Role-Based Programme
RB1279

AI for Customer Retention & Renewals

Advanced Churn Intelligence, Renewal Strategy & Customer Value Growth

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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 retention, renewal planning, churn prevention, relationship management, and revenue protection.
  • Use AI-assisted analysis to identify customer health changes, adoption gaps, dissatisfaction signals, stakeholder risks, commercial concerns, and renewal barriers.
  • Apply AI to renewal preparation, value demonstration, customer recovery, stakeholder engagement, objection management, and retention planning.
  • Use AI-assisted analytics to strengthen retention rates, renewal predictability, customer lifetime value, account stability, and appropriate expansion opportunities.
  • Build responsible AI-enabled Retention and Renewal workflows with strong privacy, governance, validation, commercial discipline, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchCustomer Health AnalysisChurn Risk AnalysisRenewal IntelligenceCustomer Sentiment AnalysisAdoption AnalyticsValue Realisation AnalysisStakeholder MappingRenewal ForecastingExpansion Opportunity AnalysisCRM IntelligenceWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Customer Retention Managers
  • Renewal Managers
  • Customer Success Managers
  • Senior Customer Success Managers
  • Account Managers
  • Strategic Account Managers
  • Customer Renewal Specialists
  • Customer Lifecycle Managers
  • Customer Success Operations Professionals
  • Customer Experience Managers
  • Customer Health Analysts
  • Commercial Customer Success Professionals
  • Retention Analysts
  • Revenue Operations Professionals Supporting Renewals
  • Leaders Responsible for Customer Retention & Renewal Revenue

Prerequisites & Participant Readiness

  • Experience in customer success, renewals, account management, retention, customer experience, or commercial customer management
  • Familiarity with customer health, adoption, renewal cycles, contracts, CRM systems, and customer business reviews
  • Basic awareness of Generative AI and common business applications
  • Comfort working with customer, usage, engagement, commercial, and relationship data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across churn prevention, renewal planning, customer recovery, and account growth
  • Distinguishing AI-assisted retention management from automated commercial decision-making
  • Understanding hallucinations, customer-data sensitivity, bias, and human accountability
Practical activities
  • Mapping AI opportunities across the retention and renewal lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Retention and Renewal teams

Scenarios

At-Risk Customer to Renewal Recovery Plan

Health Signals → Usage Decline → Customer Feedback → Stakeholder Risk → Root Causes → Recovery Actions → Value Evidence → Renewal Plan

Participants use AI to analyse an at-risk customer, identify the combination of adoption, experience, relationship, and commercial risks, and create a structured recovery and renewal strategy.

Large Renewal Portfolio to AI-Enabled Retention Strategy

Renewal Calendar → Customer Health → Revenue Exposure → Risk Segmentation → Intervention Priorities → Renewal Forecast → Executive Dashboard → Retention Actions

Participants use AI to assess a large portfolio of upcoming renewals, prioritise accounts by risk and revenue exposure, improve renewal forecasting, and create a scalable retention operating model.

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