12 Best Product Analytics Books to Read in 2024

Product analytics is a data-driven process whereby companies examine data from user interactions to optimize their products. The objective of these improvements is simple, optimization will improve user experience, which will in turn raise revenues for the company.

It requires knowledge from several different disciplines, including statistics, AI, and user behavior analysis. If you are currently exploring this field for the first time and looking for reviews on the best product analytic books, then this guide is for you.

1. Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights by Joanne Rodrigues

Joanne Rodrigues’ book offers an excellent entry point into the world of product analytics. Although the book touches on some of the math and code used in product analytics, it excels at explaining how product developers can better interpret user actions to predict motivations.

This book also explains how behaviors develop and how this knowledge can be used to change them.

Product Analytics shows how product creators can merge social science with data science to get deeper insights into user actions. The book uses simple and relatable examples to explain topics such as A/B testing and designing better metrics or KPIs.

Why This Book is a Must-Read:

Joanne Rodrigues explains how user behavior can be understood and how product creators can change these behaviors to suit their products. The book also shows how readers can go beyond correlation and focus on causation to better understand why users behave the way they do and address their needs better.

For those who have not used any statistical tools, the book also includes an introduction to R. It shows how it can perform many operations, including predictive modeling, statistical matching, and time-series modeling.

2. Experimentation Works: The Surprising Power of Business Experiments by Stefan H. Thomke

In Experimentation Works, Stefan Thomke shows how experimentation has become a key ingredient of business success and how the world’s biggest companies are reaping huge rewards as a result.

In the book, Thomke explains why experiments yield better results than acting on gut instinct. The author explains how you can decide if an experiment is good and how to conduct online experiments before finally showing us what life is like inside an organization that fully embraces experimentation.

Experimentation Works concludes by exploring how you can effect change in your organization to make it more experiment-friendly.

Why This Book is a Must-Read:

Many organizations still rely on key personnel’s experience and intuition to drive business decisions. In this book, Thomke demonstrates that the best ideas have been those that fly in the face of experience and that good ideas are even easier to identify through experimentation.

Experimentation Works doesn’t focus on the nitty-gritty of running an experiment. It serves as more of a high-level guide to encouraging your organization to embrace experimentation and shows why you should do this.

3. Naked Statistics: Stripping the Dread from the Data by Charles Wheelan

Naked Statistics by Charles Wheelan is an accessible introduction to statistics and probability. The author uses wit, humor, and real-world examples to explain the foundational ideas in this area, including correlation, basic probability, the central limit theorem, and regression analysis.

Wheelan also explains, with examples, how good data is vital to making good use of statistical tools and the mistakes we can easily make when we use statistics and probability to predict the future.

Why This Book is a Must-Read:

Anyone looking to harness the power of product analytics must understand statistical tools and methods well. If this is an area you have found intimidating in the past and traditional textbooks are too math-forward for you, Naked Statistics can be the friendly guide you need.

The book doesn’t teach statistics for the sake of statistics. It is filled with real examples showing why specific concepts matter and how the theory translates to the practical.

4. Lean Analytics: Use Data to Build a Better Startup Faster by Alistair Croll and Benjamin Yoskovitz

Lean Analytics by Croll and Yoskovitz is a guide to help startup founders find the product to help them succeed before they run out of money. The book emphasizes identifying a single metric that best measures the startup’s health at different stages and prioritizing tracking this metric.

The book takes you through the five stages a startup typically goes through, from identifying a problem to scaling a solution. In each stage, the writers explain how to identify the one important metric you need to focus on to give your business the best chance of success.

Lean Analytics is also packed with case studies demonstrating how the methods championed in the book have been successfully implemented in online and offline businesses.

Why This Book is a Must-Read:

Startups have a limited window to come up with a successful product before they become among the 20% of new businesses that fail in their first year. Data analytics can help with this. Still, modern startups are flooded with data and many don’t know what metrics to prioritize.

