Salesforce Salesforce Certifications SALESFORCE-AI-ASSOCIATE Questions & Answers

• Question 21:

  A service leader wants use AI to help customer resolve their issues quicker in a guided self-serve application.

  Which Einstein functionality provides the best solution?

  A. Case Classification

  B. Bots

  C. Recommendation

  Correct Answer: B

  "Bots provide the best solution for a service leader who wants to use AI to help customers resolve their issues quicker in a guided self-serve application. Bots are a feature that uses natural language processing (NLP) and natural language understanding (NLU) to create conversational interfaces that can interact with customers using text or voice. Bots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the customer's intent and context."

• Question 22:

  What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?

  A. Testing models with diverse datasets

  B. Striving for model explain ability

  C. Working with human rights experts

  Correct Answer: A

  "An example of Salesforce's Trusted AI Principle of Inclusivity in practice is testing models with diverse datasets. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing models with diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."

• Question 23:

  How does AI assist in lead qualification?

  A. Scores leads based on customer data

  B. Creates personalized SMS campaigns

  C. Automatically interacts with prospects

  Correct Answer: A

  AI assists in lead qualification primarily by scoring leads based on customer data. This process, known as lead scoring, uses machine learning algorithms to evaluate leads 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 to convert, thus improving efficiency and success rates in sales activities. Salesforce AI enhances this process through features like Einstein Lead Scoring, which automatically calculates scores based on both historical conversion data and behavioral data from prospects. For further insights, Salesforce provides detailed documentation on lead scoring with AI at Salesforce Einstein Lead Scoring.

• Question 24:

  An administrator at Cloud Kicks wants to ensure that a field is set up on the customer record so their preferred name can be captured.

  Which Salesforce field type should the administrator use to accomplish this?

  A. Multi-Select Picklist

  B. Text

  C. Rich Text Area

  Correct Answer: B

  "A text field type should be used to capture the customer's preferred name. A text field type allows the user to enter any combination of letters, numbers, or symbols. A text field type can be used to store names, addresses, phone numbers, or other personal information."

• Question 25:

  What is an example of ethical debt?

  A. Violating a data privacy law and falling to pay fines

  B. Launching an AI feature after discovering a harmful bias

  C. Delaying an AI product launch to retrain an AI data model

  Correct Answer: B

  "Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical debt is a term that describes the potential harm or risk caused by unethical or irresponsible decisions or actions related to AI systems. Ethical debt can accumulate over time and have negative consequences for users, customers, partners, or society. For example, launching an AI feature after discovering a harmful bias can create ethical debt by exposing users to unfair or inaccurate results that may affect their trust, satisfaction, or well-being."

• Question 26:

  Cloud kicks wants to develop a solution to predict customers' interest based on historical data. The company found that employee region uses a text field to capture the product category while employee from all other locations use a picklist.

  Which dimension of data quality is affected in this scenario?

  A. Accuracy

  B. Consistency

  C. Completeness

  Correct Answer: B

  "Consistency is the dimension of data quality that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Inconsistent data can cause confusion, errors, or duplication in data analysis and processing. For example, using different field types for the same attribute can affect the consistency of the data."

• Question 27:

  A marketing manager wants to use AI to better engage their customers.

  Which functionality provides the best solution?

  A. Journey Optimization

  B. Bring Your Own Model

  C. Einstein Engagement

  Correct Answer: C

  "Einstein Engagement provides the best solution for a marketing manager who wants to use AI to better engage their customers. Einstein Engagement is a feature that uses AI to optimize email marketing campaigns by providing insights and recommendations on the best time, frequency, content, and subject lines to send emails to each customer. Einstein Engagement can help increase customer engagement, retention, and loyalty by delivering personalized and relevant messages."

• Question 28:

  Cloud Kicks wants to evaluate the quality of its sales data.

  Which first step should they take for the data quality assessment?

  A. Plan and align territories,

  B. Run a new report or dashboard.

  C. Identify business objectives.

  Correct Answer: C

  The first step Cloud Kicks should take for data quality assessment is to identify business objectives. This is crucial because understanding how the company uses customer data to support its business objectives will guide the assessment process1. By identifying the business objectives, Cloud Kicks can determine what customer data is required to support those objectives and how that data is being used. This foundational step is essential before moving on to other aspects of data quality assessment, such as running reports or planning territories. It aligns the data quality initiatives with the company's goals and ensures that the assessment is focused on areas that will drive business value

• Question 29:

  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

  Correct Answer: A

  Natural language processing (NLP) is the type of AI that can enhance customer service agents' email responses by analyzing the written content of previous emails. NLP technologies interpret and generate human language, allowing AI systems to understand, 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 to augment various customer service functions. More about Salesforce Einstein's NLP capabilities can be found on the Salesforce Einstein page at Salesforce Einstein NLP.

• Question 30:

  What does the term "data completeness" refer to in the context of data quality?

  A. The degree to which all required data points are present in the dataset

  B. The process of aggregating multiple datasets from various databases

  C. The ability to access data from multiple sources in real time

  Correct Answer: A

  Data completeness is a measure of data quality that assesses whether all required data points are present in a dataset. It checks for missing values or gaps in data necessary for accurate analysis and decision-making. In the context of Salesforce, ensuring data completeness is crucial for the effectiveness of CRM operations, reporting, and AI-driven applications like Salesforce Einstein, which rely on complete data to function optimally. Salesforce provides various tools and features, such as data validation rules and batch data import processes, that help maintain data completeness across its platform. Detailed guidance on managing data quality in Salesforce can be found in the Salesforce Help documentation on data management at Salesforce Help Data Management.