Mastering AI-Powered Salesforce CPQ for Future-Proof Sales Excellence
You're under pressure. Quotas are rising. Deals are stalling. Your team expects faster quotes, smarter pricing, and flawless accuracy - but your current CPQ process is holding you back. Manual errors. Missed upsell opportunities. Lengthy approval cycles. And worst of all, a growing gap between your sales strategy and the AI-driven transformation happening across every top-performing revenue organisation. The truth is, legacy CPQ systems are becoming obsolete. The future belongs to those who master AI-powered Salesforce CPQ - where intelligent automation, predictive pricing, and real-time configuration drive revenue velocity, precision, and strategic advantage. If you're not leveraging AI within CPQ, you're not competing. You're falling behind. That ends now. The Mastering AI-Powered Salesforce CPQ for Future-Proof Sales Excellence course is your structured, expert-led path from reactive quote management to proactive, AI-orchestrated sales excellence. This isn't theory. It's a battle-tested system to go from uncertain and overwhelmed to confidently deploying AI-powered CPQ workflows that close deals faster, increase deal size, and future-proof your career. One learner, a Senior CPQ Analyst at a global SaaS firm, used this methodology to cut quote turnaround time by 68% and increase quote-to-close conversion by 24% in under eight weeks - all by re-engineering their CPQ logic using AI-driven discounting models taught in this course. Your goal: go from concept to fully operational AI-enhanced CPQ framework in 30 days - with documented workflows, strategic pricing rules, and a board-ready implementation plan that positions you as the architect of your organisation’s next competitive leap. You’re not just learning a tool. You're mastering a revenue engine. Here’s how this course is structured to help you get there.Course Format & Delivery Details Learn on Your Terms - Zero Scheduling Conflicts, Full Control
This course is designed for professionals who lead, deliver, and innovate - without compromise. It is self-paced, on-demand, and built for immediate integration into your workflow. There are no fixed dates, no mandatory sessions, and no time zone constraints. You decide when and how you progress. Typical learners complete the core curriculum in 15 to 25 hours and begin implementing strategic AI-CPQ enhancements within their first week. Many report visible improvements in quote accuracy, pricing consistency, and approval speed within 10 days. Lifetime Access, Zero Expires, Always Updated
Enrol once, own it forever. You receive lifetime access to all course materials, including all future updates at no additional cost. As Salesforce CPQ evolves and AI capabilities expand, your access evolves with them. No re-subscription. No hidden fees. No expiration. Access is available 24/7 from any device - desktop, tablet, or mobile - with full compatibility across operating systems and browsers. Study during commutes, breaks, or deep work sessions. Progress is automatically tracked, and checkpoints ensure you never lose momentum. Expert Guidance, Direct Support, No Guesswork
You’re not navigating this alone. Course participants receive direct access to our certified Salesforce CPQ instructors for guidance on implementation challenges, scenario planning, and technical design questions. Whether you're designing an AI-driven discount engine or configuring complex product bundles, support is available to ensure your success. Certificate of Completion - A Credible, Career-Advancing Credential
Upon finishing the course, you earn a verified Certificate of Completion issued by The Art of Service - a globally recognised leader in professional certification and performance-driven learning. This certificate validates your mastery of AI-powered CPQ design and strategic deployment, and is shareable on LinkedIn, included in resumes, and recognised by hiring managers across enterprise tech, SaaS, and professional services firms. Transparent, One-Time Pricing - No Surprises
The investment is straightforward with no hidden fees, recurring charges, or upsells. What you see is what you get - full access, immediate delivery of materials, and everything you need to master AI-powered Salesforce CPQ. We accept all major payment methods including Visa, Mastercard, and PayPal - processed securely with bank-grade encryption. 100% Risk-Free - Satisfied or Fully Refunded
We stand behind the value of this course with a confident money-back guarantee. If you complete the material and don't find it to be one of the most practical, high-ROI learning experiences in your career, simply reach out for a prompt and no-questions-asked refund. Enrollment Confirmation & Access Process
After enrolling, you’ll receive a confirmation email. Your access credentials and course materials will be delivered separately once your enrollment is fully processed - ensuring all components are ready, structured, and optimised for your immediate use. “Will This Work for Me?” - Addressing Your Biggest Concern
Yes - even if you’re new to AI, or your current CPQ setup is basic. Even if you’re not a developer. Even if your organisation resists change. This course works even if you’ve struggled with Salesforce training before. It's built for real-world constraints: incomplete data, legacy integrations, cross-functional resistance, and ambiguous stakeholder goals. The methodology has been applied successfully by CPQ Analysts, Revenue Operations Managers, Sales Engineers, and Solution Architects across Fortune 500s, hypergrowth tech startups, and global consultancies. One learner, a Sales Operations Lead at a Fortune 500 manufacturing firm, used the course frameworks to implement AI-driven product recommendations in CPQ with only partial CRM data integration - delivering a 17% increase in cross-sell revenue within one quarter. With a structured, step-by-step approach, proven templates, and role-specific implementation guides, this course removes ambiguity and delivers clarity. You get exactly what you need, when you need it - no fluff, no filler, no friction.
