Salesforce AI Specialist Practice Exam

Disable ads (and more) with a membership for a one time $2.99 payment

Boost your career with the Salesforce AI Specialist Test. Engage with multiple-choice questions featuring explanations and hints. Prepare effectively with our comprehensive resources. Get exam-ready!

Each practice test/flash card set has 50 randomly selected questions from a bank of over 500. You'll get a new set of questions each time!

Practice this question and more.

What type of data is not recommended for training a lead conversion model?

Historical data from fully converted leads.
The most recent data from a prior sales quarter.
Data from both converted and non-converted leads.
Data skewed towards leads with low engagement.

The correct answer is: Data skewed towards leads with low engagement.

Training a lead conversion model with data skewed towards leads with low engagement is not recommended because such data does not represent the characteristics or behaviors that are most indicative of successful conversions. A model trained on this type of data may struggle to learn the relevant patterns and insights that drive effective lead conversion, leading to poor performance in actual lead scoring and conversion tasks. Using historical data from fully converted leads offers a rich source of information about successful conversions and helps the model understand what factors contribute to lead success. Recent data from a prior sales quarter can provide context on current market conditions and lead behaviors that are more relevant to the model’s predictive capabilities. Combining data from both converted and non-converted leads can present a comprehensive view of the lead landscape, allowing the model to learn from both successes and failures. In contrast, focusing on low engagement leads skews the training process towards examples that are less likely to convert, potentially resulting in a model that undervalues stronger leads or misidentifies high-potential contacts.