AI Associate AI Capabilities in CRM — Timed 20 Questions

Question 1

A sales rep wants to use Einstein Activity Capture to automatically log emails and meetings. Which prerequisite must be met?

Accepted Answer

Users must grant access to their email and calendar via OAuth. Einstein Activity Capture requires users to explicitly grant access to their email and calendar via OAuth (Option D). This OAuth-based authentication allows Salesforce to securely sync emails and meetings from the user's email provider (e.g., Gmail, Outlook) into Salesforce records. Without this explicit consent, the feature cannot access or log the user's activity data.

Answer

Chatter must be disabled for the organization

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Sales Cloud Einstein licenses for all users

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The feature is automatically enabled once email integration is configured

Question 2

A company uses Einstein Lead Scoring and finds that leads with high scores are not converting. What should the admin do to improve prediction accuracy?

Accepted Answer

Retrain the model with more recent conversion data. Option B is correct because retraining the model with more recent conversion data allows the Einstein Lead Scoring model to adapt to changing patterns in lead behavior and conversion criteria. When high-scoring leads fail to convert, it indicates that the historical data used to train the model no longer reflects current conversion dynamics, so refreshing the training dataset improves prediction accuracy by aligning the model with recent outcomes.

Answer

Increase the scoring model's maximum score

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Disable field-level security for scoring fields

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Lower the lead conversion threshold

Question 3

An admin notices that Einstein Opportunity Scoring is not generating scores for new opportunities created in the past week. Which troubleshooting step should the admin take first?

Accepted Answer

Check that there are at least 50 won and 50 lost opportunities with populated fields. Option C is correct because Einstein Opportunity Scoring requires a minimum of 50 won and 50 lost opportunities with populated fields to generate scores. Without this historical data, the model cannot learn patterns to score new opportunities. The admin should first verify this prerequisite before considering other steps.

Answer

Retrain the Opportunity Scoring model

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Verify that users have the 'View Einstein Scores' permission

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Wait 48 hours for the model to update

Question 4

A company wants to use Einstein Bots to handle common customer service inquiries. Which feature should be enabled to allow the bot to escalate to a live agent when it cannot resolve the issue?

Accepted Answer

Omni-Channel Flow. Option D is correct because Omni-Channel Flow routes work to agents. Option A is wrong because Einstein Case Classification categorizes cases, not escalates. Option B is wrong because Einstein Article Recommendations suggests knowledge articles. Option C is wrong because Einstein Reply Recommendations suggests responses, not escalation.

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Einstein Case Classification

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Einstein Reply Recommendations

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Einstein Article Recommendations

Question 5

Which TWO actions can be performed using Einstein Activity Capture?

Accepted Answer

Automatically log emails from Outlook or Gmail. Einstein Activity Capture is designed to automatically log user activities such as emails and meetings from connected email and calendar systems (Outlook, Gmail, Exchange) into Salesforce records. Option A is correct because the feature captures emails sent or received from these providers and logs them as EmailMessage records against the relevant contacts, leads, and opportunities without manual user intervention.

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Update opportunity amounts based on email content

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Create tasks from email attachments

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Generate leads from email signatures

Question 6

Which THREE factors influence the prediction accuracy of Einstein Lead Scoring?

Accepted Answer

Historical conversion data of leads. Option C is correct because Einstein Lead Scoring relies on historical conversion data to identify patterns that distinguish leads likely to convert. By analyzing past leads that converted, the model learns which attributes and behaviors correlate with successful outcomes, directly influencing prediction accuracy.

Answer

Custom formula fields on the lead object

Answer

Number of times a lead is viewed by sales reps

Question 7

An admin reviews the Einstein service configuration JSON. Based on the exhibit, which statement is true?

Accepted Answer

Opportunities will not have Einstein scores. Option B is correct because the JSON exhibit shows that the Einstein Opportunity Scoring feature is disabled (the 'status' field is set to 'Disabled'), meaning opportunities will not have Einstein scores. This is determined by the configuration flag that controls whether Einstein scoring is active for opportunities in the org.

