Quick Answer
The answer is predictive scoring. This is the correct feature because Dynamics 365 Customer Insights applies machine learning models to historical customer data and engagement patterns, generating a numerical score that predicts the likelihood of a specific outcome—such as responding to a new product campaign. For the MB-910 exam, this concept tests your understanding of how Customer Insights uses AI to drive data-driven marketing decisions, often appearing in scenario-based questions where you must distinguish predictive scoring from other features like segments or measures. A common trap is confusing predictive scoring with simple segmentation; remember that scoring predicts future behavior, while segments group existing data. To lock it in, think of the mnemonic “Score for the Future”—predictive scoring always forecasts a probability, not just describes what already happened.
This MB-910 practice question tests your understanding of describe dynamics 365 customer insights. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to use Customer Insights to identify customers who are likely to respond to a new product campaign. Which feature should they use?
Enrichment
Why wrong: Enrichment adds external data but does not predict.
Predictive scoring
Predictive scoring uses AI to predict customer behavior such as likelihood to respond.
Measures
Why wrong: Measures track KPIs but do not predict.
Segmentation
Why wrong: Segmentation groups customers but does not predict response.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Predictive scoring
Predictive scoring in Dynamics 365 Customer Insights uses machine learning models to analyze historical customer data and engagement patterns, assigning a score that predicts the likelihood of a specific outcome—such as responding to a new product campaign. This directly matches the company's goal of identifying high-propensity customers for targeted outreach.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Enrichment
Why it's wrong here
Enrichment adds external data but does not predict.
Predictive scoring
Why this is correct
Predictive scoring uses AI to predict customer behavior such as likelihood to respond.
Related concept
Read the scenario before looking for a memorised answer.
Measures
Why it's wrong here
Measures track KPIs but do not predict.
Segmentation
Why it's wrong here
Segmentation groups customers but does not predict response.
Common exam traps
The trap here is that candidates confuse Segmentation (a static grouping tool) with Predictive scoring (a dynamic machine learning output), because both can be used to target customers, but only Predictive scoring answers the 'likely to respond' question using probability modeling.
Detailed technical explanation
Predictive scoring in Customer Insights leverages built-in machine learning models (e.g., binary classification) trained on your tenant's data, including attributes like past purchases, click-through rates, and churn history. The model outputs a probability score between 0 and 1, which can be used in real-time segmentation or triggered journeys in Dynamics 365 Marketing. A subtle behavior: the model automatically retrains on a schedule (e.g., weekly) to adapt to changing customer patterns, but you must have sufficient historical data (at least 500 records per outcome) for reliable results.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Describe Dynamics 365 Customer Insights — This question tests Describe Dynamics 365 Customer Insights — Read the scenario before looking for a memorised answer..
The correct answer is: Predictive scoring — Predictive scoring in Dynamics 365 Customer Insights uses machine learning models to analyze historical customer data and engagement patterns, assigning a score that predicts the likelihood of a specific outcome—such as responding to a new product campaign. This directly matches the company's goal of identifying high-propensity customers for targeted outreach.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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