1. Course Format & Delivery Details Fully Self-Paced, On-Demand Learning — Start Anytime, Learn Anywhere
This course is designed for professionals like you who need flexibility without sacrificing depth, structure, or outcomes. From the moment you enroll, you gain immediate online access to the full suite of learning materials—no waiting, no schedules, no limitations. Study at your own pace, on your own time, from any device with internet access. Lifetime Access + Ongoing Updates — A Career-Long Investment
When you enroll in AI-Driven Sales Excellence, you're not just purchasing a course—you're making a long-term investment in your skills and professional trajectory. You receive lifetime access to all course content, including every future update released at no additional cost. As AI technology evolves and new sales strategies emerge, your learning evolves with it—automatically and seamlessly. Designed for Rapid Results — See Impact in Under 30 Days
Most learners complete the core curriculum in 12–18 hours and begin applying high-impact techniques within the first week. The content is structured to deliver practical value fast: you'll implement AI-driven tools, refine customer outreach, and optimize sales workflows from day one. Whether you apply 20 minutes a day or complete a module each weekend, the structured flow ensures measurable progress with every step. 24/7 Global, Mobile-Friendly Access — Learn on the Go
Access your course anywhere in the world, any time of day, from your desktop, tablet, or smartphone. Our responsive learning platform adapts perfectly to your device, so you can review strategies during commutes, update your sales playbook between meetings, or reinforce insights while traveling. The entire experience is optimized for mobile—no apps to download, no compatibility issues. Direct Instructor Support & Expert Guidance — You're Not Alone
Throughout your journey, you’ll have direct access to expert facilitators who specialise in AI, data analytics, and modern sales transformation. Whether you need clarification on a framework, want feedback on a strategy, or are troubleshooting an automation setup, qualified support is available via structured inquiry channels. This isn’t a passive learning experience—your success is actively supported. Certificate of Completion — A Globally Recognized Credential
Upon finishing the course, you will earn a Certificate of Completion issued by The Art of Service—a hallmark of excellence trusted by professionals in over 140 countries. This credential validates your mastery of AI-powered sales strategy, data fluency, automation integration, and customer intelligence. It’s shareable on LinkedIn, verifiable online, and designed to stand out to hiring managers, clients, and leadership teams. Transparent, Upfront Pricing — No Hidden Fees, Ever
The price you see is the price you pay—there are no hidden fees, surprise charges, or recurring subscription traps. Your one-time payment grants full, permanent access to the entire course, including all updates, tools, exercises, and certification. No upsells. No fine print. Just clear, honest value. Accepted Payment Methods
- Visa
- Mastercard
- PayPal
Zero-Risk Enrollment — Satisfied or Refunded
We stand behind the transformative power of this course with a strong satisfaction guarantee. If at any point you find the content doesn’t meet your expectations for clarity, practicality, or professional ROI, simply contact us for a full refund. There’s no risk in starting—only the opportunity to gain a decisive competitive edge. What to Expect After Enrollment
After registering, you’ll receive a confirmation email acknowledging your enrollment. Shortly afterward, you’ll receive a separate message with your secure access details and step-by-step login instructions. This process ensures your access is properly provisioned and your learning environment is fully prepared for a seamless start. “Will This Work for Me?” — Confidence You Can Rely On
You might be asking: “I’m not technical—will AI strategies really work for me?” Or perhaps: “I’ve tried other courses, and they didn’t translate to real results.” This works even if: you've never used AI before, your company hasn’t adopted automation, you’re not in tech sales, or you’re unsure where to start with data. The course is built on proven, role-specific frameworks that work across industries and seniority levels. Real-World Impact by Role: - Sales Representatives use AI to identify high-intent leads, personalise outreach at scale, and increase conversion rates by 40%+.
- Sales Managers deploy predictive analytics to forecast performance, detect pipeline risks early, and coach teams with data-backed insights.
- Entrepreneurs & Founders leverage automation to run lean, scalable sales operations without hiring early.
- Customer Success Teams apply AI-driven insights to reduce churn and uncover upsell opportunities in real time.
