Role-Based Programme
RB1290

AI for Customer Service & Customer Success

Customer Intelligence, Service Excellence & Retention Growth

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

Programme Objectives

  • Develop practical AI capabilities across customer support, customer success, onboarding, experience, retention, and service operations.
  • Apply AI to analyse customer interactions, feedback, product usage, support history, health indicators, service issues, and churn signals.
  • Use AI to improve customer communication, case resolution, onboarding, success planning, knowledge management, and renewal readiness.
  • Strengthen customer-service and customer-success decisions through analytics, journey intelligence, root-cause analysis, and performance insights.
  • Apply responsible AI practices related to privacy, confidentiality, bias, customer data, response accuracy, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchCustomer IntelligenceConversation AnalysisCustomer Sentiment AnalysisKnowledge RetrievalCase SummarisationCustomer Health AnalysisChurn Risk AnalysisService AnalyticsCRM Workflow ConceptsExecutive Summarisation

Who should attend

  • Customer Service Managers
  • Customer Success Managers
  • Customer Support Managers
  • Customer Experience Managers
  • Customer Service Executives
  • Customer Success Executives
  • Customer Support Specialists
  • Customer Relationship Managers
  • Customer Onboarding Professionals
  • Customer Retention & Renewal Professionals
  • Contact Centre Professionals
  • Service Operations Professionals
  • Customer Success Operations Professionals
  • Quality & Service Excellence Professionals
  • Customer Service & Success Leaders

Prerequisites & Participant Readiness

  • Experience in customer service, customer success, customer support, customer experience, or relationship management
  • Familiarity with CRM systems, customer interactions, support processes, onboarding, retention, or service metrics
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret customer and service information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across support, onboarding, success, retention, and customer experience
  • Understanding how AI differs from CRM, helpdesk, customer-success, and analytics platforms
  • Recognising hallucinations, unsupported assumptions, and AI limitations
Practical activities
  • Mapping the end-to-end customer lifecycle to practical AI applications
  • Identifying high-value versus high-risk use cases
  • Comparing traditional and AI-assisted customer workflows

Scenarios

Customer Issue to Successful Service & Success Recovery

Customer Interaction → Intent & Sentiment Analysis → Case Resolution → Root-Cause Review → Customer Health → Recovery Actions → Follow-Up → Success Plan

Participants use AI to analyse a simulated customer issue, support resolution, identify wider account risks, and develop a structured recovery and success plan.

Customer Portfolio to Retention & Growth Strategy

Customer Data → Health Analysis → Adoption Review → Voice of Customer → Churn Risk → Renewal Readiness → Retention Actions → Portfolio Strategy

Participants use AI to analyse a simulated customer portfolio, identify at-risk and high-potential accounts, and develop a structured strategy covering adoption, retention, renewal, and customer value.

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