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Why every business needs to know about NLU

With tech, apps and gadgets evolving at pace, it can be hard to keep up with every innovation that comes to market – not least because so many are either beyond the reach of or of little relevance to mainstream businesses. One that genuinely does have the potential to be transformative for organisations of all shapes and sizes is Natural Language Understanding (NLU), as Tim Mercer, CEO of disruptive cloud specialist Vapour, explains

With roots surprisingly dating back to the 1950s, Natural Language Processing (NLP) is not new. However, the explosion of the internet and the ever increasing adoption of digital technologies mean there is now a wealth of linguistic data available. And, with human-to-machine communication also more prevalent than ever before, the utilisation of NLP technologies has continued to rise.

In the simplest terms, NLP enables computers to comprehend the spoken or written word – even though they speak in ones and zeros – and perform an action as a result of that interpretation.

It’s a powerful combination of linguistics, computer science and artificial intelligence that, in the home, allows our personal devices to satisfy a music request, for example, in a matter of seconds. It has changed how we interact with search engines, too, and today automated assistants – which many people refer to as chatbots – support us like never before when we transact online.

In truth, the list of examples goes on and on, with NLP being used to answer questions, extract and retrieve information and even analyse sentiment. As a result, we’ve seen increased deployment of NLP in much wider business settings, including the contact centre, where it has been revolutionary.

Now, instead of traditional IVRs simply routing calls to relevant operators according to the nature of the query, intelligent agent assistants can pull people from lengthy queues and address matters quickly and easily themselves. This reduces the wait time for people who require more complex assistance and provides a swifter response for callers with more basic requests. The customer experience (CX) is improved for all, and the productivity and wellbeing of contact centre staff is also boosted, as workloads should become more manageable.

Businesses overwhelmed with volume during peak periods of activity undoubtedly benefit from NLP, as do omnichannel contact centres that pull together information from various communications sources, including web chat, social media and email, in the interest of CX.

The next level

NLU – Natural Language Understanding – takes this technology to the next level. While NLP is capable of sentiment analysis, it focuses on what was said. The machine learning in NLU, on the other hand, is so deep that it looks at tone, context and intent to deduce what was meant. The challenge a customer faces

Natural Language Understanding

– and what they feel about the situation – can therefore be anticipated and managed accordingly. Likewise, in more positive situations, I see NLU accelerating customer service successes and transactions, because, for want of a better phrase, it can read the room.

Information from various channels – voice, email, chat, social media and more – can now be analysed and managed by both human and digital interaction, with a degree of speed and agility we haven’t seen before in a business environment. The value it can add will vary from one business to the next, from proactive signposting and engagement to the reactive triaging and remedying of potentially brand-damaging situations.

From customer service environments to healthcare, from insurance to retail, the use cases for this type of tech are vast. In organisations where margins are minimal and volume is everything, intelligent machine agents can take care of the majority of customer communications, if not all. This won’t be the preferred route for all brands, of course, but the bottom line is that the tech exists and it isn’t as inaccessible as you might think.

As is often the case when it comes to tech vision and adoption, large firms with deep pockets are a little ahead of the curve with NLP and NLU. However, savvy contact centres and scale up- hungry businesses aren’t far behind. From automated document reviews to order shipping completions, it will be interesting to see which other firms start on this journey as the technology becomes more mainstream over the next three years.

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