Aim

This course shows how AI can transform the customer experience (CX) across the full journey—discover, buy, use, and support. Participants will learn how to apply AI for personalization, conversational support, sentiment analysis, customer insights, and proactive service—while maintaining trust, privacy, and brand consistency.

Who This Course Is For

• CX leaders, customer success managers, and support teams
• Marketing and growth professionals focused on engagement and retention
• Product managers improving onboarding and in-app experiences
• Founders and operations teams scaling customer support efficiently
• Data and AI professionals working on customer-facing solutions

Prerequisites

• No coding required (optional demos use simple tools/templates)
• Basic familiarity with customer journeys, CRM/support workflows is helpful
• Curiosity to improve customer satisfaction through data-driven decisions

What You’ll Learn

• Mapping the customer journey and spotting AI opportunities
• Personalization strategies: recommendations, next-best action, and tailored messaging
• Conversational AI: chatbots, voicebots, and GenAI assistants for support and sales
• Sentiment and intent detection from chats, calls, surveys, and reviews
• Customer segmentation and churn prediction basics
• Proactive support: ticket triage, auto-routing, and resolution suggestions
• Omnichannel CX: consistent experience across email, chat, social, and phone
• Measuring CX impact: CSAT, NPS, CES, FRT, AHT, and retention metrics
• Responsible AI: privacy, bias, transparency, and “human-in-the-loop” design

Program Structure (Humanized)

This program is designed like a CX improvement sprint. We start by understanding your customers and pain points, then apply AI methods to improve engagement, speed, and satisfaction. You’ll leave with a ready-to-implement CX roadmap and templates your team can reuse.

Module 1: The CX Mindset + Where AI Fits

• CX fundamentals: moments that matter, trust, and consistency
• Where AI creates real value vs where it creates friction
• Designing AI experiences that still feel “human”

Module 2: Customer Journey Mapping & Opportunity Discovery

• Journey mapping: acquisition → onboarding → usage → support → renewal
• Identifying high-friction points (drop-offs, repeat contacts, escalations)
• Use-case scoring: impact vs feasibility vs risk

Module 3: Personalization That Doesn’t Feel Creepy

• Segments, personas, and dynamic personalization
• Recommendation engines: products, content, and help articles
• Next-best action and lifecycle messaging (email/in-app/CRM)

Module 4: Conversational AI for Support & Engagement

• Chatbots vs GenAI assistants: choosing the right approach
• Conversation design: tone, guardrails, escalation to humans
• Knowledge base + retrieval: giving accurate, consistent answers

Module 5: Voice of Customer Analytics (VoC)

• Mining insights from surveys, reviews, tickets, chats, and calls
• Sentiment + intent + topic detection (what customers really want)
• Building feedback loops for continuous improvement

Module 6: Smarter Support Operations with AI

• Ticket triage: categorization, routing, priority, and SLA risk
• Agent assist: response suggestions, summaries, and resolution steps
• Reducing repeat contacts: automation + better self-service

Module 7: Churn, Retention & Proactive Customer Success

• Churn signals: usage patterns, complaints, and engagement drops
• Proactive interventions: save plays, onboarding nudges, renewal support
• Customer health score design (practical and explainable)

Module 8: Governance, Privacy & Measuring ROI

• Privacy by design: permissions, consent, and minimal data use
• Guardrails: hallucination risk, policy compliance, and brand safety
• CX KPI dashboards: CSAT/NPS/CES + operational metrics (FRT, AHT)

Hands-On Deliverables (Portfolio + Business Ready)

• CX Journey Map: pain points + AI opportunities across touchpoints
• Use-Case Prioritization Sheet: impact/effort/risk scoring
• Conversational AI Blueprint: sample flows, escalation rules, guardrails
• VoC Insight Summary: top customer issues + recommended fixes
• 90-Day CX AI Roadmap: quick wins + scalable improvements

Tools & Platforms (Conceptual + Demonstration)

• CRM & support workflow concepts (tickets, SLAs, routing, knowledge bases)
• GenAI assistant patterns (retrieval + guardrails + human-in-loop)
• Analytics basics for CX dashboards and KPI measurement

Outcomes

• Design AI-powered CX improvements without compromising trust
• Implement personalization and conversational AI thoughtfully
• Use sentiment/VoC insights to improve products and support operations
• Reduce support load while improving CSAT and resolution quality
• Build a practical roadmap to scale AI across CX teams