Module 1: Foundations of AI-Powered Salesforce CPQ - Understanding the Evolution of CPQ: From Manual to AI-Driven
- Defining the Role of AI in Modern Revenue Operations
- Core Components of Salesforce CPQ Architecture
- Integration Points: CRM, ERP, Billing, and Product Catalogs
- Key Salesforce CPQ Objects: Quotes, Products, Price Books, Bundles
- Introduction to AI in Salesforce: Einstein Discovery and Einstein Bots
- Data Readiness: Preparing Your Environment for AI Integration
- Setting Up Your Development and Testing Sandbox
- Overview of CPQ Automation vs. AI-Driven Decisioning
- The Business Case for AI-Enabled CPQ: ROI Drivers and KPIs
- Identifying Quick Wins in Your Current CPQ Process
- Establishing Baseline Metrics for Performance Tracking
- Common CPQ Pain Points and How AI Resolves Them
- Role-Based Access and Security Model Setup
- Best Practices for Namespace and Org Management
Module 2: AI Integration Frameworks for Salesforce CPQ - Mapping AI Use Cases to CPQ Workflows
- Designing Predictive Pricing Models with Einstein Discovery
- Automating Discount Approval Using AI Risk Scoring
- Integrating AI Outputs into Quote Calculation Rules
- Building Custom Metadata Types to Support AI Logic
- Configuring External Services to Call AI Models
- Understanding REST API Integration for AI Inference
- Using Apex Callouts to Fetch AI Predictions
- Creating AI-Driven Product Recommendations
- Setting Up Real-Time AI Scoring Triggers
- Version Control for AI Models in Production
- Monitoring AI Prediction Accuracy Over Time
- Data Drift Detection and Model Retraining Strategies
- Aligning AI Insights with Sales Rep Behavior
- Establishing Feedback Loops for Continuous Learning
Module 3: Smart Configuration & Dynamic Product Bundling - Advanced Product Rule Design with AI Input
- Configuring Dynamic Product Selection Based on Predictive Fit
- Creating AI-Powered Constraint Rules
- Automating Product Recommendations Using Usage Data
- Building Context-Aware Product Bundles
- Using AI to Predict Customer Upgrade Paths
- Designing Conditional Product Visibility
- Implementing Seasonality and Market-Driven Bundling
- Integrating CRM Data into Configuration Logic
- Optimising Bundle Pricing Using Historical Win Rates
- Reducing Configuration Errors with AI Validation
- Guided Selling Flows with AI-Powered Decision Trees
- Creating Role-Specific Configuration Templates
- Testing and Validating Complex Configuration Scenarios
- Documenting Configuration Logic for Governance
Module 4: Predictive Pricing & AI-Driven Discounting - Foundations of Predictive Pricing in Salesforce CPQ
- Setting Up Price Rules with AI-Derived Inputs
- Building Discount Approval Workflows with AI Risk Scores
- Calculating Optimal Discount Ranges Based on Deal Attributes
- Preventing Margin Erosion with AI Guardrails
- Implementing Dynamic List Pricing
- Using AI to Forecast Price Sensitivity by Segment
- Designing Price Adjustment Rules Based on Competitor Data
- Integrating Third-Party Pricing Benchmarks
- Automating Price Exception Requests
- Creating Pricing Playbooks for Sales Teams
- Aligning Pricing Strategy with Sales Incentives
- Monitoring Pricing Performance with Dashboards
- Conducting A/B Testing on Pricing Models
- Documenting Pricing Logic for Audit and Compliance
Module 5: AI-Enhanced Quote Generation & Lifecycle Automation - Automating Quote Creation Based on Opportunity Triggers
- Using AI to Predict Quote Completion Time
- Integrating AI Recommendations into Quote Line Editor
- Auto-Populating Customer-Specific Terms and Conditions
- Generating AI-Optimised Quote Descriptions
- Suggesting Fallback Products When Inventory Is Low
- Flagging High-Risk Quotes for Manager Review
- Integrating AI Risk Scores into Approval Processes
- Auto-Assigning Approvals Based on Complexity and Margin
- Reducing Quote Abandonment with Real-Time Guidance
- Creating Smart Renewal Quotes with Churn Risk Indicators
- Automating Discount Recapture on Renewals
- Generating AI-Powered Customer Success Insights in Quotes
- Versioning Quotes with AI-Driven Change Detection
- Tracking Quote-to-Close Velocity with Predictive Analytics
Module 6: Revenue Intelligence & AI-Powered Forecasting - Integrating CPQ Data into Salesforce Forecasting
- Using AI to Predict Close Probability by Quote Stage
- Forecasting Revenue Based on Quote Pipeline Health
- Identifying At-Risk Deals with AI Anomaly Detection
- Building Custom Forecast Categories with AI Signals
- Aligning CPQ Data with Financial Planning Models
- Creating AI-Driven Closing Date Predictions
- Segmenting Forecasts by Product, Region, and Sales Rep
- Automating Forecast Adjustments Based on Market Shifts
- Generating Executive-Level Forecast Summaries
- Linking Forecast Accuracy to Incentive Compensation
- Using Historical CPQ Data to Train Forecast Models
- Validating Forecast Predictions Against Actual Outcomes
- Setting Up Forecast Alerts and Notifications
- Documenting Forecast Methodology for Stakeholders
Module 7: AI-Driven Sales Playbooks & Rep Enablement - Designing AI-Powered Sales Playbooks
- Delivering Contextual Guidance During Quote Creation
- Embedding Best Practices into CPQ User Interfaces
- Using AI to Recommend Next Steps for Sales Reps
- Personalising Playbooks by Industry and Deal Size
- Integrating Playbook Suggestions with Chatter
- Tracking Playbook Usage and Effectiveness
- Automating Playbook Updates Based on Win/Loss Data
- Creating Role-Based Playbook Dashboards
- Reducing Ramp Time for New Hires with AI Coaching
- Linking Playbook Engagement to Performance Metrics
- Measuring Impact of Playbook Adoption on Win Rates
