IIT Bombay | Executive Leadership for CMOs in the Age of AI

• Educational Background: Bachelor's or Master's degree (or higher qualification) in business administration/marketing from a recognised university.
• Professional Experience: Minimum of 8 years of relevant professional work experience.

Module 1: Business Models, Competitive Landscape, and Growth Strategy

Topics Covered:

• Product, subscription, platform, and ecosystem-based business models
• Growth strategy: core growth, adjacency expansion, and new growth bets
• The evolution of marketing: from performance marketing to phygital, omnichannel, immersive
• experiences, and Marketing 6.0
• Hyper-personalisation and its implications
• CMO strategies for balancing technology, data, and AI to sustain market leadership

Module 2: Customer Value Chain Analysis and Experience Management

Topics Covered:

• Buyer personas and consumer behaviour across omnichannel journeys
• Decoding the customer experience
• Customer value chain analysis and customer lifetime value modelling
• New approaches to market segmentation
• Customer engagement, brand communities, and next-generation immersive experiences

Module 3: Product and Brand Strategy in Digital and AI-Mediated Markets

Topics Covered:

• Product management and product-market fit in digital markets
• Building and measuring brand equity: new tools and brand valuation models
• Promotion strategy across traditional and digital channels
• Influencer marketing strategy

Module 4: Revenue, Pricing, and Go-To-Market Strategy

Topics Covered:

• Value-based pricing models and linking brand investment to margins using conjoint analysis
• Evolving pricing architectures: BNPL, freemium, monetisation layers, and AI-driven dynamic pricing
• Omnichannel go-to-market strategy and channel design
• Measuring GTM eectiveness and revenue ROI

Module 5: Researching Customers: Evidence Over Intuition

Topics Covered:

• Experimental design and A/B testing at scale
• Neuromarketing research to understand subconscious consumer responses
• Digital and real-time research: social listening, customer journey analytics, and behavioural data

Module 6: AI Foundations and the Agentic AI Paradigm for Marketing

Topics Covered:

• AI foundations and Prompt Engineering for marketing leaders
• The evolution from traditional marketing automation to agentic AI for marketing
• The agentic AI for marketing paradigm and its implications for strategy, operations, and organisational design

Module 7: Digital Marketing Communications: The Core and the Agentic Evolution

Topics Covered:

• The shift from SEO to AI-mediated search: SGE, GEO, and the agentic web
• Automated brand identity with Google Pomelli
• High-velocity content marketing
• Paid media, attribution, and data-driven performance
• Social engagement, community building, and social media orchestration with visual scaling
• Email marketing and lifecycle management: conversational CRM and the "Claude Skill" writer
• The hybrid MarTech stack from no-code to AI-code
• Agentic AI for sales, channels, and distribution

Module 8: Marketing Analytics and Agents

Topics Covered:

• Descriptive, predictive, and prescriptive analytics as a decision-making framework
• Multi-channel data ingestion agents
• Customer journey and attribution agents
• Audience intelligence and segmentation agents
• Campaign anomaly detection and alerting
• Predictive analytics and revenue forecasting
• Budget optimisation and media mix agents
• Content and creative performance agents
• Competitive intelligence agents
• Marketing Command Centre and agent orchestration
• Predictive modelling for demand forecasting and churn modelling
• Governance and ethics