The client wants to be able to recommend high-profit-margin products on low-profit-margin product pages. Which method should be used to pass profit margin product data to Adobe Target Recommendations?

Question

Options

• AData Source
• BURL parameter
• CFeeds Entity
• DProduct Metadata

• A
  3% (1)
• B
  13% (5)
• C
  77% (30)
• D
  8% (3)

Explanation

Feeds Entity is the correct method because Adobe Target Recommendations uses Entity Feeds (CSV, Google Product Feed, or Analytics Classification) to bulk-upload product metadata - including profit margin - that can then drive recommendation logic like "show high-margin products on low-margin pages." This is exactly the mechanism designed for passing structured product attribute data at scale into the Recommendations catalog.

Why the distractors are wrong:

• A. Data Source is not a native Adobe Target concept for this purpose; it's more associated with Adobe Analytics data ingestion pipelines, not Target Recommendations product attributes.
• B. URL parameter can pass entity.* attributes for a single viewed product on a page, but it only captures data for products a user actually visits - you cannot use it to pre-load an entire catalog of profit margin data for cross-referencing.
• D. Product Metadata sounds plausible but is not a specific Adobe Target Recommendations ingestion method; product attributes are metadata, but the mechanism to deliver them in bulk is the Entity Feed.

Memory tip: Think of "Feeds" as the bulk upload path - when you need to get product attributes (like profit margin) into Target before a user ever visits those pages, you feed them in via an Entity Feed CSV or product catalog feed.

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