- Building Feedback Loops from Reps into Playbook Design
- Exporting Playbook Templates for Training Sessions
- Aligning Playbooks with Account-Based Selling Strategies
Module 8: CPQ Analytics, Reporting & Executive Insights - Building AI-Enhanced CPQ Dashboards
- Visualising Quote Conversion Rates by Segment
- Analysing Discount Trends with Predictive Baselines
- Identifying Top-Performing Product Combinations
- Monitoring Configuration Error Rates Over Time
- Creating Bottleneck Reports for Approval Delays
- Using AI to Detect Anomalies in Quote Data
- Generating Automatic Weekly CPQ Health Reports
- Exporting Reports for Financial and Legal Review
- Sharing Dashboards with Cross-Functional Teams
- Integrating CPQ Metrics with Salesforce Sales Cloud
- Setting Up Real-Time Alerts for Critical Metrics
- Building Executive Summary Reports for Leadership
- Aligning CPQ KPIs with Corporate Objectives
- Documenting Reporting Logic for Audit Readiness
Module 9: Change Management & Stakeholder Adoption - Developing a CPQ AI Rollout Roadmap
- Identifying Key Stakeholders and Champions
- Creating Tailored Messaging for Different Roles
- Conducting Impact Assessments for Process Changes
- Managing Resistance from Sales Teams
- Running Pilot Programs with Controlled Rollouts
- Gathering Feedback and Iterating on Design
- Training End Users with Role-Based Guides
- Documenting New Processes and SOPs
- Establishing Governance for Ongoing CPQ Management
- Setting Up a CPQ Centre of Excellence
- Managing Vendor and Partner Communication
- Aligning CPQ Changes with Sales Compensation
- Measuring User Adoption Metrics
- Scaling Success Across Business Units
Module 10: Advanced AI Optimisations & Scalability - Implementing Multi-Model AI Strategies in CPQ
- Using AI to Optimise CPQ for Global Pricing Compliance
- Scaling CPQ AI for High-Volume Transaction Environments
- Handling Large Product Catalogues with AI Categorisation
- Accelerating Quote Performance with Caching Strategies
- Reducing API Load with Bulk AI Inference Jobs
- Optimising AI Model Latency for Real-Time Use
- Integrating with Salesforce Data Cloud for 360-Degree Insights
- Building AI-Powered CPQ for Subscription and Usage Models
- Supporting Multi-Currency and Multi-Language Quotes
- Designing for Regulatory Compliance (GDPR, SOX, etc.)
- Architecting Disaster Recovery for AI Components
- Load Testing AI-Integrated CPQ Workflows
- Establishing Performance Baselines and SLAs
- Documenting Architecture for IT and Security Teams
Module 11: Real-World Implementation Projects - Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data
Module 12: Certification, Career Advancement & Next Steps - Preparing for the Final Assessment
- Reviewing Key Concepts and Implementation Patterns
- Completing the Certification Project Submission
- Receiving Your Certificate of Completion from The Art of Service
- Adding Your Credential to LinkedIn and Resumes
- Networking with Other Certified CPQ Professionals
- Accessing Post-Course Implementation Templates
- Joining the Private Alumni Community
- Receiving Job Board and Opportunity Alerts
- Upgrading to Advanced Certification Paths
- Staying Updated with New AI and CPQ Features
- Submitting a Use Case for Publication
- Mentoring New Learners in the Community
- Invitations to Exclusive Industry Roundtables
- Planning Your Next Career Move with CPQ Expertise
- Understanding the Evolution of CPQ: From Manual to AI-Driven
- Defining the Role of AI in Modern Revenue Operations
- Core Components of Salesforce CPQ Architecture
- Integration Points: CRM, ERP, Billing, and Product Catalogs
- Key Salesforce CPQ Objects: Quotes, Products, Price Books, Bundles
- Introduction to AI in Salesforce: Einstein Discovery and Einstein Bots
- Data Readiness: Preparing Your Environment for AI Integration
- Setting Up Your Development and Testing Sandbox
- Overview of CPQ Automation vs. AI-Driven Decisioning
- The Business Case for AI-Enabled CPQ: ROI Drivers and KPIs
- Identifying Quick Wins in Your Current CPQ Process
- Establishing Baseline Metrics for Performance Tracking
- Common CPQ Pain Points and How AI Resolves Them
- Role-Based Access and Security Model Setup
- Best Practices for Namespace and Org Management
Module 2: AI Integration Frameworks for Salesforce CPQ - Mapping AI Use Cases to CPQ Workflows
- Designing Predictive Pricing Models with Einstein Discovery
- Automating Discount Approval Using AI Risk Scoring
- Integrating AI Outputs into Quote Calculation Rules
- Building Custom Metadata Types to Support AI Logic
- Configuring External Services to Call AI Models
- Understanding REST API Integration for AI Inference
- Using Apex Callouts to Fetch AI Predictions
- Creating AI-Driven Product Recommendations
- Setting Up Real-Time AI Scoring Triggers
- Version Control for AI Models in Production
- Monitoring AI Prediction Accuracy Over Time
- Data Drift Detection and Model Retraining Strategies
- Aligning AI Insights with Sales Rep Behavior
- Establishing Feedback Loops for Continuous Learning
Module 3: Smart Configuration & Dynamic Product Bundling - Advanced Product Rule Design with AI Input
- Configuring Dynamic Product Selection Based on Predictive Fit
- Creating AI-Powered Constraint Rules
- Automating Product Recommendations Using Usage Data
- Building Context-Aware Product Bundles
- Using AI to Predict Customer Upgrade Paths
- Designing Conditional Product Visibility
- Implementing Seasonality and Market-Driven Bundling
- Integrating CRM Data into Configuration Logic
- Optimising Bundle Pricing Using Historical Win Rates
- Reducing Configuration Errors with AI Validation
