Explanation:
To classify documents in SharePoint Online using Customer.csv, you need to create a trainable classifier. A trainable classifier is best suited for identifying patterns in unstructured data (e.g., customer names in documents). A sensitive info type is more suitable for structured data (e.g., credit card numbers, SSNs). An adaptive scope is used to apply policies dynamically based on attributes, not for classifying content.
Since Customer.csv contains a list of names, the best element to use is a keyword dictionary. A keyword dictionary allows you to upload a list of predefined terms (such as customer names) to classify documents based on their presence. Regular expressions are used for pattern-based detection (e.g., credit card numbers, serial numbers), which is not needed here. Functions are used for predefined sensitive data detection (e.g., checksum validation for credit card numbers), which does not apply in this case.