Dimensions, Metrics and Data Sources
In the previous article in this series you got an overview of the report structure in Clarisights. This article takes you through the building blocks of reporting in Clarisights; i.e: dimensions, metrics and data sources.
In clarisights all the data you can use to create your reports and analyse information is in the form of dimensions and metrics.
Dimensions
Dimensions and dimension values are qualitative in nature. If you consider a Facebook Ad Campaign, the Campaign name, ID, Campaign Type, Start Date, etc are different dimensions representing the attributes of that Campaign. You can use dimensions to categorize, group, and breakdown to granular details in your data.
On Clarisights, dimensions are timeless attributes. For example if the name of a Facebook Ad Campaign is changed, it changes on Clarisights as well for the entire duration that the Campaign has data for.
There are broadly two kinds of dimensions in Clarisights - System & Custom Dimensions
System dimensions are those which come into Clarisights as part of the original dataset that was imported. For example, Campaign Type is a system dimension name from Google Ads that represents the type of campaign (Search, Display, UAC, etc)
Clarisights has many system dimensions imported from the various ad channels that are integrated and they can be used in various places like reports and custom dimensions.
Custom dimensions are created by users on top of the data that comes in from an external source. Editors or Admins can create custom dimensions that allow users to group data in their own ways that all other users can include in their reports. For example, “Marketing Channel” is a business classification that may not exist as part of the datasets from Ad channels like Facebook, Google Ads, etc. but on Clarisights you can create a custom dimension called Marketing Channel to group together data from various sources in a classification specific to your organization.
Metrics
Metrics and metric values are quantitative in nature, that you can measure. Metrics in Clarisights are always attributed to dates. For example Spend, Clicks, CTR are metrics. They are bound to change over time and you can track these changes in Clarisights. This means all metric data in Clarisights is time-series in nature.
There are broadly two kinds of metrics in Clarisights- System & Custom Metrics.
System metrics come into Clarisights as part of the dataset that’s imported into the platform. And are always prefixed with an abbreviation of the data source they come from. For example, FB: Spend is a system metric that measures spend reported by Facebook coming into Clarisights via the Facebook Ads API.
Custom metrics are created by users on top of the data that comes in from an external source. Editors or Admins can create custom metrics that allow users to combine datapoints from different sources in one single column.
Users can also do calculations using different system or custom metrics. For example when you need a metric for measuring Cost per Click across all performance marketing data, admins can create that using custom metrics.
Data Sources
All the system dimensions and metrics come from various data sources that Clarisights can connect to. Whether you are using existing reports or creating new ones from scratch you will come across data sources also known as report segments when they're used to create reports
Broadly there are two types of report segments
Native Segment: These are unfiltered and contain all the information that are present in the data source. Examples include Facebook Ads, Google Ads, etc
Custom Segments: These are groups of multiple native segments and typically filtered for a subset of the information coming from those sources. They are curated by Admins for your workspace
If your organization has curated report segments we recommend using them in Clarisights. You can also contact admins in your organization to create report segments for frequently used data sources and filter combinations. This article covers more details on report segments and how to create them.
For advanced use cases and to explore unfiltered data from the different data sources, use native segments in your reports. You can find in this collection of articles, the various integrations, and all the dimensions and metrics that are being imported into Clarisights.
In the next article we explore using dimensions and metrics in widgets in Clarisights to enable reporting and exploration in existing reports.
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