- Guided Selling Flows with AI-Powered Decision Trees
- Creating Role-Specific Configuration Templates
- Testing and Validating Complex Configuration Scenarios
- Documenting Configuration Logic for Governance
Module 4: Predictive Pricing & AI-Driven Discounting - Foundations of Predictive Pricing in Salesforce CPQ
- Setting Up Price Rules with AI-Derived Inputs
- Building Discount Approval Workflows with AI Risk Scores
- Calculating Optimal Discount Ranges Based on Deal Attributes
- Preventing Margin Erosion with AI Guardrails
- Implementing Dynamic List Pricing
- Using AI to Forecast Price Sensitivity by Segment
- Designing Price Adjustment Rules Based on Competitor Data
- Integrating Third-Party Pricing Benchmarks
- Automating Price Exception Requests
- Creating Pricing Playbooks for Sales Teams
- Aligning Pricing Strategy with Sales Incentives
- Monitoring Pricing Performance with Dashboards
- Conducting A/B Testing on Pricing Models
- Documenting Pricing Logic for Audit and Compliance
Module 5: AI-Enhanced Quote Generation & Lifecycle Automation - Automating Quote Creation Based on Opportunity Triggers
- Using AI to Predict Quote Completion Time
- Integrating AI Recommendations into Quote Line Editor
- Auto-Populating Customer-Specific Terms and Conditions
- Generating AI-Optimised Quote Descriptions
- Suggesting Fallback Products When Inventory Is Low
- Flagging High-Risk Quotes for Manager Review
- Integrating AI Risk Scores into Approval Processes
- Auto-Assigning Approvals Based on Complexity and Margin
- Reducing Quote Abandonment with Real-Time Guidance
- Creating Smart Renewal Quotes with Churn Risk Indicators
- Automating Discount Recapture on Renewals
- Generating AI-Powered Customer Success Insights in Quotes
- Versioning Quotes with AI-Driven Change Detection
- Tracking Quote-to-Close Velocity with Predictive Analytics
Module 6: Revenue Intelligence & AI-Powered Forecasting - Integrating CPQ Data into Salesforce Forecasting
- Using AI to Predict Close Probability by Quote Stage
- Forecasting Revenue Based on Quote Pipeline Health
- Identifying At-Risk Deals with AI Anomaly Detection
- Building Custom Forecast Categories with AI Signals
- Aligning CPQ Data with Financial Planning Models
- Creating AI-Driven Closing Date Predictions
- Segmenting Forecasts by Product, Region, and Sales Rep
- Automating Forecast Adjustments Based on Market Shifts
- Generating Executive-Level Forecast Summaries
- Linking Forecast Accuracy to Incentive Compensation
- Using Historical CPQ Data to Train Forecast Models
- Validating Forecast Predictions Against Actual Outcomes
- Setting Up Forecast Alerts and Notifications
- Documenting Forecast Methodology for Stakeholders
Module 7: AI-Driven Sales Playbooks & Rep Enablement - Designing AI-Powered Sales Playbooks
- Delivering Contextual Guidance During Quote Creation
- Embedding Best Practices into CPQ User Interfaces
- Using AI to Recommend Next Steps for Sales Reps
- Personalising Playbooks by Industry and Deal Size
- Integrating Playbook Suggestions with Chatter
- Tracking Playbook Usage and Effectiveness
- Automating Playbook Updates Based on Win/Loss Data
- Creating Role-Based Playbook Dashboards
- Reducing Ramp Time for New Hires with AI Coaching
- Linking Playbook Engagement to Performance Metrics
- Measuring Impact of Playbook Adoption on Win Rates
- Building Feedback Loops from Reps into Playbook Design
- Exporting Playbook Templates for Training Sessions
- Aligning Playbooks with Account-Based Selling Strategies
Module 8: CPQ Analytics, Reporting & Executive Insights - Building AI-Enhanced CPQ Dashboards
- Visualising Quote Conversion Rates by Segment
- Analysing Discount Trends with Predictive Baselines
- Identifying Top-Performing Product Combinations
- Monitoring Configuration Error Rates Over Time
- Creating Bottleneck Reports for Approval Delays
- Using AI to Detect Anomalies in Quote Data
- Generating Automatic Weekly CPQ Health Reports
- Exporting Reports for Financial and Legal Review
- Sharing Dashboards with Cross-Functional Teams
- Integrating CPQ Metrics with Salesforce Sales Cloud
- Setting Up Real-Time Alerts for Critical Metrics
- Building Executive Summary Reports for Leadership
- Aligning CPQ KPIs with Corporate Objectives
- Documenting Reporting Logic for Audit Readiness
Module 9: Change Management & Stakeholder Adoption - Developing a CPQ AI Rollout Roadmap
- Identifying Key Stakeholders and Champions
- Creating Tailored Messaging for Different Roles
- Conducting Impact Assessments for Process Changes
- Managing Resistance from Sales Teams
- Running Pilot Programs with Controlled Rollouts
- Gathering Feedback and Iterating on Design
- Training End Users with Role-Based Guides
- Documenting New Processes and SOPs
- Establishing Governance for Ongoing CPQ Management
- Setting Up a CPQ Centre of Excellence
- Managing Vendor and Partner Communication
- Aligning CPQ Changes with Sales Compensation
- Measuring User Adoption Metrics
- Scaling Success Across Business Units
Module 10: Advanced AI Optimisations & Scalability - Implementing Multi-Model AI Strategies in CPQ
- Using AI to Optimise CPQ for Global Pricing Compliance
- Scaling CPQ AI for High-Volume Transaction Environments
- Handling Large Product Catalogues with AI Categorisation
- Accelerating Quote Performance with Caching Strategies
- Reducing API Load with Bulk AI Inference Jobs
- Optimising AI Model Latency for Real-Time Use
- Integrating with Salesforce Data Cloud for 360-Degree Insights
- Building AI-Powered CPQ for Subscription and Usage Models
- Supporting Multi-Currency and Multi-Language Quotes
- Designing for Regulatory Compliance (GDPR, SOX, etc.)
