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Chatbots are rapidly becoming ubiquitous in marketing and support. The potential for brands to interact with customers using natural language – and perhaps a bit of personality – without needing an army of paid human agents is driving major investment from enterprises. Tech giants – from Google to Facebook and IBM and Weibo to Microsoft – have started a virtual race to dominate this field. However, what is missing in this picture so far is serious attention to multilingual needs. Amazon, Apple, Google, and Microsoft have all released digital assistants – Alexa, Siri, Google Assistant, and Cortana respectively – in multiple languages, but these are the exception, and other enterprises struggle to move past the language of their home market. As part of a detailed examination of how enterprises provide multilingual customer support, CSA Research interviewed market leaders in the creation of chatbots, also known as intelligent online agents, about how they provide multilingual capabilities. The results revealed that few companies have found ways to deal with language in a systematic fashion. As a result, results are sporadic, methods are ad hoc, and failures common. One chatbot implementer at a large tech vendor – one that develops a commonly used open chatbot framework – stated that the company’s team expects a 30% success rate from its own efforts. Chatbots pose challenges fundamentally different from what is seen with traditional content. The shift to conversational structures and the need to embrace “messy” terminology are among these.
As you build – or localize – chatbots, CSA Research’s examination of the issues reveals several techniques you can adopt to help ensure success. Five key points are:
Senior Analyst
Focuses on language technology, artificial intelligence, translation quality, and overall economic factors impacting globalization
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