Up to 60 million people speak Spanish today in the USA. However, large companies like Bank of America or Amtrak are struggling to have a Spanish-speaking customer support bot to multiply their sales opportunities. Is it that difficult to make AI understand Spanish?
Any improvement you want to make to your chatbot must be based on real facts to achieve more favorable results; there is no time to shoot in the dark. This is where metrics have an important role to play. Telling you what needs to be modified to assure a better customer experience and increase your revenue rates. What gets measured, gets managed.
Big companies don’t think it twice: the wider their audience, the higher their profits. In this context, when they want to carve out a market niche worldwide, English is not enough. What is missing here, as far as businesses are concerned, is serious attention to multilingual needs in customer support. Multilingual chatbot is a gold opportunity to reach them all.
Many consulting companies are currently delivering chatbots that understand and reply to humans in a more natural way. Nevertheless, there is still scope for improvement and challenges to overcome. Chatbots must know how to deal with complex queries not to scare customers away. Therefore, those able to achieve this goal will turn into cash cows for their consulting firms.
Bots built upon machine learning need long training processes to have the ability to hold a meaningful conversation with real people. Training data becomes, therefore, a diamond in the rough; all companies need such input for their bots. Until now, this data was generated in a slow manual way. However, speeding up your bot training can now come true with artificially generated data.