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AI+ Sales™ Self-Paced Learning
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Module 01: Introduction to Artificial Intelligence (AI) in Sales
1.0 Introduction: Introduction to Artificial Intelligence (AI) in Sales
1.1 Characteristics of AI
1.2 Key Components of AI
1.3 Role of AI in Sales
1.4 Advanced Technologies in Business Forecasting
1.5 Challenges
1.6 Applications of AI
1.7 Virtual Sales Assistants
1.8 Predictive Analytics
1.9 Automated Data Analysis
1.10 Sales Process Optimization
1.11 Augmented Reality (AR) in Sales
1.12 Transformation through AI
1.13 Summary: Introduction to Artificial Intelligence (AI) in Sales
Module 1: E-Book
Quiz
Module 02: Understanding Data in Sales
2.0 Introduction: Understanding Data in Sales
2.1 Types of Sales Data
2.2 Significance of Data Types in Sales
2.3 Primary and Secondary Data Collection Techniques
2.4 Importance of Data Interpretation in Sales
2.5 Data Collection, Preparation, and Descriptive Analysis
2.6 Inferential Analysis
2.7 Data Visualization
2.8 Data Interpretation Milestones
2.9 Data Management Methods
2.10 Data Protection Principles
2.11 Data Integration in CRM Systems
2.12 Ethical Use of Sales Data
2.13 Summary: Understanding Data in Sales
Module 2: E-Book
Quiz
Module 03: AI Technologies for Sales
3.0 Introduction: AI Technologies for Sales
3.1 Understanding Machine Learning
3.2 Role of Machine Learning in Sales
3.3 Applications of Machine Learning in Sales
3.4 Challenges and Considerations in Implementing ML in Sales
3.5 Predictive Analytics: Forecasting Sales Trends
3.6 Importance of Customer Interactions
3.7 Understanding Natural Language Processing (NLP)
3.8 Understanding Chatbots
3.9 Benefits of Chatbots in Customer Service
3.10 How Chatbots Work
3.11 Best Practices for Implementing Chatbots
3.12 Segmentation: Tailoring Customer Experiences
3.13 Personalization: Customizing Sales Approaches
3.14 Recommendation Engines: Driving Product Suggestions
3.15 Sales Automation: Streamlining Sales Processes
3.16 Performance Analysis: Measuring Sales Effectiveness
3.17 Summary: AI Technologies for Sales
Module 03: E-Book
Quiz
Module 04: Implementation of AI in CRM Systems
4.0 Introduction: Implementation of AI in CRM Systems
4.1 Foundation of CRM Systems
4.2 AI Integration into CRM Systems
4.3 Lead Scoring
4.4 Streamlining Lead Management
4.5 Automating Communication, Improving Sales Forecasting and Reporting
4.6 Enhancing Collaboration and Knowledge Sharing
4.7 Integrating AI-powered Sales
4.8 Benefits of Chatbots in CRM
4.9 Implementing Chatbots in CRM
4.10 Gaining Actionable Insights from Data
4.11 Summary: Implementation of AI in CRM Systems
Module 4: E-Book
Quiz
Module 05: Sales Forecasting with AI
5.0 Introduction: Sales Forecasting with AI
5.1 Introduction to Sales Forecasting and Key Concepts
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 Process and Benefits of Scenario Planning
5.7 Sales Forecast Accuracy
5.8 Forecast Bias, Gain and Loss
5.9 Summary: Sales Forecasting with AI
Module 5: E-Book
Quiz
Module 06: Enhancing Sales Processes with AI
6.0 Introduction: Enhancing Sales Processes with AI
6.1 Maximizing Sales Efficiency with Task Automation
6.2 AI-driven Personalization in Email Marketing
6.3 AI-driven Email Marketing Strategies and Best Practices
6.4 Understanding AI Analytics
6.5 Sentiment Analysis
6.6 Predictive Analytics
6.7 Social Listening
6.8 Audience Segmentation and Optimizing Social Media Advertisements
6.9 AI-powered Lead Generation
6.10 Optimizing Sales Visits and Calls
6.11 Importance of Customer Segmentation
6.12 Tailoring Content with AI Insights
6.13 Real-Time Sales Activity Monitoring
6.14 Upselling and Cross-selling with AI
6.15 Summary: Enhancing Sales Processes with AI
Module 6: E-Book
Quiz
Resources
AI+ Sales Tools
AI+ Sales Blueprint
AI+ Sales Detailed Curriculum
AI+ Sales Reference Videos and Links
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Sales Examination
AI+ Sales Examination
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AI+ Sales™ Self-Paced Learning
