A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase in sales of recommended items to existing customers immediately after deploying a new solution version, but these sales decrease a short time after deployment. Only historical data from before the marketing campaign is available for training. How should a data scientist adjust the solution?
A) Use the event tracker in Amazon Personalize to include real-time user interactions.
B) Add user metadata and use the HRNN-Metadata recipe in Amazon Personalize.
C) Implement a new solution using the built-in factorization machines (FM) algorithm in Amazon SageMaker.
D) Add event type and event value fields to the interactions dataset in Amazon Personalize.

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The Answer of A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase in sales of recommended items to existing customers immediately after deploying a new solution version, but these sales decrease a short time after deployment. Only historical data from before the marketing campaign is available for training. How should a data scientist adjust the solution?
A) Use the event tracker in Amazon Personalize to include real-time user interactions.
B) Add user metadata and use the HRNN-Metadata recipe in Amazon Personalize.
C) Implement a new solution using the built-in factorization machines (FM) algorithm in Amazon SageMaker.
D) Add event type and event value fields to the interactions dataset in Amazon Personalize.

A Retail Company Is Using Amazon Personalize to Provide Personalized