Let’s go back to the state of machine translation as recent as ten years ago. Back then, machine translation systems were largely based on statistical algorithms. It was considered a step up compared to previous rules-based methods of machine translation, but the results were still far from satisfactory.
You can learn more about statistical machine translation in our article: The Impact of Statistical Machine Translation On Globalization
But by the mid-2010s, developments in AI and machine learning were beginning to show effects in the field of machine translation. Most people would be familiar with Google Translate, and how its quality improved by leaps and bounds after the introduction of neural machine learning technology into its system.
eBay had also begun implementing AI-based MT technology for select oman mobile database languages around that time as well. In 2014, eBay acquired the MT tech company AppTek, boosting their machine translation capabilities to a higher degree.
It’s a well-known fact in the language industry that consumers prefer to buy products that have information available in their own language. CSA’s oft-cited study Can’t Read, Won’t Buy reports that a full 40% of consumers won’t buy products that aren’t available in their own language. That’s a huge share of the market that remains untapped.
If your business’s website is only available in English, then you’re missing out. English is no longer the lingua franca of the internet—In 1996, 80% of the internet’s users spoke native English. But by 2010, that number had dropped to 27.3%. That number may be even less today.
This is because growth continues to accelerate in emerging markets around the world. China is now one of the biggest drivers of global economic growth. The Middle East has also seen a major upturn in the past few decades. Other countries are also getting a larger slice of the pie than before.