Freemium Economics: Leveraging Analytics and User Segmentation to Drive Revenue

By Eric Benjamin Seufert

Freemium Economics presents a practical, instructive approach to successfully implementing the freemium model into your software products by building analytics into product design from the earliest stages of development.

Your freemium product generates vast volumes of data, but using that data to maximize conversion, boost retention, and deliver revenue can be challenging if you don't fully understand the impact that small changes can have on revenue. In this book, author Eric Seufert provides clear guidelines for using data and analytics through all stages of development to optimize your implementation of the freemium model. Freemium Economics de-mystifies the freemium model through an exploration of its core, data-oriented tenets, so that you can apply it methodically rather than hoping that conversion and revenue will naturally follow product launch.

• Learn how to apply data science and big data principles in freemium product design and development to maximize conversion, boost retention, and deliver revenue
• Gain a broad introduction to the conceptual economic pillars of freemium and a complete understanding of the unique approaches needed to acquire users and convert them from free to paying customers
• Get practical tips and analytical guidance to successfully implement the freemium model
• Understand the metrics and infrastructure required to measure the success of a freemium product and improve it post-launch
• Includes a detailed explanation of the lifetime customer value (LCV) calculation and step-by-step instructions for implementing key performance indicators in a simple, universally-accessible tool like Excel

• Language: English
• Publisher: Elsevier Science
• Release date: Dec 27, 2013
• ISBN: 9780124166981

Eric Benjamin Seufert

Eric Seufert is a quantitative marketer with a passion for blending real-world problems with large amounts of data, econometric frameworks, and analytical systems. His professional specialty lies in programmatic statistical methods and predictive forecasting in freemium environments. Eric received an undergraduate degree in Finance from the University of Texas at Austin and an MA in Economics from University College London, where he was an Erasmus Mundus scholar. Eric joined Skype immediately out of graduate school and subsequently held marketing and strategy roles at Digital Chocolate and Wooga, where he is now the Head of Marketing. Prior to graduate school, Eric worked at uShip, the Austin-based marketplace for shipping services. Originally from Texas, Eric currently lives in Berlin. In his spare time, Eric enjoys traveling and writing.

Book preview

1

The Freemium Business Model

This chapter, The Freemium Business Model, introduces the freemium model from a conceptual, academic, and practical standpoint, establishing several fundamental considerations that are used throughout the book. Although the freemium model is a fairly recent development, having been popularized with the widespread adoption of mobile smartphone devices and tablet devices that are constantly connected to the Internet, its roots exist in a business model that was prevalent in the 1980s called feature-limited software development, which was distributed on physical discs.

The chapter begins with an overview of the principles of the freemium model, which offer conditions and requirements for freemium success. These principles are scale, insight, monetization, and optimization. The chapter then addresses three economic concepts that render the freemium model viable: the price elasticity of demand, price discrimination, and Pareto efficiency. The chapter ends on a practical note with case studies of three freemium success stores: Skype, the peer-to-peer calling product; Spotify, the streaming music service; and Candy Crush Saga, the casual puzzle game from developer King.

Keywords

freemium; price discrimination; price elasticity of demand; Pareto optimal; prisoner’s dilemma; consumer insight; Skype; Spotify; King.com; Candy Crush Saga

Commerce at a price point of $0

All business models are malleable thought structures, meant to be adapted and decisively employed to best achieve a specific product’s or service’s goals. This being understood, and for the purposes of this book, a broad and basic formal definition of the freemium business model is described as follows:

The freemium business model stipulates that a product’s basic functionality be given away for free, in an environment of very low or no marginal distribution and production costs that provides the potential for massive scale, with advanced functionality, premium access, and other product-specific benefits available for a fee.

The freemium business model is an adaptation of a fairly common distribution and monetization scheme used in software since the 1980s: the feature-limited software paradigm was when consumers saw most of the fundamental core components of a product released for free, with the product’s remaining functionality (such as saving progress or printing) becoming available only upon purchase, either in a one-time payment or through recurring subscription payments.

The most basic point of difference between the freemium business model—freemium being a portmanteau of free and premium—and the feature-limited model is distribution: feature-limited software products were generally distributed on physical discs, whereas freemium products are almost exclusively distributed via the Internet. So the distribution speed and ultimate reach of feature-limited products were a function of the firm’s capacity to produce and ship tangible goods; no such restrictions limit the distribution of freemium products.

A second distinction between the freemium and feature-limited business models is the scope of functionality of each: whereas feature-limited products often merely showcased the look and feel of the full product and could not be used to fulfill their primary use cases at the free price tier, with freemium products, payment restrictions generally do not limit access to basic functionality. Rather, freemium products exist as fully featured, wholly useful entities even at the free price tier; payment generally unlocks advanced functionality that appeals to the most engaged users.

The freemium model represents a fundamental evolution from the feature-limited model, given a new set of circumstances under which software is distributed and consumed: mobile devices give users access to products at a moment’s notice and throughout the day, cloud storage services and digital distribution channels allow products to be discovered and purchased without the need for physical discs, and digital payment mechanisms render purchases nearly frictionless.

