What are the biggest challenges when building a truly global product?

In our case, it wasn't localisation in terms of language.

It was predominantly finding different paths and customising to people's mindset (it usually affected the pricing), and also differently crafted creative (you had to literally work with different concepts and tone of voice).

We believe the biggest challenge lies in localization. While our product supports multiple languages, apart from English and Chinese, all other languages rely on AI translations. To be honest, this doesn't look great, as AI-generated localization is far from perfect, and we currently lack the resources to proofread every language. We hope to address this issue in the future when we have more revenue.

Additionally, our product is designed for the web platform, and our UI has been developed with multi-language adaptability in mind, such as automatically adjusting container lengths to accommodate language switching.

I think localization is not only about translation, but also about the inequality of the global technological infrastructure. This can be found on the internet:

① Indian users often use apps with unstable internet connections and need strong offline capabilities.

② The African market is dominated by low- and mid-range Android devices, where memory optimization is critical.

③ Japanese and Korean users have a very low tolerance for page load times, about 40% lower than Western standards.

Regarding your mention of AI bias towards English. The solution may not only be technical, but require a fundamental rethinking of the design process:

① Consider fine-tuning with region-specific models rather than a single global model.

②Build multicultural development teams - I think this is much more effective than translating after the fact.

③ Adapt language switching in design - for example, consider separating code output from interpretation, allowing code to remain in English and interpretation to be in the local language.

Finally, have you considered adopting an “incremental globalization” strategy, first validating in culturally similar markets and then expanding outward?🤔

What’s your biggest frustration when using "global" tools that are clearly built with English-first assumptions?

I'm only annoyed when I have to learn that a product isn't working with non-English input. I've encountered problems with the decimal point and thousands separators for numbers or text input only accepting US-ASCII letters even for things like names. All other things, I can tolerate.

As a maker, I concentrate on making the app work no matter what language etc. is used, while leaving the language in English. For a solo dev (or a small team) I think our time is best spent on features, focussing only on real obstacles for non-English users.

What a fantastic discussion—thanks for kicking this off, @yeedoong88!

In my experience, I’ve run headfirst into a lot of these pain points.

Localization isn’t just swapping words—it’s about nailing cultural nuances, payment methods, and support expectations.

And the “AI loves English” issue? So real. Even when you offer multiple language options, the AI often defaults to English for clarity, leaving non-English speakers feeling like economy-class 🤯.

My biggest pain point: tools that tout “global” capabilities but still center on English-first UX or only support key markets. It’s not enough to translate the UI—true global products anticipate local workflows, time zones for notifications, and even regional compliance quirks from day one.

I’m excited to hear how others have built scalable, genuinely multilingual experiences. What tactics have you used to make every user—no matter their language or location—feel like your product was built just for them? 🤔

I'm curious to know. Is there a particular reason why you are trying to go global right off the bat?

Are there any tools or products worth recommending for solving globalization/localization challenges?

Absolutely agree with you.

I am also working on a multilanguage tool, and yeah, it is kinda annoying when AI suddenly switches to english.

Legalities and time zones not really made sense to me at first either still getting used to

I'm building a website & community builder called Slashpage, and I realized that users find it difficult to support multiple languages. I started offering multilingual support pretty early on.

When launching a global product, do you think it's more effective to focus on a specific region first? Or is it better to go with an English-first launch to reach a wider audience?

I used to be an engineer at Facebook working on a product used in developing nations like India, Brazil, etc.

It's really hard to know what is going to resonate. Even though I went on research trips to India and Brazil, I was still surprised by which product framing performed best.

Also, you need to interpret signals differently. Indian users engage with social media content way more than Americans, for example.

Plus what others have said: Translations. Right-to-left languages. Etc.

This is a super insightful list, Yee Doong. On the 'unexpected challenges' front, I find the dilemma of 'where to start' particularly tricky for a global product.

You have this expansive vision, but the practical advice is always to nail a very specific ICP and perhaps even a specific region first.

How do you reconcile that almost paradoxical advice? It feels like a critical, yet sometimes underestimated, hurdle to get that initial traction in a way that doesn't limit future global pathways.

For us, localization was the biggest challenge. The problem with most translation APIs is that they have strict word limits, and the pricing beyond those limits becomes extremely expensive. Since our platform is mainly content- and text-based, this would’ve led to very high costs, making it not worth it for us.

On top of that, based on our in-depth research, we found there’s a risk of being penalized by Google if the localized content is too similar to the original version. So, considering both the cost and SEO risks, we decided to skip localization and focus our efforts elsewhere.

Recently, we launched our Korean service globally. In Korea, teenage girls were the primary users, but in the global market, the user demographic has shifted to those in their twenties and older.

With this change in our main customer base, updating our marketing and content has been added to my to-do list. It's unfortunate that we can't share results yet, as it's been less than a month since the global launch, but I will share again once we have more data.

Totally agree—building global products is so much more than just translation. I’ve seen the same issue with AI defaulting to English, especially for technical stuff. We’ve tried language settings and context prompts, but it’s still tricky.

How have you handled cultural differences beyond language, like UI or interaction style? And what about feedback from users in less common languages?

Thanks for bringing this up—definitely one of the toughest challenges in scaling AI!

Personally, as a non-native English speaker, my biggest frustration is when global products ignore local usage habits. For instance, address forms that don’t support my country’s format, or date/time pickers that only use the US style. These small details add up and make the product feel foreign.

Hi Yee Doong, thanks for sharing these insightful challenges! Building a truly global product definitely goes beyond just translation—cultural nuances and local user expectations make a huge difference. I completely agree on the AI language issue; getting models to respond naturally in users’ native languages, especially for technical topics, is a tough balancing act. For language fallback, we’ve found that allowing users to explicitly set their preferred language and offering seamless switching helps a lot. Also, investing in regional user research early on can uncover unexpected pain points, especially around legal compliance and UX design for different scripts or reading directions. One unexpected challenge we faced was handling payment methods that vary widely by country—something easily overlooked but critical for conversion. Looking forward to hearing how others tackle these complexities!

Absolutely resonate with your points! 🌍 As someone who's worked on multilingual AI products, I totally get the struggle. The English-first bias is real—sometimes even when you set the language, technical responses (especially with code) slip back into English, which can be frustrating for non-English speakers. 😅

For language fallback, we try to:

Always check the user's preferred language and prompt the model accordingly (though it’s not perfect).

If the AI responds in English, we provide an instant translation or a “Translate to [user’s language]” button.

Collect user feedback on language quality to improve and fine-tune over time.

Biggest unexpected challenge? Handling cultural nuances in humor and tone. Something that sounds friendly in English can come across as rude or awkward in another language. 🤦‍♂️

To all non-English speakers: I’d love to know—do you prefer getting code comments/outputs in your native language, or is English actually easier for technical stuff?

Thanks for starting this great conversation! 🚀