Subject & Topic Overview

Within the Carbon Arc Builder, Insights are organized using a taxonomy of Subjects and Topics to make it easier for users to navigate and filter through a large volume of metrics.

• Subjects represent high-level groupings of data, such as Card Transactions, Point of Sale (POS), or Advertising.

• Topics provide a more detailed breakdown within each subject, classifying specific attributes of the dataset, like geographic coverage, panel filters, or custom data slices — for example, “By Demographic” views that analyze data by demographic cohorts, or Constant Shopper panels that focus on repeat purchase behaviors.

This approach is meant to help you quickly locate the data most relevant to your business questions while maintaining clarity across complex datasets about what is fundamentally being returned.

For example, the Subject > Topic level classifications in some of our Credit Card datasets are structured to give users a clear, consistent view of the data.

A Subject like Credit Card Spend organizes all relevant metrics tied to card-based transactions. Within this subject, Topics then break down the data into more focused perspectives, such as:

• By Income Cohort: analyzing spending by income cohort features
• Constant Shopper: tracking behavior of consistent shoppers over time
• By Payment Type: distinguishing debit vs. credit payment types and more

This layered classification is meant to make it easier for your to explore, filter, and extract insights without losing track of the broader data context, while still supporting granular questions.