What professionals say: “I applied the lead-scoring automation in Week 2—and closed three opportunities I would have otherwise missed. This paid for itself in the first quarter.” – Nadia R., Enterprise Account Executive, Germany
“The CRM-AI integration guide transformed how our team prioritises deals. My forecast accuracy jumped from 68% to 92% in two cycles.” – Carlos M., Sales Director, Mexico
Your Safety, Clarity & Success Are Built In
We remove every barrier between you and success: no time pressure, no technical jargon, no obsolete theories. You’ll follow a crystal-clear path from confusion to confidence. With lifetime access, ongoing updates, certification, expert support, and a full refund guarantee, the only risk is not taking action—and the reward is transformative sales mastery rooted in AI, data, and human insight.
2. Extensive & Detailed Course Curriculum
Module 1: Foundations of AI in Modern Sales - The evolution of sales: From intuition to intelligence
- What AI really means for sales professionals
- Understanding machine learning vs. automation vs. predictive analytics
- Debunking 7 common myths about AI in sales
- The role of data in shaping customer conversations
- Why traditional sales methods are no longer enough
- Case study: How a mid-sized firm doubled its conversion rate using AI
- AI adoption curves across industries
- How AI enhances—not replaces—human relationships
- Setting your personal baseline: Where you stand today
Module 2: Building a Data-Driven Sales Mindset - Shifting from activity-based to outcome-based metrics
- Identifying high-value vs. vanity metrics
- Creating your personal KPI dashboard
- How to extract insights from limited datasets
- Understanding signal, noise, and bias in sales data
- Principles of statistical thinking for non-analysts
- Using data storytelling to influence stakeholders
- The psychology of data interpretation
- Establishing a culture of evidence-based decisions
- Building confidence when working with numbers
Module 3: AI-Powered Customer Intelligence Frameworks - Defining customer-centric intelligence
- The 5 layers of customer insight: Behavioural, emotional, contextual, intent, predictive
- Mapping customer journeys using AI signals
- Identifying micro-moments that drive buying decisions
- Using sentiment analysis to detect emotional cues
- Leveraging digital body language in outreach
- Scoring customer engagement intensity
- Real-time intent detection from online activity
- Inferring needs from indirect signals (downloads, time on page, video views)
- Linking behavioural patterns to sales stages
Module 4: Lead Scoring & Predictive Prioritisation Models - Why 80% of leads go cold—and how to fix it
- Manual vs. algorithmic lead scoring
- Designing your own lead-scoring rubric
- Integrating firmographic, behavioural, and technographic data
- Weighting signals by predictive power
- Setting dynamic thresholds for follow-up intensity
- Automating triage rules in your CRM
- Calibrating models to reduce false positives
- Handling low-data scenarios with proxy indicators
- Validating model accuracy over time
Module 5: Intelligent Outreach & Personalisation at Scale - The anatomy of high-conversion outreach
- Segmenting prospects using AI clusters
- Dynamic content personalisation principles
- Auto-generating outreach variations based on profile data
- Using natural language generation (NLG) for email drafting
- Optimising subject lines using A/B testing algorithms
- Timing outreach based on timezone, role, and behaviour
- Multi-channel sequencing with AI coordination
- Automated follow-up cadences with conditional logic
- Measuring personalisation ROI: opens, replies, meetings
Module 6: AI-Enhanced Email, Calling & Messaging - Smart email templates that adapt to recipient profiles
- Real-time email suggestions during drafting
- Outbound email deliverability optimisation
- AI-driven call scripting for discovery conversations
- Speech pattern analysis for rapport building
- Live call coaching cues and tone monitoring
- Post-call summarisation and action item extraction
- AI-powered voicemail transcription and sentiment tagging
- Chatbot handoff protocols for sales teams
- Building responsive messaging workflows across platforms
Module 7: CRM Integration & Data Orchestration - Choosing the right CRM for AI readiness
- Mapping your data ecosystem: CRMs, MAPs, APIs, data lakes
- Designing clean data input standards
- Automated data enrichment techniques
- Removing duplicates and inconsistencies
- Setting up trigger-based data updates
- Building centralised customer profiles
