Google Analytics has a lot of metrics and dimensions tracked right out of the box. However, it is still a blunt tool. In order to sharpen Google Analytics, you will need to add custom data. This will help you match your tracking capabilities to the unique needs of your particular website (or the needs of your clients’ websites).
Google’s Digital Marketing Evangelist, Avinash Kaushik, might have put it best when he said, “All data in aggregate is ‘crap.’ Segment absolutely everything.” And in order to segment as much as possible, you need to use custom data. There is an unlimited amount of custom data you could create, in theory, but in this post, we’re going to be talking about the two most common custom data types you should be leveraging in Google Analytics: goals and events.
The custom data type that just about every Google Analytics user will add first is goals. In Google Analytics, goals are actions that users complete on a website and are then collected as conversion metrics.
Goals are built into a lot of different reports, so you can see how different dimensions affect goal completions and goal rates. You can see how different sources and campaigns affect goals, or you can see how different landing pages affect goals. Goals also have their own report in the Conversions reports. You can even compare different attribution models. Lastly, goals can be shared with Google Ads, so you can use one source to track both Google Ads and Google Analytics activity.
There are two limitations to goals to keep in mind. First, you can only create 20 goals for a view, ever. You can have goals in different views for a single property, but the data cannot be combined in the default Google Analytics. You would need to pull the goal conversions into a third-party tool like Looker, Power BI, or Data Studio to see them all together.
The second limitation is that you cannot delete goals. You can rename a goal, and change the rules, but it will still maintain the historical data from its earlier iterations. This can be a problem if you change a goal but try to compare historical trends for that goal. It is a very bad idea to change a goal that has been collecting data.
Goals should be named in a consistent manner and with the assumption that they will be used in a third-party system. It is a good idea to identify where the goal came from when it is pulled into a third-party tool. That being said, you can pull additional metrics such as region, device type, or other custom dimensions, in order to help segment goals.
Assigning a value to goals is extremely useful when trying to determine your return on ad spend, and also when trying to see how different pages and paths are affecting your overall revenue. For example, if you have a lead submission goal, you should be able to pull a report from your customer database to determine the customer lifetime value (CLV) for customers that came from website lead submissions. Then get the rate of how many lead submissions you receive a year and divide by how many become customers to get your conversion rate. Then take your CLV and multiply by conversion rate to get the average value of your lead submission goal.
Ideally, the value is set in Google Tag Manager, so you can dynamically change it if your CLV or conversion rate changes over time.
Last, it is good practice to categorize macro and micro conversions. Macro conversions are activities that are directly tied to the success of an organization. Lead submissions, e-commerce transactions, and account creations could all be possible macro conversions.
The other key activities on the site that should be tracked are micro conversions. These could include newsletter sign-ups, whitepaper downloads, and job application submissions. They are activities that have some level of correlation with the macro conversions.
Macro and micro conversions generally work best when your macro conversions are 1-2 lagging metrics on your site (like first-time purchase) and the micro conversions are leading metrics that can help you improve your macro conversion rate. However, micro conversions may not always be something you can directly influence and therefore may not be the best metrics to measure the day-to-day success of your team.
Macro vs micro lines can become blurry, especially for non-profit organizations, so a well-planned strategy can help a lot in determining what should be considered a macro conversion.
The second-most common custom data type in GA is events. Before Google Tag Manager, events were difficult to set up and were not commonly used. In fact, Google Analytics comes with zero events out of the box.
Events are dimensions where you can assign three values to an activity on the site — an event category, action and label. Events are generally set up in Google Tag Manager and are designed to capture user activities that are not pageviews. This includes playing videos, clicking on interactive elements, and AJAX forms that don’t fire a new pageview.
Events have three attributes: category, action and label. These are normally used as a funnel which gets more specific as you go from category to label.
We recommend that categories and actions are mutually exclusive nominal data and the fewer categories you have the better. In our approach, labels do not need to be mutually exclusive, and they can stack infinitely. Labels should be used as a way to search for data, so it is good to have a system for labels. We often store dynamic information about an action in a label like Click Classes, Click ID, and Container ID, which can then help us segment data like if a user clicked the same link from different spots on the page, or how the change of the click text affected conversions over time.
In short, Google Analytics goals are used to track conversions on your website. If goals are set up correctly, they can help you make important business decisions, like the ones that affect your bottom line. Remember, though, that you can only create 20 goals per view, and once created you cannot delete a goal, and you should not change a goal after it starts collecting data. So be careful in setting up your goals and before you do so, make sure your high-level strategy is solidified.
Events in Google Analytics are used to track a wide variety of non-pageview events on your site. Events have three attributes — category, action and label — and these can be used to organize and segment your data on a more granular level.
We hope this post provided a good overview of the two most common custom data types in Google Analytics: goals and events. Once you have these mastered, you may find that you have more complex data that does not fit into goals or events. In that case, you will likely have to define your own custom metrics and dimensions in Google Analytics. More on that in a later post.