Course Modules

Module 1: Digital Transformation and Customer Intelligence in Telecommunications

• Evolution of customer-centric telecommunications
• Industry challenges:
  • Increasing customer expectations
  • Customer churn
  • Digital competition
  • Omnichannel service delivery
• AI opportunities in customer engagement
• Customer journey mapping
• Customer intelligence frameworks
• Future digital service ecosystems
• Case Study & Practical Application: Assessing customer experience maturity and developing a customer intelligence transformation roadmap for a telecom operator.

Module 2: Customer Data Platforms and Advanced Customer Analytics

• Customer Data Platforms (CDPs)
• Data integration strategies
• Customer segmentation
• Behavioural analytics
• Customer Lifetime Value (CLV)
• Customer journey analytics
• Predictive customer modelling
• Case Study & Practical Application: Building a customer intelligence framework using subscriber data to identify high-value customers and improve retention.

Module 3: Generative AI, Large Language Models and Conversational Intelligence

• Fundamentals of Generative AI
• Large Language Models (LLMs)
• Prompt engineering principles
• Retrieval-Augmented Generation (RAG)
• Natural Language Processing (NLP)
• Intelligent virtual assistants
• AI-powered customer support
• Knowledge management using GenAI
• Case Study & Practical Application: Designing a Generative AI-powered virtual assistant capable of resolving telecom customer enquiries, recommending services, and escalating complex issues.

Module 4: AI-Powered Customer Engagement and Personalization

• Recommendation engines
• Hyper-personalization
• Intelligent marketing automation
• AI-powered campaign management
• Dynamic pricing strategies
• Customer sentiment analysis
• Omnichannel engagement optimization
• Case Study & Practical Application: Developing an AI-driven personalization strategy that recommends tailored products and services based on subscriber behaviour.

Module 5: Customer Experience Analytics and Service Quality Management

• Measuring customer satisfaction
• Customer Experience (CX) analytics
• Quality of Experience (QoE)
• Voice of Customer (VoC) analytics
• Customer feedback analytics
• Service performance measurement
• AI-enabled continuous improvement
• Case Study & Practical Application: Developing an AI-based customer experience dashboard integrating service quality, customer feedback, and operational performance metrics.

Module 6: Revenue Intelligence and Digital Service Innovation

• AI-enabled product innovation
• Revenue optimization
• Customer value management
• Digital ecosystem development
• Subscription analytics
• Bundled service optimization
• AI-driven product lifecycle management
• Case Study & Practical Application: Developing an AI-powered digital product strategy to increase Average Revenue Per User (ARPU).

Module 7: AI Governance, Ethics and Customer Data Privacy

• Responsible AI principles
• AI bias and fairness
• Explainable AI
• Customer data governance
• Data privacy regulations
• Digital trust frameworks
• AI risk management
• Case Study & Practical Application: Developing an AI governance framework for customer-facing digital services aligned with regulatory and ethical requirements.

Module 8: Intelligent Contact Centres and Customer Service Automation

• Contact centre transformation
• Intelligent call routing
• Speech analytics
• AI-assisted customer support
• Robotic Process Automation (RPA)
• Workforce optimization
• Intelligent service workflows
• Case Study & Practical Application: Designing an AI-enabled omnichannel contact centre to improve response times and customer satisfaction.

Module 9: Emerging Technologies and Future Digital Services

• Generative AI evolution
• Digital ecosystems
• AI-powered digital marketplaces
• Metaverse applications
• Extended Reality (XR)
• Edge AI
• Intelligent digital platforms
• Case Study & Practical Application: Designing future digital services leveraging Generative AI, Edge AI, and immersive technologies.

Module 10: Enterprise AI Strategy and Customer-Centric Digital Transformation

• AI implementation roadmap
• Change management
• Innovation management
• Digital transformation strategy
• AI investment planning
• Performance measurement
• Future telecom business models
• Case Study & Practical Application: Developing an enterprise-wide AI and customer intelligence strategy that enhances digital innovation, customer engagement, operational efficiency, and long-term competitiveness.