- Syncing external behavioural data into your CRM
- Creating audit trails for data integrity
- Ensuring compliance with data protection standards
Module 8: Sales Forecasting with Predictive Analytics - Limitations of gut-based forecasting
- Transitioning from static to dynamic forecasting
- Key inputs for accurate AI forecasting models
- Handling incomplete pipeline data
- Probability scoring per deal stage
- Adjusting for stage duration and historical conversion
- Accounting for human bias in deal progression
- Generating confidence intervals around forecasts
- Visualising forecast trends and anomalies
- Communicating probabilistic forecasts to leadership
Module 9: AI Tools for Sales Managers & Leaders - Identifying coaching opportunities with AI insights
- Analysing team performance by conversion bottlenecks
- Automating weekly performance summaries
- Flagging at-risk deals for intervention
- Historical pattern recognition for strategy refinement
- Benchmarking reps against top performers
- Reducing managerial admin by 60% through automation
- Building data-rich 1:1 meeting agendas
- Identifying skill gaps across the team
- Simulating the impact of strategy changes
Module 10: AI Automation Workflows for Reps - Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
Module 1: Foundations of AI in Modern Sales - The evolution of sales: From intuition to intelligence
- What AI really means for sales professionals
- Understanding machine learning vs. automation vs. predictive analytics
- Debunking 7 common myths about AI in sales
- The role of data in shaping customer conversations
- Why traditional sales methods are no longer enough
- Case study: How a mid-sized firm doubled its conversion rate using AI
- AI adoption curves across industries
- How AI enhances—not replaces—human relationships
- Setting your personal baseline: Where you stand today
Module 2: Building a Data-Driven Sales Mindset - Shifting from activity-based to outcome-based metrics
- Identifying high-value vs. vanity metrics
- Creating your personal KPI dashboard
- How to extract insights from limited datasets
- Understanding signal, noise, and bias in sales data
- Principles of statistical thinking for non-analysts
- Using data storytelling to influence stakeholders
- The psychology of data interpretation
- Establishing a culture of evidence-based decisions
- Building confidence when working with numbers
Module 3: AI-Powered Customer Intelligence Frameworks - Defining customer-centric intelligence
- The 5 layers of customer insight: Behavioural, emotional, contextual, intent, predictive
- Mapping customer journeys using AI signals
- Identifying micro-moments that drive buying decisions
- Using sentiment analysis to detect emotional cues
- Leveraging digital body language in outreach
- Scoring customer engagement intensity
- Real-time intent detection from online activity
- Inferring needs from indirect signals (downloads, time on page, video views)
- Linking behavioural patterns to sales stages
Module 4: Lead Scoring & Predictive Prioritisation Models - Why 80% of leads go cold—and how to fix it
- Manual vs. algorithmic lead scoring
- Designing your own lead-scoring rubric
- Integrating firmographic, behavioural, and technographic data
- Weighting signals by predictive power
- Setting dynamic thresholds for follow-up intensity
- Automating triage rules in your CRM
- Calibrating models to reduce false positives
- Handling low-data scenarios with proxy indicators
- Validating model accuracy over time
Module 5: Intelligent Outreach & Personalisation at Scale - The anatomy of high-conversion outreach
- Segmenting prospects using AI clusters
- Dynamic content personalisation principles
- Auto-generating outreach variations based on profile data
- Using natural language generation (NLG) for email drafting
- Optimising subject lines using A/B testing algorithms
- Timing outreach based on timezone, role, and behaviour
- Multi-channel sequencing with AI coordination
- Automated follow-up cadences with conditional logic
- Measuring personalisation ROI: opens, replies, meetings
Module 6: AI-Enhanced Email, Calling & Messaging - Smart email templates that adapt to recipient profiles
- Real-time email suggestions during drafting
- Outbound email deliverability optimisation
- AI-driven call scripting for discovery conversations
- Speech pattern analysis for rapport building
- Live call coaching cues and tone monitoring
- Post-call summarisation and action item extraction
- AI-powered voicemail transcription and sentiment tagging
- Chatbot handoff protocols for sales teams
