Zwift, which turns indoor cycling workouts into multiplayer games, raises $120M

Fitness and gaming have been two of the most popular categories of apps for years, and now a startup founded out of London that has combined the two in a unique way has picked up a big round of funding to capitalise on that. Zwift, an interactive platform for people to turn indoor cycling workouts into massive, multi-participant races, social rides, and immersive explorations of new domains, has raised $120 million — money that its co-founder and CEO, Eric Min, said will be used to expand to more training categories (its first steps outside of cycling have been into running), and to add esports tournaments.

The funding — led by Highland Europe, with Europe’s True (not to be confused with True Ventures), Causeway Media and Novator participating — comes on the heels of very rapid growth for Zwift .

The startup now has over 1 million registered accounts (it doesn’t disclose active users), up from a mere 200,000 two years ago, with users ranging from amateur cycling enthusiasts, people who cycle as part of fitness regimes, and professional athletes who use it to supplement IRL global training schedules.

“More than one-third of the peloton in this year’s Tour de France” — despite all its controversies, still the gold standard for road races — “are users of Zwift,” Min told me. There are 200 Facebook groups built around Zwift communities, with people using them to organise rides and sometimes even to meet up in person afterwards at cafes, just as they might in actual outdoor rides. With customers in 100 countries, Min told me that there are on average 300 organised (group) rides a day happening on Zwift.

The company isn’t disclosing its valuation, but Min said that the startup is “approaching unicorn status” on account of its growth and big ambitions and it appears to be more than $500 million with “a very small dilution” — a big jump on the $180 million Pitchbook estimated its valuation to be in 2016 (it’s raised around $166 million to date).

Min believes that the upswing in e-sports could see the format getting ever-more mainstream acceptance. “Our goal is to bring Zwift to the Olympics,” he told me confidently.

Zwift is swiftly addressing two different shortcomings of two common home pastimes. One of the problems with exercising at home — and specifically training in cycling as a first effort — is that it might get a little boring, and one of the problems with playing too many video games is that they contribute to the tendency we have in our modern world to be too sedentary.

The service involves you providing your own bike, which you link up with a Zwift trainer (a rack-like piece of equipment that turns a bike into a stationary bike for indoor training), which in turn picks up your stats and adjusts tension and so on based on the course that you are riding. You cycle in front of a TV typically to get the immersive effect, linked up to a Mac, Windows or iOS App (it’s also on Apple TV). You start with a free trial before moving to a monthly fee of $15 (or $10 if you are currently on a trial or already subscribe: the higher fee was introduced last month).

There are no plans at the moment for VR headsets or other head-based wearables because so far they have proven to be too bulky to be usable in the physical environment of sometimes-gruelling cycling, Min said. And for now, you also don’t use spinners or other stationary cycling apparatuses because these can’t provide the right kind of ‘real-world’ riding feel, he said. But this might evolve as Zwift partners with more third parties (and with companies like Peloton a big hit with home fitness enthusiasts, you can see how that might evolve).

In all of its sports and sport ambitions, Zwift is bringing not just basic tension and gaming dynamics to the table: it’s using some interesting algorithms to help train its users, and figure out what might be the best logical step for them in terms of increasing or decreasing difficulty while measuring all other cycling stats. Min says this all starts with getting an accurate weight for each user.

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