Metrics are essentially numbers from your data that are used in dashboards or within reports. Commonly used metrics are the total revenue, the number of unique visitors or buyers in a given period, the conversion rate (the number of buyers per visitor), RPV (revenue per visitor), etc. A metric can either be calculated as an aggregate of one event type or as a formula including more event types.
Watch this short introductory video about this feature:
There are three ways how you can create a new metric:
- Go to
Data & Assets>
+ Create new
Once saved you can then use it in a dashboard or a report.
- In the dashboard edit view when adding a metric, you can click "create new" and specify your metric.
- Directly in a report. This metric doesn't have to be saved for use outside of the report unless you click "save" as shown in the screenshot below.
We will now explain every part of the metric editor as numbered in the screenshot below.
A simple metric is only based on a single event type, whereas a formula allows you to calculate a number using multiple simple metrics together. You can change a mathematical operator by clicking on it. This will also allow you to put the two metrics around it into brackets. You can also add a simple number as indicated in the screenshot below.
This drop-down menu allows you to select the output format of your metric. The following options are available:
Returns a date based on the timestamp of the selected event. For example, if you select
Similar as above, but this returns a specific part of the date. For example, "Year" will return the actual year when the event was tracked, "Month" will return a number between 1-12, "Day of year" can be 1-365, "weekday" returns 1-7, etc.
Similar as above but in this case, you will get a number depicting how long ago the event happened. You can select a format from seconds to years.
This drop-down menu allows you to select how the data from the selected attribute will be processed. You can find the definition of each operator in the Aggregates and running aggregates article.
If you're working with event attributes, you can refine your metrics by other attributes of the same event. For example, one of the screenshots above calculates the total revenue as
sum > purchase > total_price. We can refine this further by adding another condition:
where total_price > less than 1000. This will exclude every event
purchase where the attribute
total_price was greater than 999 and will not include it in the final metric number. Bear in mind that you can only refine the metric by attributes of the same event, in this case
Read more about using filters in the Filtering data article.
Customer filters don't filter the event directly, but rather filter the customers to be considered in your output.
Read more about using filters in Exponea as well as the difference between customer and event filters in the Filtering data article.
This toggle switch appears when you're working with an event attribute.
Processes all events that match the condition
Processes the first occurrence of an event per customer within specified constraints, such as a date filter.
Processes the last occurrence of an event per customer within specified constraints, such as a date filter.
To count the unique buyers, set
count > event > purchaseand set the toggle to
First. This looks at all purchases but counts only the first event for every customer, which means you will get the number of unique buyers. You can also use
Lastin the same way.
You can also filter by a specific time range. Read more about how date filters work in the Filtering data article.
Click preview to see the output of your current setup.
By clicking on the button, you will see information about who created and edited the metric and when. You can also add a description of the metric. If you check the "Show in view mode" button, your description will be displayed when someone views the metric in Data & Assets. This might be useful if you want to add any explanations for other users.
Click on the three dots if you want to save as copy, add to dashboard, clone to another project or delete the metric.
- When counting unique customers that fulfill some criteria (e.g. buyers, etc.) use
count eventand select the first occurrence instead of using
count customerand then specifying the customer filter. This may give you different results as explained here.
- When creating a metric, don’t specify the date filter unless necessary. Date filter can always be specified later in a report or a dashboard, and you can easily forget that you set a date filter within the metric too, resulting in unexpected outputs.
How many people visited our web page in the last 30 days?
What is our conversion rate in the last 30 days?
What is our bounce rate today?
Read our block about Email marketing analytics about metrics, KPIs, and reports for more information on Bounce rates
Updated about a year ago