This book is a useful guide that can help entrepreneurs quickly cut through the flood of data and focus on the metrics that matter most to their success at any given moment. This can help them get a successful product faster.

5. Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions by Matt Taddy

As the title suggests, this book dives into data science largely from the point of view of how it can drive business outcomes. This book will give you the skills you need to work as a data scientist at a highly data-driven company.

Business Data Science moves away from the usual predictive analytics and analyzes causal relationships between events. This approach aims to improve the practical impact data science has on a business.

Matt Taddy’s book offers a hands-on approach, and you’ll be working with statistical formulas and writing code in R to figure out where and how to apply tools like regression, tree-based methods, and unsupervised learning.

Why This Book is a Must-Read:

This book offers an in-depth and fairly technical approach to using data science to drive business outcomes. You get to work with real data examples, write code, and perform actions like cleaning and formatting the data. In essence, it explains what data science is and introduces you to the activities you’ll primarily be engaged in while working as a business data scientist.

6. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

Predictive Analytics by Eric Siegel is not a book on how to use predictive analytics. It is more of a summary of how predictive analytics are already being used, sometimes in ways or by organizations we did not expect.

Eric Siegel talks about both the highlights and perils of using predictive analytics, giving examples of how certain companies can tell if a woman is pregnant or how political campaigns figure out how best to influence your decision at the ballot.

Why This Book is a Must-Read:

Eric Siegel offers a very high-level view of the state of the field of predictive analytics. This is ideal for readers who simply want to understand what predictive analytics can achieve and who uses it for what.

If you have only heard about predictive analytics in passing and want to know more about WHAT the technology can achieve, minus the HOW, this should be on your reading list.

7. Quantifying the User Experience: Practical Statistics for User Research by Jeff Sauro and James R. Lewis

Sauro and Lewis’s book is an ideal resource for those who want to quantify the impact of making qualitative decisions. This book’s primary target is user experience designers who want to have the tools they need to analyze the impact of their design decisions.

Sauro and Lewis offer a deep yet easy-to-understand explanation of how data for user research should be gathered, the tests that can be performed, and even how to determine the precision of estimates.

The book also explains how to create standardized usability questionnaires and deal with some common statistical controversies. The appendix also contains an introduction to basic statistics.

Why This Book is a Must-Read:

If you are interested in assessing the impact of different product designs and whether users think they are good or bad, this book gives you the tools you need to handle this assessment on your own.

This book explains relevant technical concepts in a way many readers will find accessible and spares no detail.

8. The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses by Eric Ries

The Lean Startup champions a new approach to running a startup that encourages constantly iterating the product to figure out what works best faster.

This book proposes several novel approaches, such as launching a minimum viable product early and learning from it, making improvements and deploying updates continuously based on user feedback, and building cross-functional teams that can adapt faster to changing objectives.

The book also introduces the concept of innovation accounting so entrepreneurs can focus on metrics that make a true difference and not vanity metrics. This helps you identify what your users are looking for to build solutions around that.

Why This Book is a Must-Read:

The author of The Lean Startup, Eric Ries, borrows from the successful ideas of lean manufacturing. His book offers an ideology that can serve as a good roadmap to accelerate product development by constantly experimenting, gathering data, and innovating. These ideas can work for traditional businesses as well as online startups.

9. The Signal and the Noise: Why So Many Predictions Fail - but Some Don’t by Nate Silver

Nate Silver’s book is a sobering reminder that the predictions made using statistical analysis don’t always come true. Using a wide range of examples from weather and election forecasting to baseball and poker, Nate Silver takes us through many situations where predictions fall short and, crucially, why they fall short.

The book emphasizes the need to better express the inherent uncertainty associated with statistics.

Silver also criticizes some of the approaches used to teach statistical methods in colleges, claiming they oversimplify complex questions and can foster the idea that a perfect statistical experiment can be conducted with a straightforward answer.