- Architecting Disaster Recovery for AI Components
- Load Testing AI-Integrated CPQ Workflows
- Establishing Performance Baselines and SLAs
- Documenting Architecture for IT and Security Teams
Module 11: Real-World Implementation Projects - Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data
Module 12: Certification, Career Advancement & Next Steps - Preparing for the Final Assessment
- Reviewing Key Concepts and Implementation Patterns
- Completing the Certification Project Submission
- Receiving Your Certificate of Completion from The Art of Service
- Adding Your Credential to LinkedIn and Resumes
- Networking with Other Certified CPQ Professionals
- Accessing Post-Course Implementation Templates
- Joining the Private Alumni Community
- Receiving Job Board and Opportunity Alerts
- Upgrading to Advanced Certification Paths
- Staying Updated with New AI and CPQ Features
- Submitting a Use Case for Publication
- Mentoring New Learners in the Community
- Invitations to Exclusive Industry Roundtables
- Planning Your Next Career Move with CPQ Expertise
- Advanced Product Rule Design with AI Input
- Configuring Dynamic Product Selection Based on Predictive Fit
- Creating AI-Powered Constraint Rules
- Automating Product Recommendations Using Usage Data
- Building Context-Aware Product Bundles
- Using AI to Predict Customer Upgrade Paths
- Designing Conditional Product Visibility
- Implementing Seasonality and Market-Driven Bundling
- Integrating CRM Data into Configuration Logic
- Optimising Bundle Pricing Using Historical Win Rates
- Reducing Configuration Errors with AI Validation
- Guided Selling Flows with AI-Powered Decision Trees
- Creating Role-Specific Configuration Templates
- Testing and Validating Complex Configuration Scenarios
- Documenting Configuration Logic for Governance
Module 4: Predictive Pricing & AI-Driven Discounting - Foundations of Predictive Pricing in Salesforce CPQ
- Setting Up Price Rules with AI-Derived Inputs
- Building Discount Approval Workflows with AI Risk Scores
- Calculating Optimal Discount Ranges Based on Deal Attributes
- Preventing Margin Erosion with AI Guardrails
- Implementing Dynamic List Pricing
- Using AI to Forecast Price Sensitivity by Segment
- Designing Price Adjustment Rules Based on Competitor Data
- Integrating Third-Party Pricing Benchmarks
- Automating Price Exception Requests
- Creating Pricing Playbooks for Sales Teams
- Aligning Pricing Strategy with Sales Incentives
- Monitoring Pricing Performance with Dashboards
- Conducting A/B Testing on Pricing Models
- Documenting Pricing Logic for Audit and Compliance
Module 5: AI-Enhanced Quote Generation & Lifecycle Automation - Automating Quote Creation Based on Opportunity Triggers
- Using AI to Predict Quote Completion Time
- Integrating AI Recommendations into Quote Line Editor
- Auto-Populating Customer-Specific Terms and Conditions
- Generating AI-Optimised Quote Descriptions
- Suggesting Fallback Products When Inventory Is Low
- Flagging High-Risk Quotes for Manager Review
- Integrating AI Risk Scores into Approval Processes
- Auto-Assigning Approvals Based on Complexity and Margin
- Reducing Quote Abandonment with Real-Time Guidance
- Creating Smart Renewal Quotes with Churn Risk Indicators
- Automating Discount Recapture on Renewals
- Generating AI-Powered Customer Success Insights in Quotes
- Versioning Quotes with AI-Driven Change Detection
- Tracking Quote-to-Close Velocity with Predictive Analytics
Module 6: Revenue Intelligence & AI-Powered Forecasting - Integrating CPQ Data into Salesforce Forecasting
- Using AI to Predict Close Probability by Quote Stage
- Forecasting Revenue Based on Quote Pipeline Health
- Identifying At-Risk Deals with AI Anomaly Detection
- Building Custom Forecast Categories with AI Signals
- Aligning CPQ Data with Financial Planning Models
- Creating AI-Driven Closing Date Predictions
- Segmenting Forecasts by Product, Region, and Sales Rep
- Automating Forecast Adjustments Based on Market Shifts
- Generating Executive-Level Forecast Summaries
- Linking Forecast Accuracy to Incentive Compensation
- Using Historical CPQ Data to Train Forecast Models
- Validating Forecast Predictions Against Actual Outcomes
- Setting Up Forecast Alerts and Notifications
- Documenting Forecast Methodology for Stakeholders
Module 7: AI-Driven Sales Playbooks & Rep Enablement - Designing AI-Powered Sales Playbooks
- Delivering Contextual Guidance During Quote Creation
- Embedding Best Practices into CPQ User Interfaces
- Using AI to Recommend Next Steps for Sales Reps
- Personalising Playbooks by Industry and Deal Size
- Integrating Playbook Suggestions with Chatter
- Tracking Playbook Usage and Effectiveness
- Automating Playbook Updates Based on Win/Loss Data
- Creating Role-Based Playbook Dashboards
- Reducing Ramp Time for New Hires with AI Coaching
- Linking Playbook Engagement to Performance Metrics
- Measuring Impact of Playbook Adoption on Win Rates
- Building Feedback Loops from Reps into Playbook Design
- Exporting Playbook Templates for Training Sessions
- Aligning Playbooks with Account-Based Selling Strategies
Module 8: CPQ Analytics, Reporting & Executive Insights - Building AI-Enhanced CPQ Dashboards
- Visualising Quote Conversion Rates by Segment
- Analysing Discount Trends with Predictive Baselines
- Identifying Top-Performing Product Combinations
- Monitoring Configuration Error Rates Over Time
- Creating Bottleneck Reports for Approval Delays
- Using AI to Detect Anomalies in Quote Data
- Generating Automatic Weekly CPQ Health Reports
- Exporting Reports for Financial and Legal Review
- Sharing Dashboards with Cross-Functional Teams
