The Fandom Analytics Book

I finally took the time to write a book on fandom analytics. If you enjoy the blog and podcast content, the book would be a great next step. I've written the book to complement my courses at Emory, so it should be an excellent reference for students (past and present) or anyone working in a "fandom Category." I've included the preface and the book description below.

You can get the book at Amazon by clicking here. I've kept the pricing sane - the pre-order price is $31.34.

Back of the Book

The success of modern sports, entertainment, political, and other cultural categories is driven by organizations’ ability to create and manage fandom. This book explores fandom from a marketing perspective providing a multidisciplinary framework for understanding, measuring, and growing fandom. It provides a fandom analytics framework for creating and managing fandom and identifies the macro forces (technology, demographics, etc.) that are changing fandom’s structure and societal role. The book goes beyond understanding the foundations of fandom by demonstrating how marketing tools may be employed to value and manage fandom assets. It is designed for existing and new generations of sports and entertainment professionals, as well as scholars, students, and academics interested in sports and entertainment marketing and analytics.

Preface

Welcome! The book you are now beginning (or considering) reading represents the culmination of the last two decades of my professional life. I’ve started to think of my career as a three-act play. This work is the apex of the second act.

I started my intellectual journey as a quantitative marketer with multiple degrees in optimization and statistics. I spent the first 15 years of my business school professor career working on topics like yield management, dynamic pricing, and consumer loyalty programs. My work on these topics often used dynamic optimization models of consumer behavior. The goal was always to optimize the value of some asset, whether it was a consumer relationship, inventory, or a brand. It was complicated mathematics applied to explain and improve decisions related to consumers. I think of this as my first act: a marketing scientist specializing in the dynamic analysis of customers and other marketing assets.

The best thing about academia is the freedom. Marketing analytics is a worthy field, and dynamic models of consumer behavior are important, but I started to get a little bored. It was time to start something new. I began to spend more time on an underappreciated part of marketing: how marketing impacts society and culture. Developing an algorithm for setting prices to maximize customer lifetime value or setting shipping fees to optimize customer spending is worthwhile. Still, this type of work is mainly interesting to firms trying to improve their bottom line.

To me, the part of marketing that really matters is where marketing touches culture and inspires passion. Consumer loyalty matters to brands, but the loyalty we see in the grocery store pales compared to the passion we witness in people interested in sports, entertainment, politics, and other categories that make up our culture. I define fandom as the passion for some cultural entity. For my second act, I decided to apply my skills in customer analytics to topics in sports and culture (there has also been some work on politics, movies, and fashion). I think of this work as Fandom Analytics.

My second act has been an easy transition. Customer lifetime value models are not that different from models of player performance. Models of brand equity can be applied to baseball teams or soft drinks. I’ve worked on various topics ranging from on-field performance metrics to brand equity analysis for sports clubs. My second act involved combining my academic skills with my lifelong love of sports to develop a portfolio of work focused on sports and fandom analytics. It’s been a passion project that has allowed me to stay interested and to keep learning.  

A short book to an author can feel like a long book to a reader or student. When I think about the classes I've taken and the books I’ve read, things can usually be boiled down to a couple of paragraphs and maybe a key figure or two. It's just how we learn; we store a high-level summary of the material, and this map is there to bring us back to the source material when we need the details. What are the key takeaways from “Fandom Analytics?”

• The foundational argument of the book is that fandom is a critical part of human behavior that impacts both marketing results and the cultures we live in. The brands that create fans dominate the marketplace, and the cultural entities (sports, entertainment, politics, gaming, etc.) that inspire fandom define our societies.

• The Fandom Analytics Framework in Figure 2.1 provides a tool for structured thinking about fandom creation and management. The framework provides the roadmap for the book and is the critical concept I want readers to gain from the book.

• Fandom Analytics requires an interdisciplinary approach that considers stories' roles in subcultures, fandom's psychological identity benefits, and the marketing concepts of brand and customer equity. The core of fandom analytics should be sports analytics techniques that identify great players and create outstanding teams.

• The chapters on “Fandom Beyond Sports” and “The Future of Fandom” are about generalizing the book's ideas to think beyond our main context of sports and beyond what fandom looks like at the moment. The book studies the critical concept of fandom in the realm of sports, but the material can be extended to all sorts of cultural products.   

I’ve spent a lot of time thinking about and researching issues related to fandom. When it came time to put this thinking into a book, a bunch of decisions needed to be made to keep the presentation concise.  I would like to mention 3 of these decisions.

The first decision was whether to ground the book in the single category of sports or to take a more general approach to the topic and discuss fandom across multiple categories. This was a real dilemma. A book about just sports feels a little limiting, but a book about all of fandom would probably require multiple volumes. I’ve attempted to split the difference and write about primarily sports fandom with selected material that extends the work to other categories.        

Second, a challenge in writing a book about fandom is the balance between examples and theory. Examples are more powerful for most readers, but theory is more enduring. Given that the book is about fandom, I decided to err on the side of more examples and less academic theory. As the book is written in the second half of 2023 from my location at Emory University in Atlanta, the examples frequently feature names like Taylor Swift and Lionel Messi. As a side note, even coming up with examples is fairly challenging. There are very few shared cultural references these days, so I try to keep it to the big names.  

The third predicament is the issue of technical content versus accessibility. Analytics can quickly become complex. But the goal is not to write a book on statistics, so I have kept equations and mathematics to a minimum. I have provided selected references for the more adventurous analyst. The goal is to provide the structure and perhaps motivation rather than a technical treatment. Given the breadth of the topic, a technical treatment would require a much more extensive and complicated book.

The folks offering endorsements of the book deserve a special shout-out. The folks include top marketing analytics executives at the Atlanta NBA and MLB teams, an e-sports evangelist, a sportswriter who has written about NASCAR, and a woman who was the first female general manager in MLS. I’ve included these folks as they have been frequent sources of information and inspiration. These folks are passionate sports pros who work in very different functions, but at the core, they are all in the business of fandom. There is nothing better than when the professor learns something, and I’m grateful to know them.

Finally, I also want to mention a few folks from “within” the academy who contributed to the project. Doug Battle is my podcast producer and second mike. He is a great fan and provided my indirect source material. Jonathan Fineman and Jesse Bernstone were my teaching assistants and helped massively with figures. Last but certainly not least, Manish Tripathi, a former faculty at Emory, was an amazing partner during the early days of the sports analytics project.