Why This Book is a Must-Read:

Anyone using product analytics needs to know the limitations of these processes and the pitfalls of attempting to make predictions regarding user behavior. The issues pointed out in this book illustrate why constant experimentation is important in product analytics since it is one way of quickly knowing when predictions fail.

This book also serves as a guide for determining which data or metrics are useful and what is nothing more than noise.

10. Advances in Business, Operations, and Product Analytics: Cutting Edge Cases from Finance to Manufacturing to Healthcare by Matthew Drake

Matthew Drake’s book is a collection of case studies that are designed to teach the ideas of analytics by placing the reader in different environments where analytics is used.

The book contains real examples of how organizations use analytics to solve different problems in different sectors, including service and utility industries, accounting and finance, and the public sector.

The case studies are organized according to the analytical techniques used and cover descriptive, predictive, and prescriptive analytics. There is also industry-specific analytics for several industries, including HR and finance.

Why This Book is a Must-Read:

This book allows you to witness the power of analytics in action. Using the case studies in the book, you can see the decision-making process in its entirety, so you can get comfortable performing the analysis and practice using the analysis output to advise on decisions.

11. Building Analytics Teams: Harnessing Analytics and Artificial Intelligence for Business Improvement by John K. Thompson

John K. Thompson’s Building Analytics Teams focuses on how to create and lead effective teams that drive business value through analytics. This book delves into the key elements of assembling a group of data professionals, guiding them to solve business problems and create actionable insights.

The author highlights strategies for hiring the right talent, fostering collaboration between analytics teams and other departments, and overcoming common challenges, such as aligning data projects with business goals. Thompson emphasizes the human aspects of analytics, making this a unique resource for those leading analytics initiatives.

Why This Book is a Must-Read:

If you’re looking to scale product analytics in your organization, this book provides valuable insights on how to build the infrastructure and culture needed for success. It addresses the gap between technical analytics work and business strategy, helping leaders empower their teams to deliver meaningful results.

12. Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking by Foster Provost and Tom Fawcett

Foster Provost and Tom Fawcett provide a comprehensive introduction to data science principles with a strong focus on its applications in business. This book is perfect for those who want to understand the theoretical underpinnings of analytics while exploring practical ways to apply these concepts.

The authors cover key topics such as predictive modeling, classification, and clustering while providing business-oriented examples to clarify how data science creates value. The book also teaches you to think analytically about data problems, making it a useful resource for product managers and analysts alike.

Why This Book is a Must-Read:

This book bridges the gap between technical knowledge and business application, making it ideal for product professionals who want to understand the data-driven decisions shaping their industries. Its practical examples ensure readers can connect data science concepts to real-world challenges and opportunities.

Which are the best books to get started on product analytics?

If you have a good foundation in statistics or data science, start with a book that focuses on applying data science, understanding user behavior, conducting proper experiments, and identifying useful metrics.

If you don’t have a good grasp of statistics, you can also get a book on statistics or take a course on the same. Interview Query offers statistics and AB testing courses so you can also refresh your knowledge of the same.

What other resources and tools can I use to learn about product analytics?

There are videos on YouTube and online courses that you can take to quickly learn about different concepts in product analytics. Interview Query’s learning paths also offer many courses that are related to product analytics including courses on data science, data analytics, product metrics, and machine learning.

Who needs to learn about product analytics?

Product managers, startup founders, product marketing managers, and product developers can all benefit from learning about product analytics. Even employees who don’t directly work in analytics can learn about product analytics to facilitate a career change or to augment their skills.

Product analytics has been a key ingredient in the successes of many modern companies. The books on this list can teach you the skills and techniques they use, and how to implement them effectively.

If product analytics is key to your career goals, Interview Query offers other resources you can benefit from including company interview guides, and interview questions for product analysts. You can also visit our job board or check out the state of product analyst salaries in the industry today.

Modern business dynamics favor companies that use product analytics. We believe the books on our list should be essential reading for those looking to establish themselves in this field this year.