Answer

Lead scoring is disabled for the org

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The lead scoring model retrains daily

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The admin has not configured any scoring fields for leads

Question 8

A mid-size company uses Sales Cloud with Einstein Lead Scoring and Einstein Activity Capture. The sales team reports that lead scores are not updating for leads that have been engaged via email and calendar events over the past two weeks. The admin checks the Einstein Lead Scoring model and finds that the model status is 'Active' and was retrained last month. The admin also verifies that Einstein Activity Capture is enabled and syncing data correctly. However, the lead scores remain unchanged. Upon further investigation, the admin discovers that the leads were created before the Einstein Lead Scoring model was activated, and the model's training data includes only leads created after activation. The company has over 10,000 leads, but only 200 were created after activation. Historical conversion data for leads created before activation is not being used. What should the admin do to ensure lead scores reflect recent engagement?

Accepted Answer

Retrain the Einstein Lead Scoring model using all historical lead data, including pre-activation leads. Option D is correct because retraining the model with all historical lead data (including pre-activation leads) will include conversion patterns from a larger dataset, improving accuracy and enabling scores for older leads. Option A is wrong because field mapping alone does not cause scoring to update. Option B is wrong because Einstein Activity Capture is already syncing; the issue is with the model. Option C is wrong because the scoring fields are separate from activity tracking.

Answer

Map the email and event fields to the lead object so that the model can use them

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Add the Activity Count field to the scoring fields list in the model configuration

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Re-enable Einstein Activity Capture to resync all historical emails and events

Question 9

A sales manager wants to automatically prioritize leads based on their likelihood to convert. Which Einstein feature should be used?

Accepted Answer

Einstein Lead Scoring. Einstein Lead Scoring is the correct feature because it uses predictive models to automatically rank leads based on their likelihood to convert, enabling the sales manager to prioritize follow-up efforts. It analyzes historical lead data and engagement patterns to assign a score, directly addressing the requirement for automated prioritization without manual rules.

Answer

Einstein Prediction Builder

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Einstein Relationship Health

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Einstein Activity Capture

Question 10

A company uses Salesforce and wants to provide automated chat responses for common customer inquiries. Which Einstein feature should be configured?

Accepted Answer

Einstein Bots. Einstein Bots is the correct feature because it enables automated chat responses for common customer inquiries using natural language processing (NLP) and predefined dialog flows. It integrates directly with Salesforce Chat to handle routine questions without human intervention, reducing response times and agent workload.

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Einstein Sentiment

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Einstein Case Routing

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Einstein Recommender

Question 11

A Salesforce admin notices that Einstein Account Scoring is not generating scores for all accounts. Some accounts have no score even though they meet the data requirements. What is the most likely cause?

Accepted Answer

The org has fewer than 100 account records. Einstein Account Scoring requires a minimum of 100 account records to generate meaningful scores. If the org has fewer than 100 accounts, the model cannot establish a baseline for scoring, resulting in no scores for any account. This is a hard threshold enforced by the Einstein AI engine, not a configurable setting.

Answer

Einstein features are not enabled in the org

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Users do not have the 'View Scores' permission

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The accounts lack custom fields for scoring

Question 12

A service manager wants to automatically categorize incoming support cases based on the customer's description. Which Einstein feature should be used?

Accepted Answer

Einstein Case Classification. Einstein Case Classification uses machine learning to automatically categorize incoming support cases based on the customer's description, assigning them to predefined case fields (e.g., type, priority, product). This directly matches the requirement to automatically categorize cases from text, making it the correct choice.

Answer

Einstein Reply Recommendations

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Einstein Bots

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Einstein Article Recommendations

Question 13

A company wants to use Einstein to predict which customers are likely to churn in the next 30 days. Which type of prediction should be created in Einstein Prediction Builder?

Accepted Answer

Binary classification. Einstein Prediction Builder is designed for binary outcomes, such as whether a customer will churn (yes/no) within a specified time frame. A binary classification model predicts one of two possible labels, making it the correct choice for this churn prediction use case.

