Freemium Economics: Commerce at a Price Point of $0

Between March and June 2013, I spent my mornings, evenings, and weekends writing a book about the freemium business model called Freemium Economics. I was inspired to write the book one day after curiosity compelled me to count the total number of words across all my blog posts. The number was over 100,000, and I reasoned that such a voluble mass of opinion could be easily copied and pasted into a Word document and submitted to a publisher as a book. More than a year later, I realise how silly that notion is; in the end, Freemium Economics was entirely written from scratch.

Many people assume two things about Freemium Economics: that it’s about gaming, and that it’s about product design (UX / economy balancing / product psychology / etc.). Neither of those assumptions is true. In fact, Freemium Economics covers topics that I believe are ignored by many product developers, but which ultimately form the crux of the freemium model: the economic principles that drive freemium, analytics architecture, data-driven product design, applied statistical analysis, quantifying nebulous metrics like LTV and K-factor, and performance marketing. The chapter list of Freemium Economics is as follows:

Chapter One: What is the Freemium Model?
Chapter Two: Analytics as the Heart of Freemium
Chapter Three: Quantitative methods for product management
Chapter Four: Freemium Metrics
Chapter Five: Lifetime Customer Value
Chapter Six: Monetization and Downstream Marketing
Chapter Seven: Virality
Chapter Eight: Optimized User Acquisition

These topics aren’t “sexy”, and as a result, very few books (or blogs) tackle them. I wrote Freemium Economics to fill that void. Many books cover the conceptual architecture of freemium product design – the qualitative aspects of building something that people love, tell their friends about, and, ultimately, pay for. I wanted to write a book that helps product managers quantify those “fuzzy” topics and use the data they harvest from their products to drive desired behaviors.

I wrote Freemium Economics to allow a product manager to answer questions like, “I know that half of my users aren’t returning after their first session — what is causing that?”, or, “Acquiring a user for my product in a key demographic costs $X, is that profitable?”.

In fiercely competitive marketplaces like the App Store, these questions are increasingly important, while simultaneously becoming increasingly difficult to answer. Products like GameAnalytics are indispensable in the creation of freemium products – but in the hands of the uninitiated and uninformed, they’re not nearly as helpful as they could be. A metrics dashboard might as well be hieroglyphics to a product manager that doesn’t, at a deeply intellectual level, understand the interplay between data, design, and delight in freemium products.

Psychology and aesthetics are critical aspects of product design, no doubt. But for freemium products, mastery of those domains isn’t enough to tip the scales toward success: product managers must also understand how data can be used to iteratively improve product performance. Freemium Economics is a dense (an Amazon reviewer calls it “a bit too much to handle for people new to this business model”), dry, quantitatively-focused guide to harnessing data in freemium products to drive revenue. The book contains no charming anecdotes, wry metaphors, humorous asides, or clever wordplay: it’s a 250 page beast of a tome illustrated with over 100 graphs and charts. If you like your books to be peppered with visuals of Excel screenshots and algebraic formulas, you’ll love Freemium Economics.

In the end, I believe success in freemium marketplaces like the App Store is attributable in some part to luck. Luck is capricious and unpredictable; I didn’t write a book about luck. Freemium Economics is a book about how to maximize your product’s revenue whether it hits the lottery on the App Store or not: it’s less Flappy Bird than Game of War, less Chat Roulette than WhatsApp. Freemium Economics is a user’s manual to products like GameAnalytics, and I think it has a place on the bookshelf of any product manager that doesn’t want to rely solely on luck.