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Exploring the SAP Customer Data Platform's AI Workbench
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Applying the AI Workbench Predictive Models
Providing Customer Data for the AI Workbench
Identifying the Minimum Data Requirements and Distribution Criteria for the AI Workbench
14 min
Provisioning Customer Data Set for AI Workbench
9 min
Speed Running the Ingestion
10 min
Quiz
Applying the AI Workbench Predictive Models
Creating a Customer Churn Indicator
33 min
Creating a Customer Lifetime Value Indicator
34 min
Quiz
Visualizing Predictive Insights
Visualizing Predictive Insights
17 min
Quiz
Providing Customer Data for the AI Workbench
Identifying the Minimum Data Requirements and Distribution Criteria for the AI Workbench
14 min
Provisioning Customer Data Set for AI Workbench
9 min
Speed Running the Ingestion
10 min
Quiz
Applying the AI Workbench Predictive Models
Creating a Customer Churn Indicator
33 min
Creating a Customer Lifetime Value Indicator
34 min
Quiz
Visualizing Predictive Insights
Visualizing Predictive Insights
17 min
Quiz
Knowledge quiz
It's time to put what you've learned to the test, get 3 right to pass this unit.
1.
A business wants to predict customer churn based on inactivity within a specific timeframe. Using the provided example from the learning material, how would you modify the churn condition template to define churn as no orders placed in the last 120 days?
Choose the correct answer.
count(Activities.Orders.OrderId, in (120 day)) = 0
sum(Activities.Orders.OrderId, inLast (120 day)) = 0
count(Activities.Orders.OrderId, inLast (120 day)) = 0
count(Activities.Orders.OrderId, in (120 day)) > 0
sum(Activities.Orders.OrderId, in (120 day)) = 0
2.
How are the High, Medium, and Low settings configured for customer value distributions resulting from a CLV Model run?
Choose the correct answer.
This is done automatically, and these distributions cannot be adjusted
This is done based on the Segments the customers are part of
This is done based on the Processing Purposes the customers are part of
This is done by adjusting the high and low percentile settings before running the model
This is done by adjusting the high and low fixed threshold settings before running the model
3.
A business wants to predict customer value based on high activity within a specific timeframe. Using the provided example from the learning material, how would you modify the CLV Formula template to define the total value of all order amounts placed in the last 120 days?
Choose the correct answer.
count(Activities.Orders.Amount, inLast (90 day)) = 0
sum(Activities.Orders.Amount, inLast ((120 day))
sum(Activities.Orders.Amount, inLast (120 day)) > 0
sum(Activities.Orders.Amount, inLast (120 day)) = 0
count(Activities.Orders.Amount, inLast (120 day))
4.
What is the difference between the Observation Period and the Prediction Period?
Choose the correct answer.
The Observation Period is the future window; the Prediction Period is historical data.
The Observation Period is historical data; the Prediction Period is the future window for predictions.
They represent the same time frame but are used differently.
The Observation Period defines the criteria for churn, while the Prediction Period defines the timeframe for evaluating customer behavior.
The Observation Period is when the model predicts churn, while the Prediction Period is used for analyzing historical data.