Freemium business models seem to be gaining in popularity and rapidly becoming a dominant factor in the success of Web startups. Massively successful social-gaming companies like Zynga and Playdom have had a role in driving their adoption. These companies have been able to grow quickly and make substantial revenues through a combination of ad sales and charging small amounts of money for additional game items and features.
Freemium is a business model that provides users with free access to a service’s core functionality, but charges for additional or improved features. In social gaming, this often takes the form of letting players purchase special, limited-edition virtual goods using an in-game, virtual currency. Other Web services allow users to purchase a premium user experience. For example, Pandora lets users listen to music without ads. In each of these cases, there are opportunities to enhance the appeal of premium services.
In this month’s column, we’ll discuss methods of getting the most out of the freemium model and maximizing the likelihood that users of basic, free services will start paying for premium features.
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Baiting the Hook
In discussing the freemium model, it’s useful to examine why social-gaming companies are having such huge success with it in more detail. Just about all of these companies offer limited, free access to premium features—essentially, free samples. Plus, most social games allow players to purchase premium features using some type of specialized currency. This currency might, for example, take the form of a free Mafia Wars reward point or some FarmVille farm cash. Using a game’s special currency, users can purchase features or items that enhance their gaming experience.
Users get to sample the premium features for free, enticing them to make larger purchases so they can get some special item or feature that is just out of their reach. In a context outside the social-gaming realm, this would involve somehow giving users a taste of the premium features, but not enough for them to get everything they would want.
Applying this concept to the Pandora example, where the premium feature is the absence of ads, a free sample would be occasionally allowing users to skip a commercial and get right back to listening to music. If you are employing a freemium model that relies on restricting access in some way—such as the HuluPlus service, which provides access to restricted content—you would occasionally provide free access to some restricted shows. Once users get started by viewing the first episode of a compelling show—like House or Mad Men, for example—they are much more likely to want to continue viewing the show.
Schedules of Reinforcement
Psychology guru B.F. Skinner spent his entire career analyzing how reinforcement schedules affect human behavior. Among the principles of behavioral psychology, schedules of reinforcement are very well established and supported by a great deal of empirical research. His ideas can provide useful guidance for the application of the freemium model
But, before we delve into how reinforcement schedules can apply to freemium models, it’s important to first understand reinforcement, which Skinner described as a behavioral consequence that increases the likelihood of the same behavior’s occurring in the future. The logic of reinforcement is fairly simple, if a person takes an action that results in a positive response, the person is likely to take that action again in the future. For example, if a person tells a joke and people laugh at the joke, that person is more likely to tell other jokes. Over a lifetime of joke-telling, the person may get some laughs and some groans, but if he gets more laughs than groans, he’ll likely continue telling jokes and think of himself as a person with a good sense of humor.
There are four basic schedules of reinforcement:
Fixed-ratio schedules provide a positive reinforcer after a set number of actions. For example, every time a salesperson completes a sale, he or she receives a commission.
Fixed-interval schedules provide a positive reinforcer after a set period of time has passed. For example, an employee might receive a paycheck every two weeks.
Variable-interval schedules provide a positive reinforcer after a random period of time has passed. For example, listening to the radio and, after a random period of time, hearing your favorite song play.
Variable-ratio schedules provide a positive reinforcer after a random number of actions have occurred. Casino slot machines—whose winning combinations occur after a player has put money in a machine a random number of times—provide a classic example of this type of reinforcement.
Study has revealed some common themes among reinforcement schedules. First, ratio schedules are more powerful than interval schedules. This is likely because, with ratio schedules, there is a close association between an action and its reinforcer, while interval ratios are not linked to taking action. Also, variable schedules tend to be more powerful than fixed schedules. This is probably because the reinforcer occurs at unexpected times, increasing their psychological and emotional impact. Given these phenomena, variable-ratio reinforcement schedules—as in the case of slot machines—are far and away the most powerful and are associated with the establishment of very powerful and stable behavior sets, while fixed-interval schedules are the weakest—as for a biweekly payroll.