- Building responsive messaging workflows across platforms
Module 7: CRM Integration & Data Orchestration - Choosing the right CRM for AI readiness
- Mapping your data ecosystem: CRMs, MAPs, APIs, data lakes
- Designing clean data input standards
- Automated data enrichment techniques
- Removing duplicates and inconsistencies
- Setting up trigger-based data updates
- Building centralised customer profiles
- Syncing external behavioural data into your CRM
- Creating audit trails for data integrity
- Ensuring compliance with data protection standards
Module 8: Sales Forecasting with Predictive Analytics - Limitations of gut-based forecasting
- Transitioning from static to dynamic forecasting
- Key inputs for accurate AI forecasting models
- Handling incomplete pipeline data
- Probability scoring per deal stage
- Adjusting for stage duration and historical conversion
- Accounting for human bias in deal progression
- Generating confidence intervals around forecasts
- Visualising forecast trends and anomalies
- Communicating probabilistic forecasts to leadership
Module 9: AI Tools for Sales Managers & Leaders - Identifying coaching opportunities with AI insights
- Analysing team performance by conversion bottlenecks
- Automating weekly performance summaries
- Flagging at-risk deals for intervention
- Historical pattern recognition for strategy refinement
- Benchmarking reps against top performers
- Reducing managerial admin by 60% through automation
- Building data-rich 1:1 meeting agendas
- Identifying skill gaps across the team
- Simulating the impact of strategy changes
Module 10: AI Automation Workflows for Reps - Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Shifting from activity-based to outcome-based metrics
- Identifying high-value vs. vanity metrics
- Creating your personal KPI dashboard
- How to extract insights from limited datasets
- Understanding signal, noise, and bias in sales data
- Principles of statistical thinking for non-analysts
- Using data storytelling to influence stakeholders
- The psychology of data interpretation
- Establishing a culture of evidence-based decisions
- Building confidence when working with numbers
Module 3: AI-Powered Customer Intelligence Frameworks - Defining customer-centric intelligence
- The 5 layers of customer insight: Behavioural, emotional, contextual, intent, predictive
- Mapping customer journeys using AI signals
- Identifying micro-moments that drive buying decisions
- Using sentiment analysis to detect emotional cues
- Leveraging digital body language in outreach
- Scoring customer engagement intensity
- Real-time intent detection from online activity
- Inferring needs from indirect signals (downloads, time on page, video views)
- Linking behavioural patterns to sales stages
Module 4: Lead Scoring & Predictive Prioritisation Models - Why 80% of leads go cold—and how to fix it
- Manual vs. algorithmic lead scoring
- Designing your own lead-scoring rubric
- Integrating firmographic, behavioural, and technographic data
- Weighting signals by predictive power
- Setting dynamic thresholds for follow-up intensity
- Automating triage rules in your CRM
- Calibrating models to reduce false positives
- Handling low-data scenarios with proxy indicators
- Validating model accuracy over time
Module 5: Intelligent Outreach & Personalisation at Scale - The anatomy of high-conversion outreach
- Segmenting prospects using AI clusters
- Dynamic content personalisation principles
- Auto-generating outreach variations based on profile data
- Using natural language generation (NLG) for email drafting
- Optimising subject lines using A/B testing algorithms
- Timing outreach based on timezone, role, and behaviour
- Multi-channel sequencing with AI coordination
- Automated follow-up cadences with conditional logic
- Measuring personalisation ROI: opens, replies, meetings
Module 6: AI-Enhanced Email, Calling & Messaging - Smart email templates that adapt to recipient profiles
- Real-time email suggestions during drafting
- Outbound email deliverability optimisation
- AI-driven call scripting for discovery conversations
- Speech pattern analysis for rapport building
- Live call coaching cues and tone monitoring
- Post-call summarisation and action item extraction
- AI-powered voicemail transcription and sentiment tagging
- Chatbot handoff protocols for sales teams
- Building responsive messaging workflows across platforms
Module 7: CRM Integration & Data Orchestration - Choosing the right CRM for AI readiness
- Mapping your data ecosystem: CRMs, MAPs, APIs, data lakes