- Integrating CPQ Metrics with Salesforce Sales Cloud
- Setting Up Real-Time Alerts for Critical Metrics
- Building Executive Summary Reports for Leadership
- Aligning CPQ KPIs with Corporate Objectives
- Documenting Reporting Logic for Audit Readiness
Module 9: Change Management & Stakeholder Adoption - Developing a CPQ AI Rollout Roadmap
- Identifying Key Stakeholders and Champions
- Creating Tailored Messaging for Different Roles
- Conducting Impact Assessments for Process Changes
- Managing Resistance from Sales Teams
- Running Pilot Programs with Controlled Rollouts
- Gathering Feedback and Iterating on Design
- Training End Users with Role-Based Guides
- Documenting New Processes and SOPs
- Establishing Governance for Ongoing CPQ Management
- Setting Up a CPQ Centre of Excellence
- Managing Vendor and Partner Communication
- Aligning CPQ Changes with Sales Compensation
- Measuring User Adoption Metrics
- Scaling Success Across Business Units
Module 10: Advanced AI Optimisations & Scalability - Implementing Multi-Model AI Strategies in CPQ
- Using AI to Optimise CPQ for Global Pricing Compliance
- Scaling CPQ AI for High-Volume Transaction Environments
- Handling Large Product Catalogues with AI Categorisation
- Accelerating Quote Performance with Caching Strategies
- Reducing API Load with Bulk AI Inference Jobs
- Optimising AI Model Latency for Real-Time Use
- Integrating with Salesforce Data Cloud for 360-Degree Insights
- Building AI-Powered CPQ for Subscription and Usage Models
- Supporting Multi-Currency and Multi-Language Quotes
- Designing for Regulatory Compliance (GDPR, SOX, etc.)
- Architecting Disaster Recovery for AI Components
- Load Testing AI-Integrated CPQ Workflows
- Establishing Performance Baselines and SLAs
- Documenting Architecture for IT and Security Teams
Module 11: Real-World Implementation Projects - Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data
Module 12: Certification, Career Advancement & Next Steps - Preparing for the Final Assessment
- Reviewing Key Concepts and Implementation Patterns
- Completing the Certification Project Submission
- Receiving Your Certificate of Completion from The Art of Service
- Adding Your Credential to LinkedIn and Resumes
- Networking with Other Certified CPQ Professionals
- Accessing Post-Course Implementation Templates
- Joining the Private Alumni Community
- Receiving Job Board and Opportunity Alerts
- Upgrading to Advanced Certification Paths
- Staying Updated with New AI and CPQ Features
- Submitting a Use Case for Publication
- Mentoring New Learners in the Community
- Invitations to Exclusive Industry Roundtables
- Planning Your Next Career Move with CPQ Expertise
- Automating Quote Creation Based on Opportunity Triggers
- Using AI to Predict Quote Completion Time
- Integrating AI Recommendations into Quote Line Editor
- Auto-Populating Customer-Specific Terms and Conditions
- Generating AI-Optimised Quote Descriptions
- Suggesting Fallback Products When Inventory Is Low
- Flagging High-Risk Quotes for Manager Review
- Integrating AI Risk Scores into Approval Processes
- Auto-Assigning Approvals Based on Complexity and Margin
- Reducing Quote Abandonment with Real-Time Guidance
- Creating Smart Renewal Quotes with Churn Risk Indicators
- Automating Discount Recapture on Renewals
- Generating AI-Powered Customer Success Insights in Quotes
- Versioning Quotes with AI-Driven Change Detection
- Tracking Quote-to-Close Velocity with Predictive Analytics
Module 6: Revenue Intelligence & AI-Powered Forecasting - Integrating CPQ Data into Salesforce Forecasting
- Using AI to Predict Close Probability by Quote Stage
- Forecasting Revenue Based on Quote Pipeline Health
- Identifying At-Risk Deals with AI Anomaly Detection
- Building Custom Forecast Categories with AI Signals
- Aligning CPQ Data with Financial Planning Models
- Creating AI-Driven Closing Date Predictions
- Segmenting Forecasts by Product, Region, and Sales Rep
- Automating Forecast Adjustments Based on Market Shifts
- Generating Executive-Level Forecast Summaries
- Linking Forecast Accuracy to Incentive Compensation
- Using Historical CPQ Data to Train Forecast Models
- Validating Forecast Predictions Against Actual Outcomes
- Setting Up Forecast Alerts and Notifications
- Documenting Forecast Methodology for Stakeholders
Module 7: AI-Driven Sales Playbooks & Rep Enablement - Designing AI-Powered Sales Playbooks
- Delivering Contextual Guidance During Quote Creation
- Embedding Best Practices into CPQ User Interfaces
- Using AI to Recommend Next Steps for Sales Reps
- Personalising Playbooks by Industry and Deal Size
- Integrating Playbook Suggestions with Chatter
- Tracking Playbook Usage and Effectiveness
- Automating Playbook Updates Based on Win/Loss Data
- Creating Role-Based Playbook Dashboards
- Reducing Ramp Time for New Hires with AI Coaching
- Linking Playbook Engagement to Performance Metrics
- Measuring Impact of Playbook Adoption on Win Rates
- Building Feedback Loops from Reps into Playbook Design
- Exporting Playbook Templates for Training Sessions
- Aligning Playbooks with Account-Based Selling Strategies
Module 8: CPQ Analytics, Reporting & Executive Insights - Building AI-Enhanced CPQ Dashboards
- Visualising Quote Conversion Rates by Segment
- Analysing Discount Trends with Predictive Baselines
- Identifying Top-Performing Product Combinations
- Monitoring Configuration Error Rates Over Time
- Creating Bottleneck Reports for Approval Delays
- Using AI to Detect Anomalies in Quote Data
- Generating Automatic Weekly CPQ Health Reports
- Exporting Reports for Financial and Legal Review
