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          Billing Considerations for Identity Resolution

          Billing Considerations for Identity Resolution

          Use of identity resolution impacts the consumption of credits used for billing in these usage types.

          Note
          Note Customers whose Data 360 orgs operate under a Customer Data Platform license should refer to Customer Data Platform Billable Usage Calculations instead of this article.
          Tip
          Tip

          This feature has access to Digital Wallet, a free account management tool that offers near real-time consumption data for enabled products across your active contracts. Access Digital Wallet and start tracking your org's usage. To learn more, see About Digital Wallet.

          Usage Types Consumed by Identity Resolution

          Digital Wallet Card Usage Type Usage Type Description Notes
          Data Services Batch Profile Unification

          Usage is calculated based on the number of source profiles processed by an identity resolution ruleset. After the first time a ruleset runs, only new or modified source profiles are counted. A source profile is an individual and their related records, such as contact points and party identifiers, which are included in the identity ruleset.

          For example, modified means deleted profiles, or profiles marked as suppressed via Consent API preferences.

          In certain circumstances, identity resolution is triggered to fully reprocess a ruleset. These actions can trigger a full run of a ruleset.

          • Changing a ruleset's match rules.
          • Changing a ruleset's reconciliation rules.
          • Mapping a new data lake object (DLO) to a data model object (DMO) that's used in a ruleset.
          • Mapping a new field to a DMO that's used used in a ruleset. This includes mapping ssot_IsAnonymous__c to a DMO.
          Data Services Data Queries

          Usage is calculated based on the number of records processed.

          The count of records processed depends on the structure of a query as well as other related factors such as the total number of records in the objects being queried.

          Data queries are used to create the processing history table.
          Data Services Sub-second Real-Time Events & API

          Usage is calculated based on the sum of the number of profile events, engagement events, API calls, and data actions processed in the sub-second real-time layer and real-time ingestion API, including web and mobile SDKs traffic. Profile events, engagement events, API calls, and data actions are processed in the real-time layer if they are associated with a real-time data graph.

          For example, if 3 profile events, 10 engagement events, 20 API calls, and 5 data actions are processed during a particular billing period, the total processed is 38.

          This category applies only to real-time identity resolution.
          Data Storage Storage Beyond Allocation Usage is calculated based on the amount of storage used above the amount allocated. Identity resolution stores the output of ruleset runs in Data 360 data model objects.
          Note
          Note If your Data 360 home org has an active Data 360 Profiles or Data 360 Enterprise Profiles license, some credit consumption for this feature is supplanted by Data 360 Profile billing methods and limits. See Data 360 Profiles License Billing and Limits for more details.

          Customers whose Data 360 orgs operate under a Customer Data Platform license should

          For more information on how Data 360 usage is billed, refer to your contract or contact your account executive.

          Reduce Identity Resolution Costs

          You can lower credit consumption rates for identity resolution in several ways

          • Implement stricter data governance policies in source systems to improve the quality of data.
          • Use data transforms to pre-process profile data, such as by filtering out records with email addresses that occur more than 1000 times or standin phone numbers such as 888-111-1111.
          • Disable Run jobs automatically before you make multiple changes that each trigger a full refresh, such as adding new data sources, updating your data model, match rules, or reconciliation rules. Resume automatic ruleset runs after your changes are complete.
          • Test new rulesets first in a sandbox org with a small set of representative data. If you don’t have a sandbox but have multiple data spaces, consider testing in a data space with a small amount of data.
          • Maintain just one active ruleset per primary data model object per data space. Create additional rulesets only when you want to test a new configuration against your existing ruleset.
           
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