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Data-Driven Marketing with Artificial Intelligence: Harness the Power of Predictive Marketing and Machine Learning

A practical, non-technical guide for marketers and executives on how artificial intelligence, big data, and machine learning are transforming marketing into a data-driven, autonomous, and hyper-personalized discipline.

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What it’s about

Written for CEOs, CMOs, and digital marketing managers rather than data scientists, this book sits between philosophical hype and dense mathematics to explain how AI is already reshaping marketing. It surveys the landscape of commercial AI marketing tools across competitive intelligence, predictive pricing, content marketing, lead acquisition, personalization, and customer service, then explains the underlying technologies of big data, predictive analytics, and machine learning in accessible terms—including a data scientist's tour of common algorithms. It shows readers why and how they might build their own AI solutions, how AI will affect their jobs and industries, what comes next (IoT, machines as customers, blockchain), and the ethical and legal risks of data-driven decision making. Backed by interviews with two dozen vendors, it equips marketers to move from gut feeling and spammy mass marketing to fact-based, self-optimizing, personalized precision marketing at scale.

The through-line

Who it’s for
A CEO, CMO, or digital marketing manager who wants to keep their company competitive and stay relevant in an AI-driven marketing world.
The problem
AI is rapidly disrupting marketing and competitors are already using it, while the marketer lacks a clear, practical understanding of what AI can do. They feel overwhelmed by hype, jargon, and the fear of being left behind or made obsolete.
The plan
  1. Learn the key AI terms and concepts and the difference between weak and strong AI.
  2. Survey what commercial AI marketing tools already do and select the right ones.
  3. Decide whether to build your own custom AI and understand how machine learning systems are structured.
  4. Grasp the basics of big data, predictive analytics, machine learning, and common algorithms.
  5. Deploy and continuously retrain prediction models, and prepare for job and industry disruption.
The payoff
More relevant, personalized, efficient, and cost-effective marketing at scale. · Improved customer experiences, loyalty, and returns through self-optimizing systems. · A competitive, data-driven edge as an early adopter and AI evangelist in your organization.

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