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AI+ Sales Practitioner™

AI+ Sales Practitioner™
  • Sales Transformation: Harness AI to boost sales operations, CRM integration, and forecasting
  • Hands-on Approach: Practical workshops covering AI tools and ethical sales practices
  • Data-Driven Insights: Learn to analyze, optimize, and automate sales processes
  • Growth-Oriented: Drive ethical business growth and maximize performance

 

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Certificate Code

AP-270

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Basic familiarity with sales processes, proficiency in data analysis, Primary knowledge of CRM systems
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  1. Course Introduction Preview

  1. 1.1 Fundamentals of AI
  2. 1.2 Historical Journey and Evolution of AI in Sales
  3. 1.3 AI Tools & Technologies Transforming Sales
  4. 1.4 Benefits and Challenges in Adoption of AI in Sales
  5. 1.5 Real-world Examples and Applications of AI in Sales
  6. 1.6 Future of AI in Sales

  1. 2.1 Categories of Sales Data
  2. 2.2 Techniques for Effective Data Collection
  3. 2.3 Basics of Data Analysis and Interpretation
  4. 2.4 Data Management Methods
  5. 2.5 Data Protection Principles
  6. 2.6 Data Integration in CRM Systems
  7. 2.7 Overview of Analytical Tools
  8. 2.8 Ethical Use of Sales Data
  9. 2.9 Case Studies: Real-World Data Applications

  1. 3.1 Introduction to Machine Learning in Sales
  2. 3.2 Predictive Analytics: Forecasting Sales Trends
  3. 3.3 NLP: Enhancing Customer Interactions
  4. 3.4 Chatbots: Automating Customer Service
  5. 3.5 Segmentation: Tailoring Customer Experiences
  6. 3.6 Personalization: Customizing Sales Approaches
  7. 3.7 Recommendation Engines: Driving Product Suggestions
  8. 3.8 Sales Automation: Streamlining Sales Processes
  9. 3.9 Performance Analysis: Measuring Sales Effectiveness

  1. 4.1 Foundation of CRM Systems
  2. 4.2 AI Integration into CRM Systems
  3. 4.3 Lead Scoring
  4. 4.4 Customer Insights
  5. 4.5 Sales Automation
  6. 4.6 Personalized Communication
  7. 4.7 Chatbots in CRM
  8. 4.8 Gaining Actionable Insights from Data
  9. 4.9 Case Studies

  1. 5.1 Introduction to Sales Forecasting
  2. 5.2 Overview of Predictive Models in Forecasting
  3. 5.3 Data Preparation for Analysis
  4. 5.4 Identifying Sales Patterns and Trends
  5. 5.5 Enhancing Forecast Reliability
  6. 5.6 Key Forecasting AI Tools in AI
  7. 5.7 Utilizing Real-time Data for Forecasts
  8. 5.8 Developing Forecasts for Different Outcomes
  9. 5.9 Measuring the Success of Sales Forecasts

  1. 6.1 Task Automation
  2. 6.2 AI-driven Email Marketing
  3. 6.3 Social Media with AI Analytics
  4. 6.4 AI-powered Lead Generation
  5. 6.5 Customer Segmentation
  6. 6.6 Optimizing Sales Visits and Calls
  7. 6.7 Tailoring Content with AI Insights
  8. 6.8 Real-time Sales Activity Monitoring
  9. 6.9 Upselling and Cross-selling with AI

  1. 7.1 Ethical Use of AI in Sales
  2. 7.2 Bias Identification in AI Systems
  3. 7.3 Bias Mitigation
  4. 7.4 Transparency in AI Decision-Making
  5. 7.5 Accountability for AI Actions
  6. 7.6 Safeguarding Customer Data
  7. 7.7 Regulatory Compliance
  8. 7.8 Building Customer Trust through Ethical AI
  9. 7.9 Anticipating Ethical Issues in AI Advancements

  1. 8.1 Scenario-Based Exercises
  2. 8.2 Addressing Sales Challenges with AI
  3. 8.3 Collaborative AI Implementation Plans

  1. 1. What Are AI Agents
  2. 2. Types of AI Agents
  3. 3. Applications and Trend of AI Agents in Sales

AI Tools Covered

Salesforce Einstein
Conversica
Uniphore
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