In the last section you read how to classify data in various custom groupings to create new dimensions that add more detail and normalize headers across datasets from different ad partners. If you imagine custom dimensions as groups of rows based on custom rules, when used in charts Clarisights aggregates metrics on those dimensions.

In a similar fashion, custom metrics are groups of column operations such as Column A + Column B. The default aggregation in Clarisights across rows is SUM.

Custom Metrics

A good way to approach custom metrics is with the question "what do we want to measure?"

Custom metrics just like dimensions are different for each organization. Broadly there are a few ways to classify custom metrics

  • Top Level Cross-Channel KPIs- these metrics are common across channels and are the base to build the main KPIs for the marketing team to track

    • Costs

    • Engagement (Impressions, Video Views, Clicks)

    • Conversions (Installs, SignUps, Acquisitions, Orders etc)

    • Revenue

    • Budgets

    • Targets

  • Channel Specific metrics- these are metrics that may not be relevant for all channels but are relevant for some.

    • Sales

    • Spots

    • Video Quartile 25%

Using a predictable naming convention to differentiate between Cross Channel and Channel Specific KPIs can keep the workspace from being cluttered and promote users to find their metrics more easily.

Use Cases

If you wanted to track the Cost per Activation across all your ad channels, you would use custom metrics to set it up.

  • Aggregate Cost: Advertising spends reported by platforms come in various forms. Facebook calls it Spend, Google ads calls it Cost, and Awin calls it Commission. If you were to use one metric to look at aggregate costs, you could create a custom metric (say Total Ad Spend) and define it as a sum of the different cost metrics.

  • Aggregate Activations: You may be tracking Web Purchases on Facebook as "Activations" and a different metric on Google Ads to track the conversions that count as "Activations" for your business. You can create a custom metric to sum these different metrics together.

  • Aggregate Cost per Activation: Using the ratio of both the metrics you just created above in a new custom metric will give you your final aggregate CPA metric. Going forward all you would need to do is update your Aggregate Cost and Activations custom metrics to include any new channels that you do integrate.

Using custom metrics you can create multiple other calculated custom metrics such as Cost per Conversion, Budget Pace, RoAS, Conversion - Target%, etc

For streamlined management of custom metrics here are some things you should consider

  • To not use conditional rules with dimensions in segment levels for cross channel conditional metrics. Just like it's not recommended to be using the segment level in cross-channel custom dimensions, similarly it is also not recommended to use such custom dimensions in Conditional Custom Metrics.

    This is because it forces the query to go on the lowest common level (segment in this case) where some data may not be available. Eg: Facebook doesn't report on web conversions broken down by Country (Breakdown). If your Country custom dimension makes use of the segment from Facebook - you would not be able to see conversions from Facebook when using this conditional custom metric.

  • Have a clean framework so that over time, teams can manage their own KPIs and the top KPIs are always up to date with latest changes. Here is a cheat sheet to setup your structure today!

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