Opleiding: AI+ Sales Practitioner™ eLearning

Formerly known as AI+ Sales™

Boost Sales Success Through AI-Driven Insights

• 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

Sales Executives: Use AI to automate sales processes and enhance customer relationship management for improved sales performance.

Marketing Professionals: Integrate AI with marketing strategies to customer targeting, personalization, and engagement.

Business Development Managers: Leverage AI-driven insights to identify new business opportunities and drive growth.

Product Managers: Utilize AI to understand customer needs, optimize pricing strategies, and improve product positioning.

Consultants: Help organizations implement AI-powered sales strategies that drive profitability and operational efficiency.

• Comprehensive AI Understanding:Learn core AI concepts for streamlined sales workflows, trend forecasting, and client engagement.
• Predictive Sales Analytics:Learn to leverage AI for predictive modeling, forecasting sales, and enhancing decision-making.
• AI-Enhanced Customer Insights:Explore AI tools to analyze behavior, automate scoring, and personalize outreach effectively.
• Ethical AI Integration:Gain insights on addressing ethical concerns and establishing AI governance in sales.

• 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

• 1. What are AI Agents
• 2. Types of AI Agents
• 3. Applications and Trend of AI Agents in Sales
• 4. Case studies
• 5. Hands-on

• Salesforce Einstein
• Conversica
• Uniphore

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

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  Take your certification exam with one free retake.
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