Role-Based Programme
RB1274

AI for Customer Experience & Voice of Customer

Journey Intelligence, Sentiment Analysis & Experience Improvement

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for customer experience analysis, Voice of Customer programmes, journey mapping, and insight generation.
  • Apply AI to analyse surveys, reviews, complaints, service interactions, interviews, and other customer feedback sources.
  • Use AI to identify customer needs, sentiment patterns, experience gaps, friction points, and improvement opportunities.
  • Strengthen CX decision-making through structured journey analysis, root-cause investigation, prioritisation, and experience-performance reporting.
  • Apply responsible AI practices related to customer privacy, bias, sentiment interpretation, source quality, and human validation.

Tools covered

Generative AI AssistantsAI Search & ResearchCustomer Feedback AnalysisSentiment Analysis ConceptsJourney MappingSurvey AnalysisComplaint & Review AnalysisExperience AnalyticsCustomer SegmentationRoot-Cause AnalysisInsight GenerationExecutive Summarisation

Who should attend

  • Customer Experience Managers
  • Customer Experience Executives
  • Voice of Customer Managers
  • Voice of Customer Analysts
  • Customer Insights Professionals
  • Customer Success Managers
  • Customer Service Managers
  • Customer Journey Professionals
  • CX Analysts
  • Service Design Professionals
  • Customer Research Professionals
  • Quality & Service Excellence Professionals
  • Customer Retention Professionals
  • Customer Operations Professionals
  • Customer Experience Leaders

Prerequisites & Participant Readiness

  • Experience in customer experience, customer service, customer success, research, service quality, or customer insights
  • Familiarity with surveys, customer feedback, complaints, reviews, or journey mapping
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret qualitative and quantitative customer information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across customer feedback, journeys, sentiment, and experience analytics
  • Understanding how AI differs from survey, CRM, CX, and analytics platforms
  • Recognising hallucinations, over-generalisation, and limitations in customer interpretation
Practical activities
  • Mapping the Voice of Customer lifecycle to practical AI applications
  • Identifying high-value versus high-risk CX use cases
  • Comparing traditional and AI-assisted customer experience workflows

Scenarios

Voice of Customer to Experience Improvement Plan

Customer Feedback → Sentiment Analysis → Theme Identification → Journey Mapping → Pain Points → Root-Cause Analysis → Prioritisation → CX Improvement Plan

Participants use AI to analyse multi-channel customer feedback, identify recurring experience issues, map them to the customer journey, and develop a prioritised improvement plan.

Declining Customer Satisfaction to Executive CX Strategy

CSAT/NPS Data → Segment Analysis → Complaint Trends → Journey Friction → Root Causes → Experience Priorities → Action Roadmap → Executive Recommendation

Participants use AI to investigate a simulated decline in customer satisfaction, combine quantitative and qualitative evidence, and develop an executive-ready customer experience recovery strategy.

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