall conversion rate is 2.75% across all countries:
However, this view also shows the conversion rate across all countries, which means we can look at if a country performs better or worse than the average. In our Google Store example, we can see that when arranged by visits, the top 10 countries are as follows:
However, if we look at the conversion rates of these top 10 countries, we see a very disparate group of data. The United States converted at 7%, far higher than the average, while the #2 country actually didn’t convert at all, despite having nearly 8.5% of the total traffic volume. The story becomes even more interesting when we see that Canada, with just 2.64% of the traffic converted more than 50 times better than most of the other countries above it.
This is a perfect example of how seeing the traffic with a conversion in mind can completely alter how you perceive its importance in your strategy. Viewing data in this way can be a challenge, however, which is why GA has some powerful data visualization options just above the conversions table:
Each one of these table helps to visualize the data in a different way, and can be a valuable way to view large sets of data to see trends.
The simplest example of this visualization is the standard bar chart. When selecting this view, we can see goals completed by location in a more visual way:
The only caveat to this data view is that it only shows total completions and not the rate. This means that data can often be skewed by the volume of traffic to show false reports. If a location gets a lot more traffic than the others, then a lower conversion rate may not be as clear because even if that location had a lower conversion rate it would still have a lot more overall conversions. The comparison chart is a great way to make sure we don’t get lost with this bias.
Keeping the above example, if we display the conversion rate in the comparison chart format, we see the data sets visualized compared the site average and suddenly our clear winners appear by how much better they perform than the others:
One thing to bear in mind about comparison charts is the data skewing that can occur from large winners. Since, in this example, the United States converted at a 7% rate, then naturally it is going to be the most significant bar in this chart. Because it’s so much stronger, however, it can also hide insights that might lie deeper. One method to dig past this is to remove the obvious winner to remove its data skewing properties. Using the Advanced filter above the table, we can exclude certain data sets:
When we remove the United States, we can see how well Canada and the United Kingdom perform. This is because the overall conversion average has massively dropped to only 0.23% when we removed the United States. Of course, Canada isn’t as strong a performer as the United States, overall, but if we had not removed the outlier, we may have neglected to see how much more impactful it is compared to all the other countries on the list. In the first example, it only looked marginally better.
From a strategic point of view, this may be something that could be amplified even further with more regional targeting or changes in messaging, but it’s always a good practice to dig just a little deeper to see if there are hidden gems:
Sorting Table by Conversion Rate
While it’s great to visualize data in various ways, sometimes a simple solution is also a powerful one. Google Analytics is a giant pivot table, so there are times when it’s just easier to sort the table, and we can do exactly that with goal completions as well:
Just be sure to look at the visit volume when doing this because as we see above, Nicaragua was a powerful performer, but with a total visit volume of just 16 it’s hard to take as a true result. However, it’s a simple way to look at data that can give quick feedback rather than sifting through bar charts.
Different Data Sets
Although we looked at just the location data, this same visualization method works for all the other pieces of data in the table at the beginning of this article. By looking at all the key data sets in GA, you’ll be able to look at who, where, and what behavior drives the most conversions through your hub.
Looking at data through this lens allows you to think about only the variables that resulted in conversions and can allow you to target with confidence.
Although we can view each bucket in GA with goal conversions, sometimes it can be a little too granular and hard to sift through. One good tip is to create a custom segment that will allow you to look at any data in GA filtered down to only the audience that completed a goal. When looking at the volume of traffic, pages visited, channels used, this allows for a more pure view that takes out traffic that doesn’t complete a goal. Creating a segment is easy too.
At any data page in GA, you’ll see an option at the top that shows “All Users,” and also the option to create a new segment:
Typically, when creating a custom segment, marketers will segment their audience by traditional metrics such as demographic, geographic, or technological, but it also allows for more custom ones, and that’s what we’ll use.
When we create a new segment, we’re going to go to the Conditions section, and the filter we’ll choose is the goal you have set up in GA. It will ask for a number and we’re going to choose greater than zero so that it will only show sessions where a goal was completed. While this is not the complete picture, it’s a valuable way to see only the purest of goal completion traffic. The result is a view that will only show the data for people who completed goals, and can give you a powerful view into the traffic of most value to you.
Google Analytics is a powerful tool, and custom goals is one of the most powerful methods of recording data that really matters to your business. However, the data it provides is only the surface. There are a variety of ways to dig into the data of goal completions that will allow you to see how and what drives conversions most for your content.
By looking at the data in a deeper and more comparative way, it can give you actionable insights and ways to shape your strategy to drive even more conversions by driving even more of the right type of traffic. For a more detailed walkthrough, I recommend you check out our webinar to see it in action.
Liam Moroney is NewsCred’s Demand Generation Manager.
Originally published on Jan 6, 2017 11:00 AM, updated Sep 14, 2017