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It's important to note that you may sometimes be limited by dimension and metric combination limits. These limitations are defined by the API of the data provider and are most often beyond NinjaCat's control.

Datasource vs. Aggregate

Dimensions

Dimensions are required for most data widgets  - they're how we're segmenting the data. In many of the data widgets, you can add one or more dimensions to provide granular detail on things such as, for example,  Campaign Performance by Date, Demographic, or Channel.

Simple Dimensions (Data Source-Specific)

Simple dimensions can be defined as those available in a widget that contains just 1 data source (or multiple instances of the same data source). 

Aggregate Dimensions

Aggregate Dimensions are dimensions that are common across all the data sources being used in a widget. The dimension you're looking for may not be available in the Aggregate list. If this happens you will need to use Custom Dimensions. We explore these in the next section. There are many fewer aggregate dimensions than simple ones, but using custom dimensions gives you massive flexibility when adding dimensions to your data widgets.  

Custom Dimensions

Custom Dimensions allow you to build a dimension - for example if one data source calls its dimension landing page title, and the other data source calls the same dimension landing page name, you can use the custom dimension builder to instruct NinjaCat to view these as the same Dimension, which you can then custom name.

Edit the Dimension Entry Settings

1. Click on the "pencil" icon next to the desired dimension to open its Dimension Settings fly-over

2. Edit the fields below to gain the desired result

• Custom Display Name - Enter your desired name for the dimension to override the default dimension name
• Find and Replace - identify and replace text in the dimension results to create custom labels for dimension results
  • Click on "Add Replacement"
  • Type the desired dimension result text that you want to be replaced into the "Find" field
  • Type the text that you want to show up in the "Find" field text's place in the "Replace" field
  • Repeat these steps for multiple Find/Replace tasks
  • Use the "Match Case" check box to require case sensitivity
  • Use the Regex box to use text manipulation via regular expressions
  • Click "OK" when complete

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The dimension find and replace feature can be used to combine multiple dimension results into one to group different data segments together for your data display needs.

Metrics

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At least 1 Metric is required for all data widgets  - it's the measurement of performance or value. In many of the data widgets, you can add one or more metrics to provide greater detail on overall performance, such as displaying Impressions alongside Clicks, Cost, and CPC.

Simple Metrics (Data Source-Specific)

Simple metrics can be defined as those available in a widget that is specific to one of the data sources being used. If we were to use  Facebook and Google Ads in our widget, Clicks for example is available across both - if we select the simple metric of Clicks from under the Facebook Header in the widget inspector, we're only going to see clicks from Facebook. Likewise, if we only want to see clicks from Google Ads, but not Facebook, we'd select clicks from under the Google Ads header in the widget inspector. Using simple metrics allows great control over which data we present from each data source.  

Aggregate Metrics

Aggregate Metrics are metrics that are common across all the data sources being used in a widget. If a metric, such as Clicks is available from all data sources you're using you'll find it as a simple metric, but also an aggregate one. Aggregate metrics combine the metric values from ALL of the data sources you're using - so if we used Aggregate Clicks when a widget included both Facebook and Google Ads, our clicks value would be a combined total from both of those data sources.  

Custom Metrics

Custom Metrics allows you to combine metrics from individual data sources to build very specific calculations. - for example, if you're measuring clicks from one data source, but cost from another, the aggregate CPC metric won't give you what you want. Creating metrics in the custom metric editor allows you to specify exactly the calculation you want to use. Using an example of a widget containing Facebook and a Custom Data Source such as a Google Sheet, for example, we might want CPC to reflect Cost from the Google Sheet divided by Clicks from Facebook displayed as a currency. Using the aggregate CPC metric wouldn't be able to give us such a specific result, as it would provide us with Cost from Facebook AND the Google Sheet added together and divided by the total clicks from Facebook and the Google Sheet.