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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
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
- Course Introduction Preview
- 1.1 Fundamentals of AI
- 1.2 Generative AI and Modern Evolution of AI in Sales
- 1.3 AI Tools and Technologies that Transform Sales
- 1.4 Benefits and Challenges in the Adoption of AI in Sales
- 1.5 Real-world Examples and Applications of AI in Sales
- 1.6 The Future of AI in Sales
- 2.1 Categories of Sales Data
- 2.2 Techniques for Effective Data Collection
- 2.3 Basic Concepts of Data Analysis and Interpretation
- 2.4 Data Management Methods
- 2.5 Data Protection Principles
- 2.6 Data Integration in CRM Systems
- 2.7 Overview of Analytical Tools
- 2.8 Ethical Use of Sales Data
- 2.9 Case Studies: Real-World Data Applications
- 3.1 Introduction to Machine Learning in Sales
- 3.2 Predictive Analytics: Sales Trend Forecasting
- 3.3 NLP for Enhancing Customer Interactions
- 3.4 Chatbots: Customer Service Automation
- 3.5 Segmentation: Tailoring Customer Experiences
- 3.6 Personalization: Customizing Sales Approaches
- 3.7 Recommendation Engines: Driving Product Suggestions
- 3.8 Sales Automation: Streamlining Sales Processes
- 3.9 Performance Analysis: Measuring Sales Effectiveness
- 3.10 Modern AI Sales Stack: Generative AI, Copilots, and Intelligent Workflows
- 4.1 Foundation of CRM Systems
- 4.2 AI Integration into CRM Systems
- 4.3 Lead Scoring
- 4.4 Customer Insights
- 4.5 Sales Automation
- 4.6 Personalized Communication
- 4.7 Chatbots and CRM
- 4.8 Gaining Actionable Insights from Data
- 4.9 Case Studies
- 4.10 Modern AI CRM Stack: Tools, Integrations, and Execution Layer
- 5.1 Introduction to Sales Forecasting
- 5.2 Overview of Predictive Models in Forecasting
- 5.3 Data Preparation for Analysis
- 5.4 Identifying Sales Patterns and Trends
- 5.5 Enhancing Forecast Reliability
- 5.6 Key Forecasting AI Tools in AI
- 5.7 Utilizing Real-time Data for Forecasts
- 5.8 Developing Forecasts for Different Outcomes
- 5.9 Measuring the Success of Sales Forecasts
- 5.10 Case Study – How SaaS Companies Forecast Revenue Using AI
- 6.1 Task Automation
- 6.2 AI-driven Email Marketing
- 6.3 Social Media with AI Analytics
- 6.4 AI-Powered Lead Generation
- 6.5 Customer Segmentation
- 6.6 Optimization of Sales Visits and Calls
- 6.7 Tailoring Content with AI Insights
- 6.8 Real-Time Sales Activity Monitoring
- 6.9 Upselling and Cross-selling with AI
- 7.1 Ethical Use of AI in Sales
- 7.2 Bias Identification in AI Systems
- 7.3 Bias Mitigation
- 7.4 Transparency in AI Decision Making
- 7.5 Accountability for AI Actions
- 7.6 Safeguarding Customer Data
- 7.7 Regulatory Compliance
- 7.8 Building Customer Trust through Ethical AI
- 7.9 Anticipating Ethical Problems in AI Advancements
- 8.1 Scenario-Based Exercises
- 8.2 Addressing Sales Challenges with AI
- 8.3 Collaborative AI Implementation Plans
- 8.4 Hands-On Workshop: AI-Powered Sales Execution using HubSpot CRM
- 1. What are AI Agents
- 2. Types of AI Agents
- 3. Applications and Trend of AI Agents in Sales4. Case studies5. Hands-on