Which two statements are correct about the data characteristic requirements for configuring the CLV ML model?
You are a Customer Data Platform Specialist. Your company’s information technology team wants to use the out-of-the-box customer lifetime value (CLV) machine learning (ML) capabilities that come with audience insights, but the team has some concerns about the suitability of their data. You need to confirm if their research about data requirements is correct.
Which two statements are correct about the data characteristic requirements for configuring the CLV ML model? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
A . There should be at least two to three transactions per customer ID. preferably across multiple dates.
B . There should be at least 100.000 unique customers to perform the CLV model.
C . There should be preferably two to three years of transactional data to predict CLV for one year.
D . The CLV model will not run if there is any missing data in the fields.
Answer: AC
Explanation:
Reference: https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/predict-customer-lifetime-value
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