Language I / O aims to strengthen its AI-based customer service localization service
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As businesses embrace digital transformation, many are expanding their customer base beyond the limits of their pre-pandemic demographics. For example, the cross-border e-commerce market is growing twice as fast as domestic e-commerce, driven by consumers to search for brands not available in their home country. According to Worldpay, 55% of online shoppers globally purchased from another country in 2020.
But while digitization offers businesses the opportunity to expand their target markets, many face the challenge of localizing their content for particular customer segments. It is true that the majority of customers prefer to buy products with information in their native language. But companies, drawn by the promise of new business – especially in the chaos of the pandemic – have at times cut back on location experiences. Almost 68% of users in a recent survey said they come across web translations that are incorrect or confusing because they lack sufficient cultural understanding.
A large number of companies provide enterprise localization services to businesses, but an emerging subset is exploiting AI in an attempt to speed up the translation process. Lilt, based in San Francisco, Calif., Develops AI-based translation software for marketing, customer support, and e-commerce use cases. Lingo24 and Smartling, owned by Unbabel, use a combination of AI-based translation tools and human translators to localize product descriptions, user guides, websites, software and applications. There is also Lokalise, a “continuous localization” platform that helps companies ensure their software is suitable for target markets.
Language I / O is a small newcomer to the localization arena, having raised just $ 12.1 million in VC since its inception in 2011. (This includes a $ 6.5 million Series A led by Omega Venture Partners, which the company announced today.) While Language I / O is not short of competitors in a market that could be worth $ 5.51 billion by 2028, CEO Heather Shoemaker says the company’s technology sets it apart significantly from other solutions currently available.
The localization challenge
Localization is not as easy as basic translation. Sentences are longer in some languages than others (for example, “buy now” in English is “buy now” in French), which means web designers have to redesign the page elements for them. adapt to longer translated sentences. Additionally, some languages run top-to-bottom or right-to-left, which not all website templates support. And cultural considerations in each language may dictate the choice of words. For example, for a speaker in Japan, where the choice of words depends on the status of the speaker as well as that of the listener, friendly and informal advertisements that go well in the United States might rub them the wrong way.
Based in Cheyenne, Wyoming, Language I / O aims to provide solutions specifically for customer service localization, allowing businesses to use unilingual agents or chatbots to provide support articles, respond to emails and chat in multiple languages. The startup says it can get a client up and running with translations within 24 hours, thanks to the use of AI by the Language I / O platform.
Shoemaker founded Language I / O several years ago, having spent the first decade of his career as an engineer traveling internationalization. After lucratively leaving a Denver-area startup, she worked with a team to develop the localization technology that now forms the basis of Language I / O’s software-as-a-service platform.
“The need for high quality personalized customer support available on digital channels and delivered in the customer’s native language has increased dramatically during the pandemic,” Shoemaker told VentureBeat via email. “The expansion of a remote global workforce means companies are looking to extend translation and localization capabilities with current customer relationship management technologies that are already familiar to their support agents. In addition, [the pandemic] has made travel unsafe and companies are unwilling to recruit native speaker support teams around the world. This has resulted in a huge demand for technologies like those provided by Language I / O, which allow businesses to make the most of the support agents they already have in their homes.
Language I / O uses an engine that intelligently selects AI models for requests and adopts preferred translations for product names, misspellings, acronyms, industry jargon, and slang. Customers report any errors and tell Language I / O what words they want in their dictionary, allowing models to improve over time in around 100 languages.
“[Our self-improving glossary engine] uses datasets generated over the years related to the quality of the translation. Our datasets do not include actual content sent to us for translation which makes us unique in the industry as our competitors rely heavily on training their models with the content they translate, ”said Shoemaker. “Withholding this content for training is dangerous because personal data is often embedded in chats and support emails. Businesses get nervous when their customers’ personal data is duplicated and stored outside of their own systems, as this is just one more opportunity for breach. Instead, Language I / O has collected translation quality data over the years related to the metadata related to each translation request.
Language I / O integrates with customer relationship management systems, including Zendesk, Oracle, and Salesforce, and offers an API that allows customers to access company-specific translations. These systems benefit from the aforementioned feedback provided by the professional agents and linguists that Language I / O works with to refine its core technology.
It all depends on the accuracy of the translations – and the algorithms are not perfect in this regard. But according to one estimate, conversational AI-based solutions can reduce customer service costs by up to 30%. Perhaps that’s why 56% of companies say they’re investing in conversational AI technology to improve cross-channel experiences, according to Deloitte.
While the Language I / O platform, which employs 46 people, is currently focused on translating in channels such as email, articles, chat and social messaging, Shoemaker says the company is ready. to expand beyond basic support to “wherever businesses need conversational translation”. Think: Slack channels, player-to-player chats, virtual meeting technology, and learning management platforms.
“The [new] the money must allow us to scale quickly with the goal of tripling revenues in 2022, ”said Shoemaker. “Our product focus this year will be in the area of chatbots and conversational AI and for our machine learning team, which is focused on improving the quality of machine translation.”
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