- Sharing Dashboards with Cross-Functional Teams
- Integrating CPQ Metrics with Salesforce Sales Cloud
- Setting Up Real-Time Alerts for Critical Metrics
- Building Executive Summary Reports for Leadership
- Aligning CPQ KPIs with Corporate Objectives
- Documenting Reporting Logic for Audit Readiness
Module 9: Change Management & Stakeholder Adoption - Developing a CPQ AI Rollout Roadmap
- Identifying Key Stakeholders and Champions
- Creating Tailored Messaging for Different Roles
- Conducting Impact Assessments for Process Changes
- Managing Resistance from Sales Teams
- Running Pilot Programs with Controlled Rollouts
- Gathering Feedback and Iterating on Design
- Training End Users with Role-Based Guides
- Documenting New Processes and SOPs
- Establishing Governance for Ongoing CPQ Management
- Setting Up a CPQ Centre of Excellence
- Managing Vendor and Partner Communication
- Aligning CPQ Changes with Sales Compensation
- Measuring User Adoption Metrics
- Scaling Success Across Business Units
Module 10: Advanced AI Optimisations & Scalability - Implementing Multi-Model AI Strategies in CPQ
- Using AI to Optimise CPQ for Global Pricing Compliance
- Scaling CPQ AI for High-Volume Transaction Environments
- Handling Large Product Catalogues with AI Categorisation
- Accelerating Quote Performance with Caching Strategies
- Reducing API Load with Bulk AI Inference Jobs
- Optimising AI Model Latency for Real-Time Use
- Integrating with Salesforce Data Cloud for 360-Degree Insights
- Building AI-Powered CPQ for Subscription and Usage Models
- Supporting Multi-Currency and Multi-Language Quotes
- Designing for Regulatory Compliance (GDPR, SOX, etc.)
- Architecting Disaster Recovery for AI Components
- Load Testing AI-Integrated CPQ Workflows
- Establishing Performance Baselines and SLAs
- Documenting Architecture for IT and Security Teams
Module 11: Real-World Implementation Projects - Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data
Module 12: Certification, Career Advancement & Next Steps - Preparing for the Final Assessment
- Reviewing Key Concepts and Implementation Patterns
- Completing the Certification Project Submission
- Receiving Your Certificate of Completion from The Art of Service
- Adding Your Credential to LinkedIn and Resumes
- Networking with Other Certified CPQ Professionals
- Accessing Post-Course Implementation Templates
- Joining the Private Alumni Community
- Receiving Job Board and Opportunity Alerts
- Upgrading to Advanced Certification Paths
- Staying Updated with New AI and CPQ Features
- Submitting a Use Case for Publication
- Mentoring New Learners in the Community
- Invitations to Exclusive Industry Roundtables
- Planning Your Next Career Move with CPQ Expertise
- Designing AI-Powered Sales Playbooks
- Delivering Contextual Guidance During Quote Creation
- Embedding Best Practices into CPQ User Interfaces
- Using AI to Recommend Next Steps for Sales Reps
- Personalising Playbooks by Industry and Deal Size
- Integrating Playbook Suggestions with Chatter
- Tracking Playbook Usage and Effectiveness
- Automating Playbook Updates Based on Win/Loss Data
- Creating Role-Based Playbook Dashboards
- Reducing Ramp Time for New Hires with AI Coaching
- Linking Playbook Engagement to Performance Metrics
- Measuring Impact of Playbook Adoption on Win Rates
- Building Feedback Loops from Reps into Playbook Design
- Exporting Playbook Templates for Training Sessions
- Aligning Playbooks with Account-Based Selling Strategies
Module 8: CPQ Analytics, Reporting & Executive Insights - Building AI-Enhanced CPQ Dashboards
- Visualising Quote Conversion Rates by Segment
- Analysing Discount Trends with Predictive Baselines
- Identifying Top-Performing Product Combinations
- Monitoring Configuration Error Rates Over Time
- Creating Bottleneck Reports for Approval Delays
- Using AI to Detect Anomalies in Quote Data
- Generating Automatic Weekly CPQ Health Reports
- Exporting Reports for Financial and Legal Review
- Sharing Dashboards with Cross-Functional Teams
- Integrating CPQ Metrics with Salesforce Sales Cloud
- Setting Up Real-Time Alerts for Critical Metrics
- Building Executive Summary Reports for Leadership
- Aligning CPQ KPIs with Corporate Objectives
- Documenting Reporting Logic for Audit Readiness
Module 9: Change Management & Stakeholder Adoption - Developing a CPQ AI Rollout Roadmap
- Identifying Key Stakeholders and Champions
- Creating Tailored Messaging for Different Roles
- Conducting Impact Assessments for Process Changes
- Managing Resistance from Sales Teams
- Running Pilot Programs with Controlled Rollouts
- Gathering Feedback and Iterating on Design
- Training End Users with Role-Based Guides
- Documenting New Processes and SOPs
- Establishing Governance for Ongoing CPQ Management
- Setting Up a CPQ Centre of Excellence
- Managing Vendor and Partner Communication
- Aligning CPQ Changes with Sales Compensation
- Measuring User Adoption Metrics
- Scaling Success Across Business Units
Module 10: Advanced AI Optimisations & Scalability - Implementing Multi-Model AI Strategies in CPQ
- Using AI to Optimise CPQ for Global Pricing Compliance
- Scaling CPQ AI for High-Volume Transaction Environments
- Handling Large Product Catalogues with AI Categorisation
- Accelerating Quote Performance with Caching Strategies
- Reducing API Load with Bulk AI Inference Jobs
- Optimising AI Model Latency for Real-Time Use
- Integrating with Salesforce Data Cloud for 360-Degree Insights
- Building AI-Powered CPQ for Subscription and Usage Models
- Supporting Multi-Currency and Multi-Language Quotes
- Designing for Regulatory Compliance (GDPR, SOX, etc.)
