Accounts: Accounts are a Correlated Labs data type that encapsulates a centralized view of a customer organization. Accounts can either be directly associated with a metric (for example, total revenue) or indirectly associated with a metric (for example, a user from an account logged in). When you query a metric, we smartly group all the users associated with an account and display a holistic account level view of that metric. Accounts are a superset of Salesforce Accounts. If we find a matched Salesforce Account, we include those fields and dimensions as part of the Account itself. If we don’t, we are still able to pull a view of the Account from other sources, such as data warehouses.

Metrics: Metrics are numeric values that change over time. Metrics can be plotted in investigations and used as conditions in Segments. When used in Segments, counts will be totaled over the selected window of time. Numerics will be a single value that is the last known value for the selected window of time.

Dimensions: Values that describe the metric. Dimensions can be used to breakdown metrics into different groups in investigations, and can be used as filters in Segments. Dimensions can only be filtered by is and is not - they do not support comparison operators (e.g. greater than, less than).

Users: Users are single persons who are associated with a metric. For example, logins are tagged with users so that you know which user logged in. Users are typically identified by one or more dimensions. This is usually email, although in certain cases this could also be a user id or user name. You can choose how you want to identify your users to map to your business. Users are linked to Contacts and Leads in Salesforce via an arbitrary dimension, which is by default, email. Users are a superset of Contacts and Leads - all Contacts and Leads are matched to Users whenever possible, but not all Users are Contacts or Leads.