[{"_1":2,"_46":-5,"_47":-5},"loaderData",{"_3":4,"_14":15,"_44":-5,"_45":-5},"root",{"_5":-5,"_6":-5,"_7":-5,"_8":9,"_10":11},"user","shoppingCartId","toast","locale","en","constants",{"_12":13},"paypalClientId","AenrHU49peF-ZUH-Yq7AXLLNZYGUGlml474U16NCjB4ZznmQCEjiliN3whyuVZmkb7VxEzmTALgtKEKE","routes/_store+/_readers+/email_author.$slug/route",{"_16":17,"_43":-5},"book",{"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":29},"id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNjg0ODU","title","PRODUCT INTELLIGENCE","state","published","contactAuthorMethod","email","aboutText","

Product Intelligence is a practical, deeply insightful guide for modern product teams navigating a world where intuition is no longer enough. Drawing from real failures such as the $100 million intuition-led mistake and global case studies across Europe, Africa, Asia, and North America, the book shows why traditional product development breaks down in high-velocity environments and how organisations can evolve into intelligence-driven systems.

At its core, the book defines Product Intelligence (PI) as the fusion of data science, product design, and product management, working together in a closed learning loop that turns raw behavioural data into predictions, experiments, decisions, and measurable outcomes. Through this lens, readers learn how to build systems that observe behaviour, model it, test hypotheses, and adapt in real-time creating products that not only respond to users but learn from them continuously.

The book demystifies the full intelligence lifecycle from instrumentation and telemetry, to modelling, experimentation, and automated decisioning while exposing common pitfalls such as relying on dashboards for decision-making, mistaking correlation for causation, and failing to unify qualitative and quantitative insight. It introduces frameworks like the Closed-Loop Product Intelligence Cycle, Data-Driven Empathy, and Minimum Viable Experimentation, equipping readers to turn insight into action at scale.

Through vivid examples from Nigeria’s KYC failures to UK SaaS churn patterns, and from predictive credit scoring to personalised onboarding the book reveals how leading companies build adaptive, ethical, and data-fluent product teams. It also explores the future of product leadership: autonomous decision engines, agentic products, ethical guardrail metrics, and the rise of the Data Product Manager.

Ultimately, Product Intelligence is a blueprint for product managers, designers, engineers, analysts, and founders who want to build products that think, learn, and decide products shaped not by assumptions, but by intelligence.

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