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This microbook is a summary/original review based on the book: Freemium Economics: Leveraging Analytics and User Segmentation to Drive Revenue
Available for: Read online, read in our mobile apps for iPhone/Android and send in PDF/EPUB/MOBI to Amazon Kindle.
Publisher: Morgan Kaufmann
Also available in audiobook
You probably use countless freemium products in your daily life. Skype, Spotify, and Candy Crush are just some examples. But how exactly do you build a freemium product that lasts, and how can you generate money with it? In “Freemium Economics,” Eric Benjamin Seufert provides a how-to guide on how to build digital freemium products. The most important part of your freemium journey does not happen during the conceptualization of your product, but after the launch: the user data you can gather on your freemium product is paramount to its success. So, get ready to learn how to navigate the waters of freemium economics!
What is the freemium business model? Basically, it means giving a product away for free. This is done in an environment with no or low marginal distribution and production costs, which holds the potential for growth on a massive scale. Freemium products offer all the product’s basic functionality for free, but advanced functionality, premium access or other product-specific advantages are paid for.
Spotify, Skype, and Candy Crush are all examples of freemium products. Let’s look at Skype as an example of how freemium products can work in real life and generate value for the customer, as well as income for the creators.
Skype allows you to make phone and video calls via the internet. In 2014, this mostly free product was used by more than 600 million people. Skype was developed in 2003 and its first beta version for Windows allowed people to make phone calls using their computers’ microphones and speaker phones. Skype was built without central servers, instead, calls were routed through a network established between the users. Therefore, the larger the Skype network grew, the more stable the connection grew.
Skype therefore also became extremely popular in areas with a low population density, as these areas were often not served adequately by cellular networks. Skype’s initial monetization approach was to allow people to make calls to traditional phone networks with SkypeOut. But as Skype grew in popularity - and especially with the introduction of smartphones - SkypeOut became obsolete.
Eventually, Skype got a new CEO, Tony Bates. He realized his vision for Skype by making it a business telecommunications solution. He introduced video group calls for Skype Premium customers. In 2011, Skype was acquired by Microsoft for $8.5 billion. Even when Skype had faced financial difficulties, it always managed to make a revenue, since its customer base had grown exponentially fast.
How can you create a freemium model like the one used by Skype? A freemium model works because it is created with the aim of getting your product distributed to a large group of customers. By offering a product for free, many people will decide to try it out. You need to be aware, however, that most of your customers will only ever use the free version.
The premium, or paid-for version, will only be taken up by a small number of extremely engaged customers. On the upside, this means that the people who buy your premium version will likely spend more money on it than they would otherwise have if you had sold your product for a set fee. The author calls this the 5% rule: of all the people who will use your product, likely only 5% can be expected to monetize prior to product launch.
This means you want your product to appeal to as many people as possible, in order to maximize its use, case, or purpose. The author writes, “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.” The larger your customer base, the larger your 5% group, and the more money you make.
A successful freemium product is based on four components: scale, insight, monetization, and optimization. You need a product that can potentially generate massive scale, which means you need low marginal distribution and production costs. Since freemium products are mostly digital, your marginal distribution costs are close to zero – you usually incur no extra costs to deliver a product to the customer. To get your product distributed, the use of platforms is recommended, as these allow you to reach a large number of customers quickly.
Insight, according to Seufert, means having a “methodical, quantitative understanding of user behavior within the context of the product.” You need to collect analytical data to understand your customers and to adjust your product accordingly.
Monetization is the nucleus of your freemium experience, around which all other product features are grouped. For optimal monetization, create a large product catalogue with options to personalize that customers can choose from. Think about the most individual user needs and build your catalogue from there. Since you are offering a digital product, offering a wide range of options is not going to cost you extra – but it will convince your users that you provide a product of high quality.
Finally, optimization: the user experience can only be optimized once you have collected some data from your users. This is why a common model for a freemium product would look like this; a develop-release-measure-iterate feedback loop.
Gathering data on your users is essential if you want your freemium product to succeed. So how do you go about this? You need to collect minimum viable metrics (MVM) from your customer, which Seufert defines as “tracking a minimum set of metrics needed to optimize development in pursuit of greater user engagement.” The behavioral data you collect needs to be diversified enough so you can make informed product development decisions based on this data.
