Last updated March 2026
Top Three Quotes
- “Technology alone will not create better customer relationships—it’s the culture and structure that must evolve with it.”
- “Generative AI may finally deliver on the decades-old one-to-one marketing promise, but only if companies put the customer’s interest first.”
- “Trust is the foundation for creating value on both sides of any customer relationship.”
Book Theme
The New Science of Customer Relationships explores how artificial intelligence and data science are transforming customer relationships. It examines the gap between decades of marketing promises (like personalization and one-to-one marketing) and the reality of limited progress, proposing a new, evidence-based discipline called customer science—the use of AI, analytics, and organizational change to build trust-based, individualized customer engagement.
Why You Should Read This Book
- Understand how AI and generative AI can realistically personalize marketing, sales, and service.
- See why organizations—not technology—are the main barriers to effective customer relationships.
- Learn how leading companies are already succeeding with AI-driven personalization.
- Discover a practical roadmap for using AI ethically while protecting customer trust and privacy.
- Gain insight from two of the most respected authorities in analytics and marketing technology.
Key Ideas and Arguments Presented
- The one-to-one marketing dream remains unfulfilled—most firms still use mass tactics despite decades of customer data.
- Generative AI now makes it technically possible to personalize at scale, but organizational culture and data integration lag behind.
- Customer science combines rigorous data analysis, controlled experimentation, and continuous learning to improve relationships.
- Data quality and definition issues (like who “the customer” really is) are the biggest obstacles to customer insight.
- Better AI, data, and ethics must work together to transform marketing from manipulation to mutual value creation.
- AI agents and automation can handle routine interactions, freeing humans for empathy-driven work.
- Hyper-personalization requires collaboration across departments—marketing, sales, service, and analytics.
- Ethics and transparency are essential; trust is the new competitive advantage.
- The customer of tomorrow expects seamless, respectful, and intelligent interactions.
- True personalization is not a one-time project but a sustained scientific process.
Book Outline
- The Broken Promise of Customer Data and Technology – Why decades of innovation failed to produce real personalization.
- The Future Is Here, but Unevenly Distributed – Case studies of companies succeeding with AI-driven customer engagement.
- Better AI: Generative AI as a Catalyst for Change – How GenAI transforms customer relationships.
- Better Data – Data strategy and quality as the foundation of customer science.
- Better Personalization and Hyper-Personalization – How to tailor marketing for individuals.
- Better Customer Voice Analysis and Action – Using AI to listen and respond effectively.
- Better Task Automation with AI Agents – Automating repetitive customer tasks with intelligence.
- Better Customer-Facing Operations – Integrating marketing, service, and operations for unified CX.
- Better Customer Analytics and Data Science – Modern analytics for predictive, personalized insight.
- Better Ethics – Navigating privacy, bias, and trust in AI-powered marketing.
- The Customer of Tomorrow – Visionary outlook on how AI will reshape the customer experience.
Key Takeaways
- Technology progress has outpaced organizational readiness.
- Generative AI can finally make scalable personalization possible—but only when supported by ethical data use.
- Customer trust is non-negotiable; value creation must serve both sides.
- Customer science is a continuous cycle of experimentation, data integration, and improvement.
- The future of marketing lies in transparent, data-driven empathy—using AI to understand, not exploit.
Key Techniques
- Customer Science Framework: A continuous process of data collection, AI-driven analysis, and behavioral experimentation.
- Hyper-Personalization Process: Combining structured and unstructured data for real-time, individualized offers.
- AI Agent Integration: Deploying intelligent agents to handle routine customer interactions.
- Voice of Customer (VoC) AI: Using sentiment and speech analytics to guide proactive responses.
- Ethical AI Governance: Establishing policies that prioritize privacy, fairness, and long-term value.
Author’s Qualifications
Thomas H. Davenport: Distinguished Professor at Babson College, MIT Fellow, Senior Advisor to Deloitte, and author of over 25 books including Competing on Analytics. Recognized globally as one of the top voices in AI and data-driven business strategy.
Jim Sterne: Digital analytics pioneer, founder of the Marketing Analytics Summit, author of 12 books on marketing and AI, and advisor to leading global organizations on generative AI adoption.
Comparison to Similar Books
Comparable to Competing on Analytics (Davenport) and The One-to-One Future (Peppers & Rogers), this book blends AI innovation with practical business insight. Unlike purely technical AI guides or marketing casebooks, The New Science of Customer Relationships provides a scientific, ethical, and cross-functional framework for modern marketing transformation.
Target Audience
- Marketing executives adopting AI
- Data and analytics professionals
- Customer experience and CRM leaders
- Business strategists and consultants
- Technology executives and product managers
- Entrepreneurs in AI-driven industries
- Academics and students studying digital transformation
Critical Response to the Book
Early readers and industry reviewers praise the book for being both visionary and grounded, offering a realistic path to personalization after decades of hype. It’s recognized as a must-read guide for aligning AI innovation with customer trust and long-term business value.
One Sentence Takeaway
The New Science of Customer Relationships reveals how organizations can finally fulfill the long-promised vision of one-to-one marketing through AI, data, and ethics—by putting customer trust and value at the heart of every decision.
