FutureCentral > AI in Marketing: Building Audiences, Brands, and Categories Across B2C, B2B, and the Sustainability Era
AI in Marketing book cover
Marketing · MBA / Postgraduate

AI in Marketing

Building Audiences, Brands, and Categories Across B2C, B2B, and the Sustainability Era

Austin PM · FutureCentral Press

Connect AI capabilities with audience intelligence, brand decisions, B2C and B2B economics, customer experience, and the evidence needed to support trust.

Manuscript under final review31 chaptersCases and applied exercises
Read the samplesRequest academic copyView contents
EditionFirst edition · in preparation
Structure31 chapters · 9 parts
AudienceMBA and executive learners
AboutRead samplesFrameworksContentsResourcesAcademic enquiries

Marketing decisions across three waves of AI

This book connects marketing’s statistical foundations, analytics and machine learning with generative and agentic AI. A data and measurement spine supports dedicated treatments of B2C and B2B marketing, audience intelligence, creative work, customer experience and governance.

Frameworks, Indian and international cases, sustainability lenses and applied exercises ask readers to choose an approach, examine the evidence and define how the work should be governed.

What readers will learn

  • Match a marketing problem to an appropriate AI capability.
  • Assess data foundations, identity, measurement and attribution.
  • Compare B2C economics with B2B buying cycles and account development.
  • Evaluate generative content, search and agentic campaign workflows.
  • Design customer-journey experiments with statistical discipline.
  • Connect sustainability claims, brand trust and responsible AI governance.

From marketing analysis to a defensible decision

Applied exercises and discussion questions connect the chapter’s argument with a concrete brief, experiment or operating choice. The representative sample asks readers to choose an experimentation method and explain the statistical and customer safeguards it needs.

Read before you decide

Explore the book and its marketing exercises

Read a representative chapter and try its applied exercise online.

Book sample · Chapter 25

CX Journeys and Experimentation at Scale

A/B testing, multi-armed bandits, agentic personalisation, and the CX-data-marketing convergence

The chapter includes two frameworks, case illustrations, an applied exercise, discussion questions and endnotes.

Read sample chapter →
Practical work sample

Marketing Exercise Sample

AI in Marketing: Building Audiences, Brands, and Categories Across B2C, B2B, and the Sustainability Era

Design a CX experimentation programme, justify the method and explain how to protect the evidence and the customer.

Read marketing exercise →
Two frameworks from Chapter 25

Frameworks from the book

The Experimentation Method Decision Tree

Choose the method that fits the question: A/B testing for a discrete comparison, bandits for continuous optimisation, contextual bandits when the best variant depends on context, or agentic personalisation when individualisation justifies its governance burden.

The CX Journey Optimisation Loop

Observe, hypothesise, design, test, learn and scale. AI can support each stage; sound experimental design and honest interpretation remain essential.

Read Chapter 25 for the frameworks and their application →

Table of contents

View all 31 chapters

Part 1: Foundations

  1. The Three Waves in Marketing
    Why marketing in the AI era is different in B2C, B2B, and sustainability-led categories
  2. The Evolution of Digital Marketing
    From brochureware to agentic, through search, social, mobile, influencer, programmatic, and generative AI
  3. AI, ML, GenAI, and Agentic AI for Marketers
    The working mental model: what each technology does, where it breaks, and how to brief it
  4. The Four Marketer Archetypes
    B2C brand lead, B2B and RevOps marketer, performance and growth marketer, sustainability-and-trust marketer, and the fifth specialisation

Part 2: The Data And Measurement Spine

  1. The Marketing Data Warehouse and Identity Graphs
    First-party data, CDPs, the lakehouse turn, and the identity graph as the new marketing asset
  2. The Identity Stack in a Fragmented Browser World
    Cookies, consent, sandboxes that died, and what is actually left
  3. Measurement and Attribution
    MMM, incrementality, MTA, and the B2B long-cycle attribution problem
  4. Clean Rooms and Data Collaboration
    The de facto Sandbox replacement, from Ads Data Hub to Snowflake
  5. The RevOps Stack for B2B Marketers
    Intent data, ABM platforms, and the marketing-sales handoff under AI