- Designing clean data input standards
- Automated data enrichment techniques
- Removing duplicates and inconsistencies
- Setting up trigger-based data updates
- Building centralised customer profiles
- Syncing external behavioural data into your CRM
- Creating audit trails for data integrity
- Ensuring compliance with data protection standards
Module 8: Sales Forecasting with Predictive Analytics - Limitations of gut-based forecasting
- Transitioning from static to dynamic forecasting
- Key inputs for accurate AI forecasting models
- Handling incomplete pipeline data
- Probability scoring per deal stage
- Adjusting for stage duration and historical conversion
- Accounting for human bias in deal progression
- Generating confidence intervals around forecasts
- Visualising forecast trends and anomalies
- Communicating probabilistic forecasts to leadership
Module 9: AI Tools for Sales Managers & Leaders - Identifying coaching opportunities with AI insights
- Analysing team performance by conversion bottlenecks
- Automating weekly performance summaries
- Flagging at-risk deals for intervention
- Historical pattern recognition for strategy refinement
- Benchmarking reps against top performers
- Reducing managerial admin by 60% through automation
- Building data-rich 1:1 meeting agendas
- Identifying skill gaps across the team
- Simulating the impact of strategy changes
Module 10: AI Automation Workflows for Reps - Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Why 80% of leads go cold—and how to fix it
- Manual vs. algorithmic lead scoring
- Designing your own lead-scoring rubric
- Integrating firmographic, behavioural, and technographic data
- Weighting signals by predictive power
- Setting dynamic thresholds for follow-up intensity
- Automating triage rules in your CRM
- Calibrating models to reduce false positives
- Handling low-data scenarios with proxy indicators
- Validating model accuracy over time
Module 5: Intelligent Outreach & Personalisation at Scale - The anatomy of high-conversion outreach
- Segmenting prospects using AI clusters
- Dynamic content personalisation principles
- Auto-generating outreach variations based on profile data
- Using natural language generation (NLG) for email drafting
- Optimising subject lines using A/B testing algorithms
- Timing outreach based on timezone, role, and behaviour
- Multi-channel sequencing with AI coordination
- Automated follow-up cadences with conditional logic
- Measuring personalisation ROI: opens, replies, meetings
Module 6: AI-Enhanced Email, Calling & Messaging - Smart email templates that adapt to recipient profiles
- Real-time email suggestions during drafting
- Outbound email deliverability optimisation
- AI-driven call scripting for discovery conversations
- Speech pattern analysis for rapport building
- Live call coaching cues and tone monitoring
- Post-call summarisation and action item extraction
- AI-powered voicemail transcription and sentiment tagging
- Chatbot handoff protocols for sales teams
- Building responsive messaging workflows across platforms
Module 7: CRM Integration & Data Orchestration - Choosing the right CRM for AI readiness
- Mapping your data ecosystem: CRMs, MAPs, APIs, data lakes
- Designing clean data input standards
- Automated data enrichment techniques
- Removing duplicates and inconsistencies
- Setting up trigger-based data updates
- Building centralised customer profiles
- Syncing external behavioural data into your CRM
- Creating audit trails for data integrity
- Ensuring compliance with data protection standards
Module 8: Sales Forecasting with Predictive Analytics - Limitations of gut-based forecasting
- Transitioning from static to dynamic forecasting
- Key inputs for accurate AI forecasting models
- Handling incomplete pipeline data
- Probability scoring per deal stage
- Adjusting for stage duration and historical conversion
- Accounting for human bias in deal progression
- Generating confidence intervals around forecasts
- Visualising forecast trends and anomalies
- Communicating probabilistic forecasts to leadership
Module 9: AI Tools for Sales Managers & Leaders - Identifying coaching opportunities with AI insights
- Analysing team performance by conversion bottlenecks
- Automating weekly performance summaries
- Flagging at-risk deals for intervention
- Historical pattern recognition for strategy refinement
- Benchmarking reps against top performers
- Reducing managerial admin by 60% through automation
- Building data-rich 1:1 meeting agendas
- Identifying skill gaps across the team
- Simulating the impact of strategy changes
