With so much new technology emerging in the contact centre and communication markets these days, it’s easy to get confused. The term “Natural Language Understanding” (NLU) is often used interchangeably with “Natural Language Processing” (NLP). However, the truth is that NLU is just one type of natural language processing.
The concept of NLP covers all the systems that work together to cover end-to-end interactions between humans and machines. It allows people and tools to talk to each other in a natural and human way. While NLP is critical in most human-facing artificial intelligence solutions, NLU is a lot more specialised.
Natural Language Understanding addresses one of the major challenges of AI today – how to handle the unstructured conversations between machines and humans and translate them into valuable insights. While humans can handle issues like slang and mispronunciation, computers are less adept in these areas. That’s where NLU comes in handy.
What is Natural Language Understanding?
Natural Language Understanding is one of the core solutions behind today’s virtual assistant and IVR solutions. This technology allows for more efficient and intelligent applications in a business environment. For instance, with NLU, you can build contact centre systems that can intelligently assess a call and route the person behind it to the right agent. NLU also empowers users to interact with devices and systems int heir own words, without being restrained by fixed responses.
Natural Language Understanding empowers users to interact easily with devices and systems in their own words, without being constrained by fixed responses. It helps systems like virtual assistants and IVR to better understand human words. With NLU, computers can figure out what speakers mean – rather than just responding to the words that they say.
Today’s voice-first technology solutions are built with NLU, which delivers artificial intelligence focuses on recognising patterns in human language. When computers understand what people mean, conversational AI becomes a possibility. Natural Language Understanding also means that customers can use their own words to describe the reason for a call. In contact centres, this leads to faster and more direct paths to resolution.
Often, Natural Language Understanding is a common component in the construction of virtual assistants, which allow customers to easily engage with modern self-service systems. With this technology, companies can make sure that customers get the support and guidance they need as quickly as possible, even if they’re not speaking to a human agent.
Natural Language Understanding Trends
Tractica studies suggest that the Natural Language Processing market, complete with natural language understanding will reach a value of $22.3 billion by 2025. The research cites 42 different use case options in 14 industry segments, set to drive the growth of natural language software. Some of the trends we can see in the NLU market include:
1. Solutions for Customer Service
Natural Language Understanding is technology built on machine learning, AI, and neural networks. The technology provides computers with background knowledge that they can use to determine what a person would say in specific situations. This makes it easier to create self-service solutions that deliver relevant opportunities to customers.
With Natural Language Understanding, contact centres can create the next stage in customer service. Enhanced virtual assistant IVRs will be able to direct calls to the right agent depending on their individual needs. It may even be possible to pick up on cues in speech that indicate customer sentiment or emotion too. Customers may even be able to launch business conversations through Alexa or Siri.
2. Reputation Management
In an age where customers are increasingly comfortable voicing their opinions over the web, businesses have begun to invest their resources into reputation management and monitoring brand mentions. Natural Language Understanding can automate sentiment analysis strategies and make it easier for companies to keep track of the perceptions around their brand.
Systems will be able to track the feelings of customers when they’re interacting with and talking about brands so that companies can address issues faster.
3. Enhanced Business Intelligence
As the technology available for natural language understanding and processing continues to evolve, computers will be able to deliver better insights into the performance of a business. For instance, you could ask your computer how your revenues have changed in recent months, and it could return a number of insights for you to analyse.
Implementation of Natural Language Understanding solutions will allow business leaders to investigate and track the events taking place within their company. This could lead to better, more informed decisions for companies.
4. Extensive Data Management
Today, it’s becoming increasingly difficult for companies to process vast amounts of data without the support of NLP and NLU solutions. For instance, finding a piece of information in a vast data set manually would take a significant amount of time and effort. However, with natural language understanding, you can simply ask a question and get the answer returned to you in a matter of seconds.
Additionally, NLU can improve the scope of the answers that businesses unlock with their data, by making unstructured data easier to search through and manage. In the years to come, businesses will be able to use NLU to get more out of their data.
Natural Language Understanding Statistics
Both the Natural Language Processing and Natural Language Understanding markets are growing rapidly, thanks to the increased adoption of voice assistants and artificial intelligence. Tools like Siri and Alexa are already popular in the consumer world, and opportunities are emerging in business too.
- The Natural Language Processing market will reach a value of $22.3 billion by 2025.
- Natural Language Understanding promotes a 50% reduction in call duration
- Natural Language Understanding encourages a 20% increase in contact centre productivity levels.
Natural Language Understanding Hashtags Used on Social Media
- #NLU
- #NLP
- #Learning
- #MachineLearning
- #DataScience
- #Language
- #ArtificialIntelligence
- #Virtualassistant
