Option A applies the least computationally intensive feature appropriate to each requirement. Days Since Last Login is fundamentally a row-level derived value based on an existing login-date attribute, so a Data 360 data-stream formula can derive a supplemental field without requiring an analytical aggregation pipeline. Salesforce supports formula fields derived from other fields, functions, and operators during data-stream processing.

Loyalty Tier based on lifetime spend , however, requires aggregation across potentially many transaction records for each customer. A batch calculated insight is designed for that type of multi-record calculation. Because the email is monthly, a daily batch calculation is adequate; there is no business need to pay the higher processing cost associated with streaming computation.

Streaming calculated insights consume Data 360 Streaming Pipeline Flex Credits based on processed records. Batch calculated insights are billed under Data 360 Prep according to underlying records processed. Therefore, unnecessary streaming should be avoided when sub-second freshness isn't required.

A formula-field caveat is that Salesforce recalculates a data-stream formula when the corresponding record is refreshed or changed, so implementation scheduling must ensure the value is sufficiently current for the monthly send.

The master bank keys A.

Study Guide Reference: Data Modeling, Identity Resolution and Segmentation → Data 360 Calculations → Formula Fields, Calculated Insights, and Credit Optimization.

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