Vapour’s CEO, Tim Mercer, was recently featured in Technology Reseller magazine discussing NLU. If you missed it, you can read the article in full here...
With tech, apps and gadgets evolving at pace, it can be hard to keep up with the number of emerging innovations continually coming to market – certainly because so many are either beyond reach or of little relevance to mainstream businesses. However, while Natural Language Understanding (NLU) sounds cutting edge – and it is – it could actually prove transformational for a vast number of organisations, of all shapes and sizes. Tim Mercer, CEO of disruptive cloud specialist, Vapour, explores…
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, means there is a wealth of linguistic data now available. Human-to-machine communication is also more prevalent than ever before.
The utilisation of NLP technologies has therefore continued to rise.
In the simplest of terms, such tech means that computers can 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, which means that, in the home, our personal devices can satisfy a music request, for example, in a matter of seconds. It has changed how we interact with search engines too, and automated assistants – which many people refer to as chatbots – now support us like never before when we’re transacting 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. And, consequently, in recent years, we’ve seen increased deployment of NLP in much wider business settings.
The contact centre is one environment where NLP has proven revolutionary, especially during recent times.
Now, instead of traditional IVRs simply routing calls to relevant operators according to the nature of the queries, intelligent agent assistants can pull people from lengthy queues and address many 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.
An omnichannel contact centre that pulls together information from various communications sources including web chat, social media and email – because it cares so much about CX – may find this the icing on the cake. Businesses overwhelmed with volume during peak periods of activity, also undoubtedly benefit.
However, NLU – Natural Language Understanding – takes this approach to the next level. Because, 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 challenges of the customer – and the likely emotion of 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 could read the room.
This means information from various channels – voice, email, chat, social media and more – can all be analysed and managed by both human and digital interaction, with speed and agility we haven’t seen before in the 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. But from customer service environments to healthcare, and insurance to retail, the use cases for this type of tech are vast. In some organisations where margins are minimal and volume is key, intelligent machine agents can even take care of the majority of customer communications, if not all. This won’t be the preference for all brands of course, but the bottom line is that the tech exists, and it isn’t as inaccessible as many would probably 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. So, from automated document reviews to order shipping completions, it will be interesting to see which other firms start such a journey, especially as the technology becomes far more mainstream over the next three years.
