Northern Trail Outfitters has the following customer data to ingest into Data Cloud and use for segmentation. 1. Propensity to purchase 2. Has active…

When ingesting data into Data Cloud, selecting the most specific and appropriate data type is crucial for data quality, validation, and usability.

1. Propensity to purchase: This represents a likelihood or score, which is best modeled using the Percent data type. This type correctly formats the value as a percentage for analysis and segmentation.

2. Has active membership: This is a binary condition (yes/no, true/false), for which the Boolean data type is the standard and most efficient choice.

3. Work email address: Data Cloud provides a specific Email data type that includes inherent validation to ensure the data conforms to a standard email format.

1. Salesforce Help Documentation - Data Types in Data Cloud: This official document lists and describes the available data types for mapping data in Data Cloud.

Percent: "A number that is stored as a decimal and shown as a percentage in the UI." This is the most appropriate type for a propensity score.

Boolean: "A true or false value." This directly corresponds to the "Has active membership" field.

Email: "An email address. The maximum length is 255 characters." This is the specific

validated type for an email address.

The document implicitly shows why other options like Text

Number

or URL are less appropriate for these specific data points. For instance

using the 'Email' type over 'Text' adds a layer of format validation.