Module 10: AI Automation Workflows for Reps - Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Smart email templates that adapt to recipient profiles
- Real-time email suggestions during drafting
- Outbound email deliverability optimisation
- AI-driven call scripting for discovery conversations
- Speech pattern analysis for rapport building
- Live call coaching cues and tone monitoring
- Post-call summarisation and action item extraction
- AI-powered voicemail transcription and sentiment tagging
- Chatbot handoff protocols for sales teams
- Building responsive messaging workflows across platforms
Module 7: CRM Integration & Data Orchestration - Choosing the right CRM for AI readiness
- Mapping your data ecosystem: CRMs, MAPs, APIs, data lakes
- Designing clean data input standards
- Automated data enrichment techniques
- Removing duplicates and inconsistencies
- Setting up trigger-based data updates
- Building centralised customer profiles
- Syncing external behavioural data into your CRM
- Creating audit trails for data integrity
- Ensuring compliance with data protection standards
Module 8: Sales Forecasting with Predictive Analytics - Limitations of gut-based forecasting
- Transitioning from static to dynamic forecasting
- Key inputs for accurate AI forecasting models
- Handling incomplete pipeline data
- Probability scoring per deal stage
- Adjusting for stage duration and historical conversion
- Accounting for human bias in deal progression
- Generating confidence intervals around forecasts
- Visualising forecast trends and anomalies
- Communicating probabilistic forecasts to leadership
Module 9: AI Tools for Sales Managers & Leaders - Identifying coaching opportunities with AI insights
- Analysing team performance by conversion bottlenecks
- Automating weekly performance summaries
- Flagging at-risk deals for intervention
- Historical pattern recognition for strategy refinement
- Benchmarking reps against top performers
- Reducing managerial admin by 60% through automation
- Building data-rich 1:1 meeting agendas
- Identifying skill gaps across the team
- Simulating the impact of strategy changes
Module 10: AI Automation Workflows for Reps - Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Limitations of gut-based forecasting
- Transitioning from static to dynamic forecasting
- Key inputs for accurate AI forecasting models
- Handling incomplete pipeline data
- Probability scoring per deal stage
- Adjusting for stage duration and historical conversion
- Accounting for human bias in deal progression
- Generating confidence intervals around forecasts
- Visualising forecast trends and anomalies
- Communicating probabilistic forecasts to leadership
Module 9: AI Tools for Sales Managers & Leaders - Identifying coaching opportunities with AI insights
- Analysing team performance by conversion bottlenecks
- Automating weekly performance summaries
- Flagging at-risk deals for intervention
- Historical pattern recognition for strategy refinement
- Benchmarking reps against top performers
- Reducing managerial admin by 60% through automation
- Building data-rich 1:1 meeting agendas
- Identifying skill gaps across the team
- Simulating the impact of strategy changes
Module 10: AI Automation Workflows for Reps - Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Designing no-code automation sequences
- Automating lead assignment and routing
- Triggering tasks based on customer actions
- Auto-populating activity logs and deal updates
- Integrating calendar and meeting data
- Automated follow-up with conditional branching
- Using Zapier-like logic without technical skills
- Building exception-handling rules
- Testing and validating automation logic
- Documenting workflows for team alignment
Module 11: Conversational Intelligence & Voice Analytics - How voice AI captures insights from sales calls
- Transcribing calls with high accuracy
- Extracting key topics, objections, and next steps
- Tone analysis: detecting urgency, hesitation, confidence
- Metric tracking: talk-to-listen ratio, filler words, silence
- Identifying coaching moments from patterns
- Creating personal playbooks from call data
- Comparing performance across conversations
- Compliance and consent protocols
- Auto-labelling calls by theme and outcome
Module 12: Competitive Intelligence Using AI - Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Monitoring competitor strengths and weaknesses
- Analysing win/loss patterns across deals
- Extracting insights from public pricing and messaging
- Tracking competitor news, funding, and hires