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Numeric prediction

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Multi-class classification

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Regression

Question 14

A Salesforce admin has enabled Einstein Opportunity Scoring but notices that some opportunities are not being scored. The admin checks the data and finds that the opportunities have all required fields. What could be another reason for missing scores?

Accepted Answer

The org has fewer than 100 opportunities with activities. Einstein Opportunity Scoring requires a minimum of 100 opportunities with activities (e.g., emails, events, tasks) in the last 90 days to generate scores. Even if all required fields are present, the model needs sufficient historical data to calculate a predictive score. Option C correctly identifies this data volume threshold as the likely cause.

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Opportunity team members have not been assigned

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The org is on a Professional Edition

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The opportunities are missing custom fields

Question 15

A company wants to use AI to automatically recommend the best next action for service agents during a live chat with a customer. Which Einstein feature should be enabled?

Accepted Answer

Einstein Next Best Action. Option D, Einstein Next Best Action, is correct because it is specifically designed to recommend the optimal next step for service agents during live interactions. It uses AI to analyze the customer context, conversation history, and business rules to surface the most relevant action, such as offering a discount or escalating the case, directly within the agent's console.

Answer

Einstein Article Recommendations

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Einstein Bots

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Einstein Reply Recommendations

Question 16

An admin is setting up Einstein Bot for a customer service chat. The bot needs to collect the customer's account number before transferring to a human agent. What should the admin configure?

Accepted Answer

Create a Dialog to ask for the account number. Option B is correct because a Dialog is the component that handles a conversation flow, including collecting information. Option A is incorrect because a Variable stores data but does not collect it. Option C is incorrect because a Rule determines logic, not collection. Option D is incorrect because a Set Value action sets a variable, but the overall collection happens within a Dialog.

Answer

Add a Variable with the account number field

Answer

Define a Rule to validate the account number

Answer

Use a Set Value action to assign the account number

Question 17

A company uses Einstein Prediction Builder to predict whether a lead will convert. The model's confidence score is low, and the admin wants to improve accuracy. What is the most effective action?

Accepted Answer

Increase the amount of historical data for training. Option B is correct because increasing the amount of high-quality historical data provides more examples for the model to learn from, improving accuracy. Option A is incorrect because more features can improve accuracy but only if they are relevant; just adding any field may cause noise. Option C is incorrect because Einstein models train automatically on your data, and you cannot directly increase training frequency. Option D is incorrect because training multiple models is not supported and doesn't improve the single model.

Answer

Create multiple prediction models and average their scores

Answer

Add more custom fields as predictor fields

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Increase the frequency of model retraining

Question 18

Which TWO features are part of Einstein AI capabilities in Salesforce Sales Cloud?

Accepted Answer

Einstein Opportunity Scoring. Einstein Opportunity Scoring is a core Einstein AI capability in Sales Cloud that uses predictive models to analyze historical data and assign a score to each opportunity, indicating its likelihood to close. This helps sales reps prioritize their efforts on deals most likely to convert, directly leveraging AI to enhance sales productivity.

Answer

Einstein Case Classification

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Einstein Bots

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Einstein Article Recommendations

Question 19

Which THREE are requirements for enabling Einstein features in a Salesforce org?

Accepted Answer

An eligible Salesforce edition. Einstein features require an eligible Salesforce edition (e.g., Enterprise, Performance, or Unlimited) because the underlying AI infrastructure, including predictive models and data processing pipelines, is only available in these higher-tier editions. Without the correct edition, the necessary licenses and platform capabilities for Einstein are not provisioned.

Answer

Custom objects must be created

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Activation of Einstein API in Setup

Question 20

Which TWO are best practices when implementing Einstein Recommendation Builder?

Accepted Answer

Use a dataset that reflects recent customer interactions. Option A is correct because Einstein Recommendation Builder relies on recent customer interaction data to generate accurate and relevant product or content recommendations. Using stale or outdated data can lead to irrelevant suggestions, as the model learns from historical patterns that may no longer reflect current customer preferences or behaviors.

Answer

Disable negative feedback to simplify the model

Answer

Include all available data, even if it is old or unrelated

Answer

Use a single dataset that contains the entire history of the org