The pervasiveness and connectedness of software, then, represents a heightened state of awareness with respect to the demands made upon software by users. And it also presents a massive opportunity to quickly and almost effortlessly reach millions, if not billions, of potential consumers upon product launch. This is the reality of the modern software economy, and it is the backdrop against which the freemium business model has emerged.

Components of the freemium business model

The ultimate logistical purpose of the freemium business model—and the source of the advantages it affords over other business models—is the frictionless distribution of a product to as large a group of potential users as possible. This potential for massive scale accommodates three realities of the freemium model:

1. A price point of $0 renders the product accessible to the largest number of people.

2. Some users will not engage with the product beyond the free tier of functionality.

3. If the product is extremely appealing to a group of users, and the product presents the opportunity to make large or repeat purchases, a portion of the user base may spend more money in the product than they would have if the product had cost a set fee. Thus, the revenue fulcrum, or the crux of a product manager’s decision to develop a freemium product, is the potential to maximize scale, paid engagement, and appeal to the extent that the total revenue the product generates exceeds what could be expected if the product cost money.

While the freemium business model is not governed by a rigid set of physical bounds, some patterns hold true across a large enough swath of the commercial freemium landscape to be interpreted as intellectual thresholds. The first pattern that emerges is that the broader the appeal of a product, the more potential users it can reach and the more widely it will be adopted. A broadly appealing product has a widely applicable use case, or purpose. Generally speaking, products that address a universal need, pain point, or genre of entertainment appeal to more people than do products that serve a specific niche. Broad applicability obviously has a direct impact on the number of users who adopt a product.

The second pattern is that very few users of freemium products ever monetize, or spend money on them. The low proportion of users who monetize in freemium products contributes to the necessity of large potential scale: a low percentage of monetizing users within a very large total user base might represent a respectable absolute number of people. This concept is referred to in this book as the 5% rule, or the understanding that no more than 5 percent of a freemium product’s user base can be expected to monetize prior to product launch.

The third observable trend with the freemium model is that the spectrum of total monetization levels—that is, the total amount of money users spend within the product—spans a wide range of values, with a very small minority of users spending very large amounts of money. The larger the minority of highly engaged users, the more revenue the product generates in aggregate; when the spectrum of monetization levels is broad, more users tend to monetize than when the spectrum is limited to fewer values.

The confluence of these three trends establishes a freemium development directive: the broader the appeal, the higher the level of engagement; and the more numerous the opportunities to engage that the product offers, the more revenue it will generate. At some optimized point, these forces can contribute to a more advantageous revenue dynamic than could be expected under paid adoption circumstances. If frictionless distribution is the logistical purpose of the freemium model, then its commercial purpose is to establish the product attributes necessary to achieve greater monetization and absolute revenue than would be possible using a paid adoption model.

Establishing the aforementioned product attributes to fully leverage the advantages of the freemium model is not achieved through a trivial set of design decisions. The decision to apply the freemium business model to a product is one of the most formative choices made during the development process; it must be made while establishing the product’s fundamental use case, and it must inform every aspect of the development process that follows.

The reality of the freemium model is that it can very easily be misapplied. Thus, the decision to employ the freemium model or another commercial framework is first and foremost a function of ability—not whether the product should be freemium, but whether the team possesses the expertise and experience to produce a successful freemium product. If the answer to this question is yes, but a qualified, conditional, or equivocal yes, then the team is not well positioned for success. The product that emerges from the development process is an external expression of the freemium decision point, while answering the questions, Can this product succeed as a freemium product? and, Is this team capable of implementing the freemium business model? is a more introspective exercise.

Scale

The potential for scale is essentially the conceptual foundation of the freemium business model. This isn’t to say that freemium products must achieve massive scale to succeed; freemium products can be profitable and considered successful at any number of user base sizes. But the characteristics of a product that facilitates massive scale must be in place for a freemium product to achieve the level of adoption required to generate more revenue than it would if it was executed with another business model. These characteristics are low marginal distribution and production costs.

A product’s marginal cost of distribution is the cost incurred in delivering an additional purchased unit to a customer. For physical products, these costs are often realized through shipping, storage, licensing, and retail fees, and they tend to decrease with increased volume through economics of scale; that is, the more products shipped, the lower the cost of marginal distribution.

Digital products are distributed through different channels and thus face different distribution cost structures. Often, the only costs associated with distributing a digital product are hosting expenses and platform fees. In aggregate, these costs can be substantial; at the marginal level, however, they are effectively $0.

Production costs are also structured differently for digital and physical goods. Physical goods are composed of materials that must be purchased before the product can be created; likewise, the production process represents an expense, as either a human or a machine must piece the product together from its source materials. Digital products incur no such per-unit production costs; they can be replicated for effectively no cost.

