Role-Based Programme
RB1275

AI for Customer Experience & Voice of Customer

Advanced Experience Intelligence, Journey Insights & Customer-Centric Transformation

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across Customer Experience strategy, Voice-of-Customer programmes, journey analysis, feedback intelligence, and experience improvement.
  • Use AI-assisted analysis to extract actionable insights from surveys, complaints, reviews, conversations, support interactions, and behavioural data.
  • Apply AI to customer journey mapping, sentiment analysis, experience measurement, root-cause analysis, customer segmentation, and improvement prioritisation.
  • Translate customer evidence into measurable experience improvements, service-design actions, product recommendations, and executive decision support.
  • Build responsible AI-enabled Customer Experience and Voice-of-Customer workflows with strong privacy, governance, validation, fairness, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchVoice-of-Customer AnalyticsSentiment AnalysisCustomer Journey AnalysisExperience AnalyticsSurvey AnalysisFeedback MiningCustomer SegmentationRoot Cause AnalysisExperience MeasurementText AnalyticsWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Customer Experience Managers
  • Voice-of-Customer Managers
  • Customer Experience Analysts
  • Customer Insights Professionals
  • CX Strategy Professionals
  • Customer Journey Managers
  • Customer Success Leaders
  • Customer Service Leaders
  • Customer Experience Operations Professionals
  • Service Experience Managers
  • Customer Research Professionals
  • Customer Analytics Professionals
  • Quality & Service Excellence Professionals
  • Digital Experience Professionals
  • Leaders Responsible for Customer Experience Transformation

Prerequisites & Participant Readiness

  • Experience in customer experience, customer service, customer success, customer insights, research, analytics, or service improvement
  • Familiarity with customer journeys, surveys, feedback, satisfaction metrics, complaints, and customer-experience measurement
  • Basic awareness of Generative AI and common business applications
  • Comfort working with qualitative and quantitative customer information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, text analytics, automation, and AI agents
  • Exploring AI applications across feedback analysis, journeys, experience measurement, and customer insight
  • Distinguishing AI-assisted customer intelligence from automated customer judgement
  • Understanding hallucinations, bias, privacy, profiling risk, and human accountability
Practical activities
  • Mapping AI opportunities across the Customer Experience lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for CX and VoC teams

Scenarios

Falling Customer Satisfaction to Experience Recovery Plan

Survey Data → Complaints → Sentiment → Journey Friction → Root Causes → Improvement Priorities → Future-State Experience → CX Metrics

Participants use AI to analyse declining customer satisfaction, identify journey and operational causes, prioritise improvements, and create a measurable customer-experience recovery plan.

Fragmented Customer Feedback to Enterprise Voice-of-Customer Programme

Surveys → Reviews → Calls → Chats → Support Cases → Theme Analysis → Customer Segments → Executive Insights → Action Governance

Participants use AI to consolidate fragmented customer feedback, identify recurring themes and segment-specific needs, convert insights into executive actions, and build a scalable enterprise Voice-of-Customer operating model.

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