- Sentiment mapping of competitor brands
- Inferring go-to-market shifts using digital footprints
- Generating competitive battlecards with AI assistance
- Automating RFP comparison templates
- Monitoring social media and review sites
- Creating early-warning systems for market changes
Module 13: AI for Negotiation & Closing Strategies - Using historical data to predict negotiation timelines
- Identifying negotiation styles from language cues
- Offer optimisation using pricing intelligence
- Timing discount strategies based on buyer signals
- Simulating concession scenarios
- Anticipating objections with predictive modelling
- Auto-generating next-best-offer suggestions
- Tracking decision-maker sentiment during negotiations
- Documenting agreement terms with AI summaries
- Ensuring compliance in closing processes
Module 14: Customer Retention & Expansion with AI - Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Reducing churn with early-warning signals
- Scoring customer health across 12 dimensions
- Identifying upsell and cross-sell opportunities
- Automating renewal outreach sequences
- Tracking product usage patterns
- Using support ticket sentiment to flag risks
- Scheduling check-ins based on engagement dips
- Generating renewal playbooks for teams
- Triggering expansion conversations post-implementation
- Calculating lifetime value increase from AI retention
Module 15: Ethical AI & Responsible Sales Practices - Understanding bias in AI models
- Avoiding discriminatory targeting or exclusion
- Transparency in automated decision-making
- Respecting privacy and consent in data use
- Preventing over-automation of human interactions
- Maintaining authenticity in AI-assisted outreach
- Building trust while leveraging intelligence
- Legal boundaries in AI deployment
- Disclosure best practices
- Creating internal AI usage policies
Module 16: Implementing AI: A 30-Day Rollout Plan - Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Conducting a sales process audit
- Identifying high-impact, low-effort AI use cases
- Prioritising tools based on ROI potential
- Setting up your first AI integration
- Training your team on new workflows
- Running a pilot with measurable KPIs
- Gathering feedback and iterating
- Scaling successful pilots across teams
- Tracking time saved and revenue impact
- Creating a sustainable adoption roadmap
Module 17: Advanced AI Sales Architecture - Understanding data pipelines and model training
- How supervised learning applies to sales
- Using clustering to discover customer segments
- Regression models for revenue forecasting
- Decision trees for next-best-action logic
- Natural language processing for email analysis
- Ensemble models for higher accuracy
- Feature engineering for custom scoring
- Model explainability and trust building
- Monitoring model drift and retraining cycles
Module 18: Hands-On Projects & Real-World Application - Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Project 1: Build your custom lead-scoring model
- Project 2: Design an AI-powered outreach campaign
- Project 3: Create a predictive sales forecast for next quarter
- Project 4: Automate a multi-step follow-up sequence
- Project 5: Analyse real call transcripts using voice AI principles
- Project 6: Audit your CRM for AI readiness
- Project 7: Develop a customer health scoring system
- Project 8: Run a competitive intelligence report
- Project 9: Draft an AI adoption proposal for your team
- Project 10: Create your personal AI sales mastery portfolio
Module 19: Integration with Sales Tools & Platforms - Connecting AI workflows with Salesforce
- Syncing data with HubSpot and Marketo
- Integrating with LinkedIn Sales Navigator
- Using ZoomInfo for enriched prospecting
- Auto-updating calendars via Google or Outlook
- Embedding insights into Slack or Teams
- Using Zapier or Make for custom integrations
- Setting up API connections securely
- Monitoring integration health and delays
- Documenting system dependencies
Module 20: Certification & Next Steps - Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery
- Reviewing key concepts and mastery checkpoints
- Preparing for your Certificate of Completion
- Submitting your final project for evaluation
- Receiving official recognition from The Art of Service
- Sharing your credential on LinkedIn and professional networks
- Accessing downloadable templates and toolkits
- Joining the AI Sales Excellence alumni network
- Receiving curated updates on emerging AI tools
- Setting your 3-, 6-, and 12-month AI adoption goals
- Creating a personal development roadmap for ongoing mastery