Low marginal distribution and production costs create the opportunity for a product to be adopted by a large number of people, quickly, at little to no expense on the developer’s part. This is a prerequisite condition for the freemium model; because its revenue stream is not necessarily contributed to by the entirety of the user base—that is, product use and payment for the product are not mutually inclusive—the product must have the potential to reach and be adopted by a larger number of people than if each user contributed revenue.

Freemium distribution is achieved most often through platforms, or commercial outlets that aggregate products and allow for their discovery through digital storefronts. Platforms provide value through retail functionality such as the ability to comment on products, rate them, and search for them based on keywords. Platforms generally charge a percentage of the revenue generated by the product; a common fee is 30 percent, meaning the platform takes 30 percent of all pre-tax product revenues.

Freemium products can also be distributed on the web with stand-alone websites. Obviously, such a distribution method incurs no platform fees—meaning the developer keeps all revenues it generates—but it also does not benefit from the infrastructure of a platform store (most notably, the ability to search). Web distribution may also be impractical or ineffective for some freemium products, especially mobile products for which installation from the web complicates the adoption process.

The freemium product development cycle may differ fundamentally from the development cycle for paid adoption products; freemium products are generally fluid and are therefore developed through an iterative method. Freemium products also often take the form of software-as-a-service or software-as-a-platform; as such, they evolve over time, based on user preferences and observable behaviors.

The costs incurred in continuous, post-launch development cycles do represent production costs: overhead expenses, such as employee salaries, are shouldered for as long as products are maintained and developed for, which may match the lifetime of the product. But, given low distribution costs and the freemium model’s potential for very broad reach, these costs, when distributed over a very large user base, can normalize to a level approaching $0 per unit. In other words, while a given development cycle represents a real and potentially large cash expenditure for a freemium developer, the size of the potential user base that product is capable of being exposed to reduces the marginal cost of production to an immaterial amount.

This dynamic imposes requirements on the total cost of production, however. Freemium products with limited appeal yet high development costs may face more substantial obstacles in reaching profitability than do products with broad appeal. Thus, the scale and scope of production costs should be constrained by the total potential size of the user base; certain product use cases may have limited intrinsic appeal, and the higher their costs of development, the higher the marginal costs of production.

While a non-zero marginal production cost doesn’t limit scale in the short term—products that can be distributed for free are still accessible by large numbers of people—it does limit scale in the long run by creating higher threshold requirements for product monetization. In other words, to fund its continued development, a product with niche appeal must capture higher levels of revenue per user than must a product with broad, universal appeal. If this revenue threshold can’t be achieved, the product will be shuttered.

Note that massive scale itself is not a condition of the freemium business model; products need not be large to be successful, especially if success is measured in profit relative to what could be expected from the product under the conditions of a different business model. Niche freemium products experiencing high levels of monetization from passionate, dedicated users can achieve success with modestly sized user bases. Similarly, no law of physics restricts to 5 percent the proportion of a user base that monetizes in a freemium product; this number could theoretically reach 100 percent. In practice, the proportion of users monetizing in freemium products is low—often extremely low—and preparing for such an outcome during the development process allows a developer to construct a revenue strategy that more prudently accommodates the realities of freemium monetization.

Thus the 5% rule is not, in fact, a rule; it is a design decision through which the developer embraces the practicalities of the freemium business model, which suggest that a small, dedicated minority of users can monetize to greater aggregate effect than can a larger population of users that has monetized universally through paid access. This design decision is an outgrowth of the freemium model scale requirement: the larger the total user base, the more meaningful will be the minority proportion of users who monetize.

Insight

A second cardinal component of the freemium model is insight, or a methodical, quantitative understanding of user behavior within the context of the product. Insight is achieved through a battery of tools and procedures designed to track the ways users interact with the product, and it is implemented with the goal of optimizing the product’s performance relative to some metric.

Insight is a broad term that roughly describes a freemium product’s entire data supply chain, from collection to analysis. Freemium product usage is instrumented through the use of data collection mechanisms that track the interactions between users and the product; this collected data can be aggregated, audited, and parsed to glean a valuable understanding of what users like and what changes could be made to the product to better serve users’ needs.

Insight is composed of two constituent parts that are equally integral to the entire process but require disparate skills to implement. The first part is data collection, or the means through which user interaction is tracked, stored, and made available to data consumers. (Data collection is typically done by the product’s developer, but sometimes it is done by the product users themselves). The technical infrastructure—the software and hardware components that accommodate data retrieval, storage, and end-user access—is often encapsulated with the broad term analytics.

The second part of insight is the work undertaken to make sense of the data collected and stored in order to improve the product. This work might take the form of regular reporting of key metrics or an analysis of a specific process or product feature in an attempt to understand its performance. These report templates and processes are usually described with the term business intelligence.

An important and frequently recurring type of analysis undertaken on freemium products is user segmentation, which aims to draw fault lines between the naturally occurring archetypes in the user base and then map the commonalities among them. Such an analysis is especially important in the freemium model, as user archetype groups may exhibit similar payment behavior and thus bring to light meaningful opportunities to optimize