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Question 50 - Professional Machine Learning Engineer discussion

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You are designing an ML recommendation model for shoppers on your company's ecommerce website. You will use Recommendations Al to build, test, and deploy your system. How should you develop recommendations that increase revenue while following best practices?

A.
Use the 'Other Products You May Like' recommendation type to increase the click-through rate
Answers
A.
Use the 'Other Products You May Like' recommendation type to increase the click-through rate
B.
Use the 'Frequently Bought Together' recommendation type to increase the shopping cart size for each order.
Answers
B.
Use the 'Frequently Bought Together' recommendation type to increase the shopping cart size for each order.
C.
Import your user events and then your product catalog to make sure you have the highest quality event stream
Answers
C.
Import your user events and then your product catalog to make sure you have the highest quality event stream
D.
Because it will take time to collect and record product data, use placeholder values for the product catalog to test the viability of the model.
Answers
D.
Because it will take time to collect and record product data, use placeholder values for the product catalog to test the viability of the model.
Suggested answer: B

Explanation:

Recommendations AI is a service that allows users to build, test, and deploy personalized product recommendations for their ecommerce websites. It uses Google's deep learning models to learn from user behavior and product data, and generate high-quality recommendations that can increase revenue, click-through rate, and customer satisfaction. One of the best practices for using Recommendations AI is to choose the right recommendation type for the business objective. The ''Frequently Bought Together'' recommendation type shows products that are often purchased together with the current product, and encourages users to add more items to their shopping cart. This can increase the average order value and the revenue for each transaction. The other options are not as effective or feasible for this objective. The ''Other Products You May Like'' recommendation type shows products that are similar to the current product, and may increase the click-through rate, but not necessarily the shopping cart size. Importing the user events and then the product catalog is not a recommended order, as it may cause data inconsistency and missing recommendations. The product catalog should be imported first, and then the user events. Using placeholder values for the product catalog is not a viable option, as it will not produce meaningful recommendations or reflect the real performance of the model.Reference:

Recommendations AI documentation

Choosing a recommendation type

Importing data to Recommendations AI

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asked 18/09/2024
Alexis Chacon
31 questions
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