Metric Annotation via Custom Analytics

Clarisights offers two flavors of data import via custom analytics: standard and metric annotation. To understand the difference, you first need to know what an object is.

What is an object

In Clarisights, all metrics are stored against entities called objects. Each item at a given level is one object. For example, each distinct campaign in Facebook is an object at campaign level, and each distinct ad group in Google Ads is an object at ad group level.

When you look at data for a group of objects (for example, a custom dimension "Country" defined at campaign level), you are looking at the aggregate data of all the objects (in this case, campaigns) that have been tagged with each Country.

Standard Custom Analytics Data Import

In the standard flavor of custom analytics, each row in the CSV file needs to specify which specific object the metrics in that row need to be attributed to. For instance, you might have rows that each have a campaign name, in which case the metrics in each row will be attributed to those individual campaigns. This means that each row of data can be attributed only to one object.

A standard custom analytics file could look like this:

Each row uniquely identifies an object (by name and ID), and the revenue in that row is attributed to that object.

Metric Annotation Custom Analytics Data Import

Sometimes you want the metrics in one row of a custom analytics file to be attributed to several objects at once, not just one. For instance, you might import CPI values for an affiliate by city and date, and want all campaigns in each city of that affiliate to get the same CPI value, without listing every campaign in your file. The file might look like this:

And the primary affiliate data, to which the CPI values need to be joined, might look like this:

Metric annotation solves this. Instead of attributing metrics to a single object, it attributes the same metric to every object that satisfies the same condition.

In the affiliate example above, after importing the CPI data via custom analytics, all campaigns that have been grouped under City Berlin will have the metric value Affiliate CPI as €20 on 1st Jan. Similarly, all campaigns that fall under City London will have the metric value Affiliate CPI as €30 on 2nd Jan.

After the custom analytics data is imported, the primary affiliate data looks like the image below. You can define a weighted_sum of the Affiliate CPI and Affiliate Installs metrics and calculate your actual costs.

When to use metric annotation

Use metric annotation for metrics that don't need to be aggregated on their own and are only used to compute another metric. Examples are the Affiliate CPI metric above, or a standard CVR that you multiply with Clicks to calculate Conversions.

Metrics imported this way are treated as summable metrics across all the objects they are imported into (see Summable and Nonsummable Metrics). In the example above, the aggregate value of Affiliate CPI on Clarisights would be €628.

So Affiliate CPI isn't useful on its own. Its main use is in a weighted_sum function with Affiliate Installs to calculate Cost, which aggregates correctly because it is a summable metric.