Three freemium strategies

I'm excited to see so much attention being paid to freemium businesses lately. These are companies that generate revenue by offering a free product with an upsell or premium version. Their economics blends elements of the free, advertising-supported, "eyeballs" business with more traditional e-commerce and subscription businesses. For founders, I think it also has another big attraction: the ability to avoid a lot of "free vs paid" arguments. You can reach for all the scale of a free service and still make money. Pretty good deal, right?

Andrew Chen recently did a great article on the economic model underlying freemium (it includes a detailed spreadsheet, too!). In it, he mentions the core dilemma that all freemium companies face:
the key is to create the right mix of features to segment out the people who are willing to pay, but without alienating the users who make up your free audience. Do it right, and your conversion rates might be as high as 20%. Do it wrong, and your LTV gets very close to zero. This is why premium features have to be built into the core of a freemium business, rather than added in at the end. You want to be right at the balance between free and ‘mium!
Having worked in the freemium business for a number of years, I can safely report that struggling with these questions never goes away. I have sat in hundreds of meetings about what to give away and what to charge for, and they are not easy. Things get a lot worse when we don't have a coherent model of why we're using freemium in the first place. This is a common outcome I've observed among founding teams that take the "split the difference" route to freemium.

The way to resolve this tension is to agree on a fundamental freemium strategy, that leverages the free part of your business to add real value. In my experience, there are three basic choices:
  1. Free serves paid. In this model, your free users trade their time for the benefit of your paying customers. For example, Puzzle Pirates does a great job of allowing trading between two different currencies: one that is earned with time, and another that is earned by paying. Both currencies are valuable, and free users can trade theirs to the paying customers, who are allowed to access benefits that would otherwise take a long time to achieve. Other examples are user-generated content sites, where free users create content that is valuable to paying customers. The key to this model is to make sure that customers who create value are heavily rewarded, and those that don't create value are marginalized, so that they have a strong incentive to pay.

  2. Free trial. The original freemium model, where customers are given a certain amount of time before being forced to either quit the service or pay. The big question is when to pull the plug - too soon, and you risk customers not being sufficiently addicted to say yes; too late and you risk giving all the value away for free. Luckily, once you realize you are in this business, you can answer these questions empirically with good split-testing and linear optimization.

  3. Free as inventory. Some businesses actually sell access to their free users. I think this is the right way to think about many advertising businesses, like Google AdWords. Some dating sites work this way too, where you can post your profile for free, and people pay only when they want to contact you. This ensures that the most popular people get lots of value without having to pay. Here the key is for your free customers to get value from the site that is greater than the costs they perceive by the fact that you're selling access to them. Google has shown their awareness of this issue by carefully managing the annoyance-factor of ads that are shown during search. What differentiates this model from "free serves paid" is that the free users don't need to consciously do anything special to be valuable. For network-effects businesses, like Skype, just being on the network is enough to create value.
Strategy is all about what you're not going to do; for a freemium business, it's about which users you're willing to turn away. Knowing which model you're in can make these decisions a little less excruciating. It's not that you shouldn't experiment - on the contrary, this is one of the most fundamental hypotheses you want to test early on. However, it's not very useful to mix and match features from different models. Better to set up complete experiments that are themselves internally coherent. Take a cohort of new customers and expose them to a completely different approach, and measure their behavior over time. Use that data to make an informed choice about whether you want to change strategies.

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