With over 150 million users across 185 countries, Strava is one of the world’s largest digital communities for active people. It is the place where professional cyclists and weekend joggers alike go to hunt for Kudos, battle for King of the Mountain titles, and share their latest Strava Art.
In 2025, Strava reached a valuation of $2.2 billion in a funding round led by Sequoia Capital. With nearly $500 million in annual recurring revenue, Strava is the top unicorn of the fitness world.
Creating a Localization Strategy for 2 Products: Strava and Runna
When Eduardo D’Antonio, Globalization Director at Strava, set out to build a modern globalization tech stack, the stakes were high. Strava had just acquired Runna, a UK-based personalized coaching app. The mission was clear: localize Runna into seven key markets (including Dutch, French, German, Italian, Japanese, Portuguese, and Spanish) in under six weeks.
Traditional translation management systems often require months of implementation. For a high-growth unicorn like Strava, waiting six to nine months for a setup was not an option. They needed a solution that offered deep automation, a vast library of integrations, and a pricing model that scaled with their 35-million-word volume.
Why did Strava Choose Crowdin?
Eduardo evaluated the leading TMS platforms on the market but found many were too expensive, too slow to implement, or lacked the technical flexibility Strava required.
Strava chose Crowdin as the center of their localization architecture because it offered:
- Integrations (The #1 Priority): Strava needed to connect over 25 different content repositories across their ecosystem.
- Implementation Speed: While competitors quoted 6-9 months for setup, Strava didn’t have that time.
- Cost: Strava needed an affordable, scalable solution.
- Customization & Support: They needed a partner, not just a vendor, someone who would listen to feature requests and adapt as quickly as Strava does.
To meet the aggressive six-week deadline, Strava implemented an AI-driven strategy. By combining NMT and LLMs via Crowdin, the team managed to maintain quality while reducing time-to-market.
Results
Beyond the technical setup, the strategy of using Crowdin as the central hub and connectors to Figma, GitHub, Contentful, Intercom, Iterable, Kevel, Strapi, and Intento + DeepL for MT translation allowed Runna to go global in record time. It was successfully localized into Dutch, French, German, Italian, Japanese, Portuguese, and Spanish. By using NMT and LLMs via Crowdin, Strava can now translate faster, better, and cheaper.
As Dom Maskel, CEO of Runna, noted in Forbes, “Strava’s experience in localization helped us bring this all to life and their support has been instrumental in bringing this update to market at pace and at scale.”
“This means millions more runners worldwide can fully experience what we’ve built. This is about more than translation: it’s about inclusivity, accessibility and global ambition to make running more accessible, effective and enjoyable for everyone,” he continued.
“None of this would have happened without Crowdin,” says Eduardo, Globalization Director at Strava. “I think that’s the most powerful sentence I could tell you.”
Key Takeaways
- If your TMS does not integrate with your tech stack, you are not truly automating.
- Speed is a competitive advantage. In the tech world, being first to a new market can define brand loyalty for years.
- Customization and support are the silent pillars of a six-week launch. Strava required a partner willing to listen to feature requests and adapt as quickly as their own engineering team.