Part 3: Audience Intelligence

  1. Segmentation, Targeting, and Look-alikes
    Supervised and unsupervised methods, RFM to embeddings, and the look-alike problem
  2. CLV, Churn, and Propensity
    B2C subscription economics and B2B account expansion, side by side
  3. Recommendation and Personalisation Systems
    Collaborative filtering, content-based, deep recommenders, and agentic personalisation

Part 4: B2C / Consumer Marketing In The Ai Era

  1. D2C Economics and the Unit-Economics Rewrite
    CAC, LTV, payback, and contribution margin under AI-driven acquisition and retention
  2. Retail Media Networks, Quick Commerce, and the New Shelf
    Amazon Ads, Flipkart, Blinkit, Zepto, and Walmart Connect as media platforms
  3. Loyalty, Communities, and Emotional Brand-Building
    From punch cards to AI-augmented loyalty to brand-led communities in the generative era

Part 5: B2B Marketing In The Ai Era

  1. Account-Based Marketing Reinvented
    Intent signals, predictive ABM, and agentic prospecting
  2. Channel, Dealer, and Partner Marketing
    Multi-tier distribution intelligence across industrial, pharma, IT services, and agri-input
  3. The Dark Funnel and B2B Content
    Generative AI for thought leadership, sales enablement, and demand creation
  4. B2B Brand-Building Under Long Buying Cycles
    Category creation, ICP storytelling, and the brand-demand integration

Part 6: Search, Performance, Media, And Creative

  1. Generative Search and SEO/GEO
    AI Overviews, Perplexity, ChatGPT Search, and the new discovery layer
  2. Programmatic, Addressable, and CTV in the Half-Cookied World
    Bidding under privacy constraints, the CTV-as-default thesis, and the contextual revival
  3. Generative AI for Content and Creative
    Text, image, video, brand-voice governance, and the deepfake-and-consent problem
  4. Agentic Advertising
    Autonomous campaign agents, the agency operating model, and the bid-to-creative loop

Part 7: Social, Community, And Customer Experience

  1. Social Media and the Creator Economy
    Algorithmic feeds, AI influencers, social and live commerce, and the fan economy as marketing infrastructure
  2. CX Journeys and Experimentation at Scale
    A/B testing, multi-armed bandits, agentic personalisation, and the CX-data-marketing convergence
  3. Agentic Customer Operations
    Voice agents, conversational commerce, and the human-in-the-loop boundary

Part 8: Sustainability And Trust As Marketing Substance

  1. Sustainability-as-Product, Green Claims Governance, and the Trust Stack
    From sustainability-as-positioning to sustainability-as-product, with the layers that make it credible

Part 9: Governance, Strategy, And The Ai-Native Marketing Org

  1. The Regulatory Landscape
    DPDP, GDPR, the EU AI Act, the DSA, ASCI, US state laws, ASEAN PDPAs, the UK CMA cookie case, and political-deepfake regulation
  2. KPI, Measurement, and the CMO Dashboard
    What the CMO actually watches in the AI era, and what should be on the dashboard but usually is not
  3. Responsible Marketing AI
    The governance operating model that turns responsible-AI principles into how marketing actually works
  4. The AI-Native Marketing Organisation
    How the function must be structured, staffed, and led to wield everything this book has described, and what it all adds up to
Learning and teaching support

Teaching and study resources

Applied marketing exercises

Chapter exercises support marketing briefs, experimentation and operating decisions.

Discussion questions

Questions ask readers to examine the argument and apply it to a setting they know.

Frameworks and decision tools

The chapters supply named frameworks for choosing capabilities, methods and governance.

Case illustrations

Indian and international examples connect the concepts with marketing decisions.

Key terms and further reading

Chapter terms, endnotes and reading suggestions support study beyond the sample.

Academic evaluation

Faculty can enquire about inspection copies and available course materials. The manuscript is under final review.

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