QUESTION: 100 Exam Topic: Implement AI predictions in Customer Insights

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You are responsible for creating segments for your company’s marketing team using Microsoft Dynamics 365 Customer Insights.

Your Chief Marketing Officer (CMO) wants to run a re-engagement campaign for customers that have a high probability of no longer purchasing your organization’s products in the next three months.

The CMO asks you to use Dynamics 365 Customer Insights to generate a segment of customers that would meet this requirement.

Solution:
1. Generate a Transactional churn prediction for the next three months.
2. On the results page, review the model results to identify the characteristics of the highest “Likelihood to churn” group.
3. Create a segment from the results page using the ChurnScore field and a Greater than operator for the lower bounds value of the group you identified.

Does this meet the goal?

Answer(s): A

Explanation:

Transactional churn prediction helps predict if a customer will no longer purchase your products or services in a given time window.

You must have business knowledge to understand what churn means for your business. We support time-based churn definitions, meaning a customer is considered to have churned after a period of no purchases.

Note

In the output entity for this model, ChurnScore shows the predicted probability of churn and IsChurn is a binary label based on ChurnScore with 0.5 threshold.

Reference:

https://learn.microsoft.com/en-us/dynamics365/customer-insights/predict-transactional-churn

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QUESTION: 101 Exam Topic: Implement AI predictions in Customer Insights

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You are responsible for creating segments for your company’s marketing team using Microsoft Dynamics 365 Customer Insights.

Your Chief Marketing Officer (CMO) wants to run a re-engagement campaign for customers that have a high probability of no longer purchasing your organization’s products in the next three months.

The CMO asks you to use Dynamics 365 Customer Insights to generate a segment of customers that would meet this requirement.

Solution:
1. Generate a Customer Lifetime Value model for the next three months.
2. On the results page, review the model results to identify the characteristics of the lowest “Value of customers by percentile” group.
3. Create a segment using the CLVScore field and a Lesser than operator for the upper bounds value of the group you identified.

Does this meet the goal?

Answer(s): B

Explanation:

Instead: Solution:
1. Generate a Transactional churn prediction for the next three months.
2. On the results page, review the model results to identify the characteristics of the highest “Likelihood to churn” group.
3. Create a segment from the results page using the ChurnScore field and a Greater than operator for the lower bounds value of the group you identified.

Predict customer lifetime value (CLV)
Predict potential value (revenue) that individual active customers will bring in to your business through a defined future time period. This prediction helps you:

Identify high-value customers and process this insight.
Create strategical customer segments based on their potential value to run personalized campaigns with targeted sales, marketing, and support efforts.
Guide product development by focusing on features that increase customer value.
Optimize sales or marketing strategy and allocate budget more accurately for customer outreach.
Recognize and reward high-value customers through loyalty or rewards programs.

Note: Transactional churn prediction helps predict if a customer will no longer purchase your products or services in a given time window.

You must have business knowledge to understand what churn means for your business. We support time-based churn definitions, meaning a customer is considered to have churned after a period of no purchases.

Note 2:

In the output entity for this model, ChurnScore shows the predicted probability of churn and IsChurn is a binary label based on ChurnScore with 0.5 threshold.

Reference:

https://learn.microsoft.com/en-us/dynamics365/customer-insights/predict-transactional-churn
https://learn.microsoft.com/en-us/dynamics365/customer-insights/predict-customer-lifetime-value

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QUESTION: 102 Exam Topic: Implement AI predictions in Customer Insights

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You are responsible for creating segments for your company’s marketing team using Microsoft Dynamics 365 Customer Insights.

Your Chief Marketing Officer (CMO) wants to run a re-engagement campaign for customers that have a high probability of no longer purchasing your organization’s products in the next three months.

The CMO asks you to use Dynamics 365 Customer Insights to generate a segment of customers that would meet this requirement.

Solution:
-Generate an activity-based segment suggestion using frequency and recency dimensions.
-On the Suggestions page, create a segment on the High Frequency - Low Recency tile.

Does this meet the goal?

Answer(s): B

Explanation:

Reference:

https://learn.microsoft.com/en-us/dynamics365/customer-insights/predict-transactional-churn

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QUESTION: 56 Exam Topic: Create customer profiles by unifying data questions

Your organization’s IT team created the customer profile records by unifying the Account, Contact, and Web Account tables. After unification was completed, the team noticed that three relationships were created automatically:

1. CustomerToContact
2. CustomerToAccount
3. CustomerToWebAccount

You need to advise the team about how they can configure and update these three relationships.

What should you recommend?

Relationships created via the unification process can be edited by those with contributor-level access.
You can edit each of the three relationships by clicking into the Relationship tab and selecting Edit.
You cannot edit any of the three relationships, as they are non-editable system relationships.
Relationships created via the unification process can only be edited by those with administrator-level access.

Answer(s): C

Reference:

https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/relationships

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QUESTION: 100 Exam Topic: Implement AI predictions in Customer Insights

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QUESTION: 101 Exam Topic: Implement AI predictions in Customer Insights

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QUESTION: 102 Exam Topic: Implement AI predictions in Customer Insights

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QUESTION: 56 Exam Topic: Create customer profiles by unifying data questions

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