A. Scores leads based on customer data B. Creates personalized SMS campaigns C. Automatically interacts with prospects
Answer: A Explanation: AI assists in lead qualification primarily by scoring leads based on customerdata. This process, known as lead scoring, uses machine learning algorithms to evaluateleads against a set of predefined criteria that reflect potential interest and sales readiness.The scores assigned help sales teams prioritize their efforts toward leads most likely toconvert, thus improving efficiency and success rates in sales activities. Salesforce AIenhances this process through features like Einstein Lead Scoring, which automaticallycalculates scores based on both historical conversion data and behavioral data fromprospects. For further insights, Salesforce provides detailed documentation on lead scoringwith AI at Salesforce Einstein Lead Scoring.
Question # 12
Which best describes the difference between predictive AI and generative Al?
A. Predictive AT uses machine learning to classify or predict outputs from its input datawhereas generative Al does not use machine learning to generate its output. B. Predictive Al uses machine learning to classify or predict outputs from its input datawhereas generative Al uses machine learning to generate new and original output for 4given input C. Predictive Al and generative Al have the same capabilities but differ in the type of inputthey receive; predictive AT receives raw data whereas generative AT receives naturallanguage.
Answer: B Explanation: Predictive AI and generative AI represent two different applications ofmachine learning technologies. Predictive AI focuses on making predictions based onhistorical data. It analyzes past data to forecast future outcomes, such as customer churnor sales trends. On the other hand, generative AI is designed to generate new and originaloutputs based on the learned data patterns. This includes tasks like creating new images,text, or music that resemble the training data but do not duplicate it. Both types of AI usemachine learning, but their objectives and outputs are distinct. For detailed differences andapplications in a Salesforce context, Salesforce's guide on AI technologies is a helpfulresource, accessible at Salesforce AI Technologies.
Question # 13
Which action introduces bias in the training data used for AI algorithms?
A. Using a large dataset that is computationally expensive B. Using a dataset that represents diverse perspectives and populations C. Using a dataset that underrepresents perspectives and populations
Answer: C Explanation: Introducing bias in training data for AI algorithms occurs when the datasetused underrepresents certain perspectives and populations. This type of bias can skew AIpredictions, making the system less fair and accurate. For example, if a datasetpredominantly contains information from one demographic group, the AI's performancemay not generalize well to other groups, leading to biased or unfair outcomes. Salesforcediscusses the impact of biased training data and ways to mitigate this in their AI ethicsguidelines, which can be explored further in the Salesforce AI documentation onResponsible Creation of AI.
Question # 14
What is the significance of explainability of trusted AI systems?
A. Increases the complexity of AI models B. Enhances the security and accuracy of AI models C. Describes how Al models make decisions
Answer: C Explanation: The significance of the explainability of trusted AI systems is that it describeshow AI models make decisions. Explainability is crucial for building trust and accountabilityin AI systems, ensuring that users and stakeholders understand the decision-makingprocesses and outcomes generated by AI. This is particularly important in scenarios whereAI decisions impact personal or financial status, such as in credit scoring or healthcarediagnostics. Salesforce emphasizes the importance of explainable AI through its ethical AIpractices, aiming to make AI systems more transparent and understandable. More detailsabout Salesforce’s approach to ethical and explainable AI can be found in Salesforce AI ethics resources at Salesforce AI Ethics.
Question # 15
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records. Which type of records negatively impact data quality?
A. Structured B. Complete C. Duplicate
Answer: C Explanation: Duplicate records negatively impact data quality by creating inconsistenciesand confusion in database management, leading to potential errors in customerrelationship management (CRM) systems like Salesforce. Duplicates can skew analyticsresults, lead to inefficiencies in customer service, and result in redundant marketing efforts.Salesforce offers various tools to identify and merge duplicate records, thereby maintaininghigh data integrity. More about managing duplicate records in Salesforce and ensuring dataquality can be found in Salesforce’s documentation on duplicate management atSalesforce Duplicate Management.
Question # 16
Cloud Kicks' latest email campaign is struggling to attract new customers. How can AI increase the company's customer email engagement?
A. Create personalized emails B. Resend emails to inactive recipients C. Remove invalid email addresses
Answer: A Explanation: AI can significantly increase customer email engagement by creatingpersonalized emails. Salesforce Einstein AI enhances email marketing campaigns byanalyzing customer data and past interactions to tailor the content, timing, andrecommendations within emails. This personalization leads to higher engagement rates asemails resonate more closely with individual preferences and behaviors. SalesforceMarketing Cloud provides tools to leverage AI for crafting personalized email campaigns,ensuring that emails are relevant and appealing to recipients. For more insights into how AIcan be used to enhance email marketing, see the Salesforce Marketing Cloud page atSalesforce Marketing Cloud Email Studio.
Question # 17
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use. Which data quality component Is the BA verifying by checking for null values?
A. Duplication B. Usage C. Completeness
Answer: CExplanation: By checking for null values, a business analyst (BA) is verifying the data quality component of completeness. Completeness refers to the absence of missing valuesor gaps in the data, which is essential for the accuracy and reliability of reports andanalytics used in AI models. Null values can indicate incomplete data, which may adverselyaffect the performance of AI applications by leading to incorrect predictions or insights.Salesforce emphasizes the importance of data completeness for effective data analysisand provides tools for data quality assessment and improvement. Details on handling datacompleteness in Salesforce can be explored at Salesforce Help Data Management.
Question # 18
Cloud Kicks plans to use automated chat as its primary support channel. Which Einstein feature should they use?
A. Discovery B. Bots C. Next Best Action
Answer: B Explanation: For Cloud Kicks, using automated chat as the primary support channel, therecommended Einstein feature is Bots. Einstein Bots are designed to automate customerinteractions on common issues through chat and messaging platforms. They can handleroutine requests, provide quick answers to frequently asked questions, and escalate morecomplex issues to human agents. Using Einstein Bots helps improve customer serviceefficiency and speed, leading to enhanced customer satisfaction. To learn more aboutsetting up and optimizing Einstein Bots for a business, you can visit the Salesforcedocumentation on Einstein Bots at Salesforce Einstein Bots.
Question # 19
Which type of AI can enhance customer service agents' email responses by analyzing the written content of previous emails?
A. Natural language processing B. Machine learning C. Deep learning
Answer: A Explanation: Natural language processing (NLP) is the type of AI that can enhancecustomer service agents' email responses by analyzing the written content of previousemails. NLP technologies interpret and generate human language, allowing AI systems tounderstand, respond to, and even anticipate customer needs based on email interactions.This capability helps in crafting more relevant, accurate, and personalized email responses,improving customer service quality. Salesforce utilizes NLP in its Einstein AI platform toaugment various customer service functions. More about Salesforce Einstein’s NLPcapabilities can be found on the Salesforce Einstein page at Salesforce Einstein NLP.
Question # 20
A sales manager is looking to enhance the quality of lead data in their CRM system. Which process will most likely help the team accomplish this goal?
A. Redesign the lead conversion process, B. Review and update missing lead information. C. Prioritize active leads quarterly.
Answer: B Explanation: To enhance the quality of lead data in their CRM system, the most effectiveprocess is to review and update missing lead information. This process involves identifyingincomplete records and filling in missing details, which can significantly improve theaccuracy and usefulness of lead data. Accurate and complete lead information is crucial foreffective lead scoring, prioritization, and follow-up, enhancing overall sales performance.Salesforce CRM offers data quality tools and features that assist in regularly reviewing andmaintaining the accuracy of lead data. Information on managing lead data quality inSalesforce can be found at Salesforce Lead Management.