September 15, 2017

Why Are Spotify’s Freemium Conversion Rates So High? Look To the Data.

The freemium business model has been popularized by companies like Spotify, the streaming music service, with a wide range of starry-eyed startups in search of similar success. Offering basic use of software for free, while holding back more robust features for paid users, is attractive to those hoping to build an instant customer base. The aim, of course, is that they evangelize the product and help pave the way for more users to adopt paid versions with richer functionality.

But when it comes to freemium conversion rates to premium subscribers, Spotify’s success has few peers. Boasting 140 million users, some 60 million are paid users, according to the company’s website. For most companies that leverage this business model, freemium conversion rates hover somewhere between 2 and 5 percent, according to Harvard Business Review.

How do we create products that are so irresistible that users will pay for richer functionality? When we pull back the curtains of product development at Spotify, we get a good glimpse of at least one reason behind those wildly successful conversion rates.

The agile product development methodology at Spotify has been well documented – with a focus on autonomy, and product development the responsibility of cross-functional “squads” of no more than eight people. According to another Harvard Business Review article, Spotify has an “experiment-friendly culture,” and if people don’t know the best way to do something, they’ll run A/B tests to figure it out. Above all, “in place of opinion, ego and authority, Spotify works hard to substitute data, experimentation and dialogue about root causes.”

Let’s read that again, with an emphasis on the “data” part. When you’re offering free access to your software – especially packaged software – the window into use is often closed after the user downloads the product. So how can you get that data?

By leveraging software usage analytics, you can gain insight into user behavior after download that will better inform product development, outreach, and continued innovation to boost freemium conversion rates to premium. Let’s take a look at three common roadblocks from freemium to premium that can be remedied by knowing more about product usage.

Users download the application, and then my team is met with radio silence

Even when a customer buys the software outright, one of the biggest challenges product managers face is getting actionable feedback from them. When it comes to products they’re not paying for, efforts by everyone involved in the spectrum of product development and release – every email, every call, every survey – is much more likely to be ignored. Usage intelligence allows you to monitor runtime sessions, feature usage and more, with the capability to look at that data through a number of different lenses.

Starting with the foundation of how users currently leverage your freemium features lends you valuable insight that will help you solve issues with free features that may be hindering the adoption of paid ones. For instance, perhaps users on certain operating systems or with other unique machine attributes are running into problems launching the software before they even use it. When you fix issues with, say, a configuration wizard, users start off their experience with your software on the right foot and are much more likely to continue to explore how it could deliver additional value.

Users don’t know about and/or understand the value of the paid features

Despite countless, carefully crafted marketing campaigns, YouTube videos, customer tours, and dollars shelled out for trade shows, you still aren’t seeing freemium conversion rates to paid versions climb.

Chances are, even after all of that, your most actionable leads don’t know about the best features of your product. By understanding how they’re using the free version – down to the length of time they spent with each piece of functionality in runtime sessions – you gain insight that will tell you where they’re running into problems and where they’re spending most of their time – with the ability to slice and dice that data by the types of machines, memory capacity, regions, versions, editions and operating system.

With detailed information on how they’re using the product, you can target them with thoughtful, relevant messaging on how some of the paid features will help them better accomplish their jobs.  Combine that data with in-app messaging capabilities, and you have the ability to reach users when they’re most likely to respond to your offers – while they’re engaged with your product.

Customers download your product to meet immediate business needs, then export their project to another application

We’re all familiar with this cycle – in which prospects download and use the free software, then uninstall the software and sign up for a new free account when they have another business need.

Sometimes, perpetual freeloaders just need a little push to get them onto paid versions. Leveraging usage intelligence can help you decide when it makes good business sense to make users pay for a feature or service that is currently free. For instance, with data uncovered through usage intelligence, one of our customers, a software company, decided to add a watermark to its projects that could only be removed after a trial user purchased a full license. The company saw a substantial increase in conversions representing users who believed they were generating enough value from the software to pay for it.

By leveraging usage intelligence, you gain insight that will better help you develop your freemium and paid features that make your entire platform irresistible to users. Usage intelligence helps you spot problems – and opportunities – early in the product development and use lifecycle for optimal freemium conversion strategies.

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Keith Fenech

Post written by Keith Fenech

Keith is Revulytics’ VP, Software Analytics and was the co-founder and CEO of Trackerbird Software Analytics before the company was acquired by Revulytics in 2016. Following the acquisition, Keith joined the Revulytics team and is now responsible for the strategic direction and growth of the Usage Analytics business within the company. Prior to founding Trackerbird, Keith held senior product roles at GFI Software where he was responsible for the product roadmap and revenue growth for various security products in the company's portfolio. Keith also brings with him 10 years of IT consultancy experience in the SMB space. Keith has a Masters in Computer Science from the University of Malta, specializing in high performance computing.

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