Thus, these reinforcement schedules offer some extremely useful guidance for the application of the freemium model. Zynga employs a variety of different reinforcement schedules simultaneously. Users receive rewards for logging in each day—a fixed-interval schedule. They receive premium currency each time they gain a level in a game—a fixed-ratio schedule. In Mafia Wars, there is even an in-game slot machine that provides rewards on a variable-ratio schedule. Zynga has had a great deal of success with these strategies. By designing a freemium model around powerful reinforcement schedules, you can dramatically increase the likelihood that a user will purchase your premium features.
Potential Pitfalls
There are some important things to consider when determining the best means of implementing these kinds of freemium strategies. First, it’s essential that a free sample of premium features provides real value. If it does not, users will not respond, because the free sample doesn’t really function as a reinforcer. At the same time, it’s important that the free sample doesn’t completely fulfill their needs. In the words of Walt Disney, “Always leave them wanting more.”
Second, it’s essential to choose an appropriate reinforcement schedule. For example, if your Web site doesn’t lend itself to users’ actively engaging with it—as might be the case for a news site—it doesn’t make sense to use a ratio schedule, so don’t try to force it. Instead, look at the best ways of employing an interval schedule. But don’t discount fixed schedules; they provide very useful ways of emphasizing the value of your service.
Finally, ensure that the frequency at which reinforcement occurs does not frustrate your users. For variable-interval and variable-ratio schedules, the reinforcer occurs after a random amount of time has elapsed or a random number of actions have taken place. It’s usually advisable to place an upper limit on that random interval or number of actions, to ensure users’ actions do not too consistently remain unreinforced. For fixed schedules, be sure that the interval or rate is appropriate. If users must wait too long between reinforcers, they may not develop an appreciation for your premium service.
If you don’t devise an appropriate reinforcement schedule, these strategies could backfire and actually turn users off, so it’s important to get them right from the beginning. The best way to address each of these factors is through user research that identifies the appropriate sample features and items, reinforcement schedules, intervals, and ratios.
Conclusion
These reinforcement-schedule strategies offer a very effective way of getting the most out of the freemium model and increasing the likelihood that users will purchase premium features. Once users have an appreciation of the value of your site’s premium features, they are more likely to make a purchase—as long as the enhanced service provides some real value to them. To deliver value, you’ll need to identify an appropriate free sample, determine the best interval at which to offer the free sample, and determine the optimal frequency of reinforcement.
In employing these strategies, keep in mind that they are not a means of manipulating your users. If users do not find your premium service to be worth purchasing, these strategies will not be effective. To employ these strategies successfully, think of them as a way to emphasize and showcase your premium service, really letting users know what they will be getting for their money.
Co-Founder and VP of Research & Product Development at Metric Lab
Redwood City, California, USA
Demetrius truly believes in the power of user research—when it is done well. With a background in experimental psychology, Demetrius performed research within a university setting, as well as at NASA Ames Research Center before co-founding Metric Lab with long-time collaborator, Bryan McClain. At Metric Lab, Demetrius enjoys innovating powerful user research methods and working on exciting projects—ranging from consumer electronics with companies like Microsoft and Kodak to modernization efforts with the U.S. Army. Demetrius is constantly thinking of new methods and tools to make user research faster, less costly, and more accurate. His training in advanced communication helps him to understand and connect with users, tapping into the experience that lies beneath the surface. Read More
Strategic UX Adviser & Head of Business Development at 30sec.io
Redwood City, California, USA
Bryan is passionate about connecting with people and understanding their experiences and perspectives. Bryan co-founded Metric Lab with Demetrius Madrigal after doing research at NASA Ames Research Center for five years. While at NASA, Bryan worked on a variety of research studies, encompassing communication and human factors and interacting with hundreds of participants. As a part of his background in communication research, he received extensive training in communication methods, including certification-level training in police hostage negotiation. Bryan uses his extensive training in advanced communication methods in UX research to help ensure maximum accuracy and detail in user feedback. Bryan enjoys innovating user research methods that integrate communication skills, working with such companies as eBay, Kodak, Microsoft, and BAE Systems. Read More
