Air360 has already a lot of charts to display your data with various visualizations.
However, there are times when you probably want to create a bespoke chart & visualization. In this case, the Data Explorer is what you need: you can chart almost any data from Air360 and add it to your dashboard.
After clicking on "Add a new chart" in your dashboard, choose "Data Explorer".
You will be taken to a configuration view as shown below, that will ask you to select what you want to measure and how to display it. After practicing a few setups, this will become very easy in time.
The name you want this to appear on your dashboard for this chart.
This is what you want your chart to reflect. Can be a conversion rate, number of sessions, number of users, etc.
To put it simply, dimensions allow you to split your data based on any criteria. For example, you might want your sales split by Country, or your sessions split by websites your visitors came from, etc. That's dimensions.
Filters allow you to exclude some part of the data in what you measure. For example, you might want to measure your conversions only for users who came from Facebook.com and who are in the United States as show below.
The filters can be grouped and use simple logic with OR / AND operators. In the example above, we set the logic to AND, which means it will display data when BOTH filters conditions are met. If we change this to OR, it means that we we will measure when AT LEAST one of the condition is met.
It means that if all these users below will be counted in:
- User comes from United States and from google.com
- User comes from Italy and from facebook.com
If you want all dimensions EXCEPT one (or a few ones), it's also very easy to do that. For example let's say we want to see the new users coming to our websites but who didn't come as direct trafic. We could do something like below.
Basically, we created a filter that says we want to measure new users, split by which URL they came from, EXCEPT the ones who came directly to our website (not via an another website).
Filters are not here to only hide/show specific dimension, you can actually use it directly for when you want a given metric. For instance, let's say you want to see the average session duration of your users using Chrome.
Now click on "Preview". BOOM.
Want to compare it to all browsers, EXCEPT Chrome?
This is how this data to be displayed, you can have it in a pie chart, line chart, or even raw data as a table.
In our previous example where we measured the Average session duration, we might just want to have a total count on the total period used in the dashboard, for this, we can use the Total count which gives a display like this.
This is useful when you don't care about daily data and just want an average on the whole period in your dashboard.
If you prefer to have raw data, you can also choose "Table" which will give you something like below with data covering your dashboard date range (it may be many lines of data in some cases).
Chart scale (when applicable)
Two options are possible here:
Absolute scale will chart your data with a Y-axis that starts from 0 and goes up to the maximum value of your data.
Smart scale will chart your data with a Y-axis that starts from the lowest value value of your data and goes up to the maximum value of your data.
If you are more interested about variations, then Smart scale is usually a better choice.
Do you want your data to be grouped by hour, day, week, weekday, hour of the day? or month? This feature enable you to split your data however you want.
Smart time grouping option will make your chart automatically choose the best time group depending on your dashboard date range.
For instance, if your dashboard spans on 12 months, time group will be automatically set on monthly. However, if you modify your dashboard start date and end date span on a whole month, data will be grouped by day. This allows your chart to show the most relevant time grouping based on your dashboard start & end date.
Exclude unassigned values
When you check this, all dimension values will never be shown in your chart.
A classic example is when working with UTM codes, you might be interested to know how many sales were generated by UTM codes. Here again, the Data Explorer lets you do that super easily.
Which might give you something like what's below. As you can see. We can see that 94% of our sales didn't come from visitor who came from a link with a utm_source code set.
While this gives us the big picture, we want to have ONLY users who had the UTM code utm_source set. All we have to do is check "Exclude unassigned values" and here we go. As you can see, the "Not assigned" disappeared and we can now have a better idea of how our different utm_source compete among each other in terms of delivering sales.