PowerMetrics are a powerful tool to slice-and-dice your data. Modelled data sources, the foundation on which PowerMetrics are built, allow us to interpret information in numerous ways, controlling the shape, format and granularity of your data.
This article gives a practical example on how adding an additional column to a modelled data source can help you segment your data by ranges/groups.
When I want to group numeric data into ranges, I create a column in my modelled data source to use as a segment in my PowerMetric. In this example, I have online chat durations that I want to divide into one of two categories: “within chat duration limit” or “over chat duration limit”.
To do this, I need to model my data source so that it includes a segment with these categories. My data source has a column containing the chat duration in seconds.
To get the segmentation I want in my PowerMetric, I add a column to my data source model with the following formula:
For each chat in the data, this formula checks the chat duration and if it is in range, returns the value “In Duration Limit“, otherwise it returns the value “Over Duration Limit“.
Now I can build my PowerMetric and segment my data using this column.
This method can be used with other types of data:
- age groupings for demographic data
- numeric ranges, such as revenue categories