What are Marketing Cloud Personalization's machine learning powered algorithms called?

In Marketing Cloud Personalization, the machine learning-powered algorithms are configured and managed through a framework called "Einstein Recipes." A recipe is a combination of ingredients (the algorithms), inclusions, exclusions, and boosters that determines the logic for personalized recommendations. The "Einstein" branding is used across Salesforce products to denote features powered by artificial intelligence and machine learning, and "Recipes" is the specific term used in this context.

A. Data Science Workbench: This is a specific tool for data scientists to build and deploy custom models, not the name for the standard algorithms.

B. Machine Learning Tools: This is a generic, descriptive phrase, not the official product name for the algorithms within Marketing Cloud Personalization.

C. Einstein Decisions: This term is associated with AI-powered path optimization features within Journey Builder, not the recommendation algorithms in Personalization.

1. Salesforce Help. (2024). Einstein Recipes and Templates. Marketing Cloud Personalization. Retrieved from https://help.salesforce.com/s/articleView?id=sf.mcperseinsteinrecipesandtemplates.htm&type=5. The first sentence states, "Einstein Recipes are algorithms you configure to control which recommendations a user sees."

2. Salesforce Help. (2024). Einstein Personalization Recipes. Marketing Cloud Personalization. Retrieved from https://help.salesforce.com/s/articleView?id=sf.mcperspersonalizationrecipes.htm&type=5. This page provides a high-level overview, consistently using the term "Einstein Recipes" to describe the recommendation logic.