- Architecting Disaster Recovery for AI Components
- Load Testing AI-Integrated CPQ Workflows
- Establishing Performance Baselines and SLAs
- Documenting Architecture for IT and Security Teams
Module 11: Real-World Implementation Projects - Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data
Module 12: Certification, Career Advancement & Next Steps - Preparing for the Final Assessment
- Reviewing Key Concepts and Implementation Patterns
- Completing the Certification Project Submission
- Receiving Your Certificate of Completion from The Art of Service
- Adding Your Credential to LinkedIn and Resumes
- Networking with Other Certified CPQ Professionals
- Accessing Post-Course Implementation Templates
- Joining the Private Alumni Community
- Receiving Job Board and Opportunity Alerts
- Upgrading to Advanced Certification Paths
- Staying Updated with New AI and CPQ Features
- Submitting a Use Case for Publication
- Mentoring New Learners in the Community
- Invitations to Exclusive Industry Roundtables
- Planning Your Next Career Move with CPQ Expertise
- Developing a CPQ AI Rollout Roadmap
- Identifying Key Stakeholders and Champions
- Creating Tailored Messaging for Different Roles
- Conducting Impact Assessments for Process Changes
- Managing Resistance from Sales Teams
- Running Pilot Programs with Controlled Rollouts
- Gathering Feedback and Iterating on Design
- Training End Users with Role-Based Guides
- Documenting New Processes and SOPs
- Establishing Governance for Ongoing CPQ Management
- Setting Up a CPQ Centre of Excellence
- Managing Vendor and Partner Communication
- Aligning CPQ Changes with Sales Compensation
- Measuring User Adoption Metrics
- Scaling Success Across Business Units
Module 10: Advanced AI Optimisations & Scalability - Implementing Multi-Model AI Strategies in CPQ
- Using AI to Optimise CPQ for Global Pricing Compliance
- Scaling CPQ AI for High-Volume Transaction Environments
- Handling Large Product Catalogues with AI Categorisation
- Accelerating Quote Performance with Caching Strategies
- Reducing API Load with Bulk AI Inference Jobs
- Optimising AI Model Latency for Real-Time Use
- Integrating with Salesforce Data Cloud for 360-Degree Insights
- Building AI-Powered CPQ for Subscription and Usage Models
- Supporting Multi-Currency and Multi-Language Quotes
- Designing for Regulatory Compliance (GDPR, SOX, etc.)
- Architecting Disaster Recovery for AI Components
- Load Testing AI-Integrated CPQ Workflows
- Establishing Performance Baselines and SLAs
- Documenting Architecture for IT and Security Teams
Module 11: Real-World Implementation Projects - Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data
Module 12: Certification, Career Advancement & Next Steps - Preparing for the Final Assessment
- Reviewing Key Concepts and Implementation Patterns
- Completing the Certification Project Submission
- Receiving Your Certificate of Completion from The Art of Service
- Adding Your Credential to LinkedIn and Resumes
- Networking with Other Certified CPQ Professionals
- Accessing Post-Course Implementation Templates
- Joining the Private Alumni Community
- Receiving Job Board and Opportunity Alerts
- Upgrading to Advanced Certification Paths
- Staying Updated with New AI and CPQ Features
- Submitting a Use Case for Publication
- Mentoring New Learners in the Community
- Invitations to Exclusive Industry Roundtables
- Planning Your Next Career Move with CPQ Expertise
- Project 1: Build an AI-Driven Discount Approval Engine
- Project 2: Implement Predictive Product Recommendations
- Project 3: Create a Dynamic Pricing Model by Customer Tier
- Project 4: Automate High-Risk Quote Flagging and Routing
- Project 5: Generate AI-Optimised Renewal Quotes
- Project 6: Design a Guided Selling Flow with AI Logic
- Project 7: Integrate CPQ Data into Executive Forecasting
- Project 8: Build a CPQ Health Dashboard with Anomaly Detection
- Project 9: Develop a Sales Playbook with Real-Time Suggestions
- Project 10: Execute a Full CPQ AI Pilot with Metrics Tracking
- Defining Success Criteria for Each Project
- Testing and Validating Implementation Logic
- Documenting Assumptions and Dependencies
- Presenting Results to Stakeholders
- Iterating Based on Feedback and Performance Data