Preply, an online language learning startup based in Ukraine, has raised a $10 million Series A amid a surge in demand for its platform.
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The financing brings Preply’s total raised since its inception in 2013 to $15.6 million, nearly doubling its previous investment total, according to Crunchbase data. Preply uses machine learning and artificial intelligence to match tutors and language learners.
This news caught our attention for a couple of reasons. For one, its diverse investor base. London-based Hoxton Ventures led the round, which included participation from Berlin’s Point Nine Capital, All Iron Ventures out of Spain, Paris-based firms The Family and EduCapital, and Diligent Capital in Ukraine. Notably, in a growing trend of startup founders and executives backing other companies, a number of individual angel investors also put money in the round: Arthur Kosten, co-founder of Booking.com; Gary Swart, former CEO of Upwork; David Helgason, founder of Unity Technologies; and Daniel Hoffer, co-founder of Couchsurfing.
This news is also interesting in that Preply raised this money prior to seeing a major spike in its growth over the past few weeks as people are forced to stay at home in the face of the COVID-19 pandemic.
Prior to this month, Preply had a network of tens of thousands of learners with 10,000 verified tutors teaching more than 50 languages around the world. Globally, the company saw the number of hours of tutoring purchases on its platform spike by 50 percent in recent weeks compared to the third week in February.
Growth nearly tripled in Italy, almost doubled in Spain and was up by 130 percent in France. The startup also saw the number of tutors registered on its platform surge by 80 percent globally compared to the third week in February. The number of tutors in the U.S. and Italy more than doubled, almost tripled in Germany and were up by 140 percent in Spain.
Preply plans to use its new capital to expand its global presence with an eye toward opening an office in the United States later this year. It also intends to grow its network of tutors.
The company currently has 125 employees (spanning 25 nationalities) in Kyiv and Barcelona. Preply says its revenue has grown by ten times in the last three years. The majority of its users are people needing to learn another language because they are moving abroad for work, for example. Others use it recreationally. Over time, 2 million courses have been taken via its platform.
With a plan to hire more than 100 people over the next 12 months in Barcelona, particularly in its product, engineering and marketing departments, the company says it’s also actively looking for “senior talent.”
Preply credits its flexibility and targeted matching for its success. It claims to make it easy to find a tutor at a variety of times throughout the day for an affordable price, which averages $15 to $20 per hour. Students enter their bank account details when they register and tutors can take money out of their Preply account immediately after providing a lesson.
The recent funding is planned to be used to roll out new tools, assessments and homework as well as to develop the company’s mobile offering.
Ukrainian based co-founders Kirill Bigai, Dmytro Voloshyn and Serge Lukyanovhad started Preply while on their own personal journeys to learn English. Bigai, now CEO, found an online tutor in 2012 when he started classes with a Texas-based teacher via Skype from his home in Kyiv. He described the experience as “game-changing,” and realized the potential of expanding online tutoring on a global scale.
The company says it is different from other players in the market such as Duolingo and Babbel in that it believes “live engagement with a teacher is still the most effective way to learn a new skill.”
Over the past six months, Preply has focused on developing a proprietary learning strategy that incorporates a mix of human-to-human interaction and self-guided learning activities in an effort to maximize tutor and student effectiveness.
As mentioned above, the company also believes it’s unique in the way it pairs learners with tutors. It uses a machine learning algorithm to increase matching efficiency between learners and tutors on a variety of parameters, which includes subjects, native language, time zones and learning goals. From there, students can select their preferred tutor.
Blog Roll Illustration: Li-Anne Dias
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