You will be relying on large data sets, which can only be analyzed programmatically. These data sets can be broken up into four categories: retention, engagement, monetization, and virality.
Retention means measuring the product use for a specific day in retrospective. If you break these values up and display them for day one, day three, day seven, and day 14, you can gain valuable insights into how many users return to your product after a first contact, and how many customers you have retained after two weeks.
If you use your retention metrics cleverly, you can see how frequently and for how long customers use your product. If you graph these, you can get a visual funnel of your average use case. With this data set, you can then estimate user lifetime.
Measuring monetization is less important than gathering data on retention, as in order to make money you need to first focus on building and maintaining a user base. The author writes, “Monetization metrics communicate not only volume of revenue but also crucial shifts in spending patterns over time and the degree to which the freemium model is being leveraged to produce highly monetizing users.”
You can also use monetization data to illustrate conversion rates. This is not as straightforward as you might think, as freemium business models gain revenue from two sources: advertising and through purchases the customer makes. Seufert believes that in order to gain accurate data on conversion rates, you should concentrate solely on purchases made by customers.
Advertising in general can be a highly controversial topic in freemium economics. You should only use it if it does not affect your product’s ability to monetize highly engaged users in any way. Think about it: many potential highly engaged users could become alienated if they are frequently shown advertisements. It can also turn away your NPUs (non-paying users).
And you need NPUs to be successful in the freemium world. Even though they might not directly make you money, they do so by indirectly becoming your product ambassadors. By spreading the word about your product, they will likely attract those highly engaged users that you need for your business to be profitable.
You should also gather data on engagement, which captures user behaviors in relation to product interaction. Your highest ambition should be to achieve consistent, daily use. To do so, you will need to collect data on your users’ session frequencies and lengths.
The first session with your product is the most critical in determining a user’s lifetime with it. With every freemium product, it can be expected that some users will drop out within the first session. Your job is to keep the user fall-off percentage as low as possible.
Your onboarding period can be an explicit sequence of events within the first interaction session, or it can be subtly implemented over several sessions. Your goal here is to make the user familiar with your product and give him the necessary information to use it. This, of course, depends on the compatibility between the user’s needs and your product.
If you choose an aggressive onboarding process, you will quickly alert users whose needs do not meet your product. This means you will lose more customers in the early stages. However, the alternative would be to alienate these users further down the line, which could potentially result in negative publicity for your product.
Users engaged with your product are potential sources of virality, and this is the last area you should collect data on. According to Seufert, virality “describes the extent to which products are distributed without any active marketing participation from a business.” You cannot predict virality as it is largely serendipitous. However, you can increase the chances of your product gaining traction by including “virality hooks.”
Virality hooks, according to Seufert, are “mechanics or product features that connect to a third-party API and can broadcast an aspect of the user’s activity.” Most commonly, these are implemented through social networks. Some freemium games on Facebook, for example, generate automatic messages and notifications that are sent to the user’s social network. Usually, these do more harm than good because they lack personalization. They can even alienate current users as the freemium product abuses its permission to access the user’s social network.
In any case, it is difficult to track virality. Deep virality hooks allow for tracking, as these can take the form of web-hosted social layers in an app, which would allow the user to send out invitations to friends via email. Obviously, such a personalized method would reach fewer people, but would likely also result in a higher conversion rate. Additionally, they also allow you to gather data on the virality of your product.
Whatever you do, build a product that encourages virality through auditability and effectiveness, but rely on assumptions of normal growth levels in your financial projections pre-launch.
In order for your freemium product to take off, you will need to put a strong analytical framework in place. Create a product that appeals to a broad customer base, and track the retention, monetization, engagement, and virality of your product. The data you gather should be used to optimize your product along the way. If you do it right, you will quickly build a large customer base, of which around 5% will convert to regular, paying customers. The larger your customer base, the more money you will make.
Think about what kind of virality hooks you could add to your product.
Eric Benjamin Seufert is an American quantitative marketer. He specializes in predictive forecasting of freemium products as well as programmatic statistical methods. After graduating from University... (Read more)
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