What is Natural Language Processing (NLP)?
Natural Language Processing (NLP) is a subfield of AI that helps computers understand natural human language. NLP uses computer science and linguistics to build systems that can analyze and extract meaning from human speech and text. NLP can be extremely useful for analyzing large amounts of text at scale, partially or completely automating processes, and generally making human-to-machine communication easy and effective.
How does NLP work?
NLP is used to allow machines to decipher meaning from human language by analyzing different aspects like syntax, semantics, and morphology. This linguistic knowledge is then transformed into rule-based machine learning algorithms.
Applied to NLP, machine learning lets machines absorb vast amounts of natural language data and make sense of it in two main ways: syntactic analysis, where syntax and grammatical rules are used to derive meaning from a text, and semantic analysis, where algorithms focus on what the words themselves mean and how they can be interpreted depending on context.
More on the uses of AI in customer service
What are some NLP use cases?
NLP is already used in many everyday applications like autocorrect, predictive typing, chatbots, translation apps, and voice assistants like Siri or Alexa. NLP is also used by HR professionals to sort through applications and resumes, by email filtering technology to determine what messages are spam, promotional or important, and by publishing companies for more accurate news and content aggregation.
Essentially, anywhere it might be more efficient for a machine (vs. a human) to derive meaning from a text or voice input, NLP can be used. And it’s a rapidly growing segment of the AI market. Fortune Business Insights estimates that,
By 2028, the worldwide NLP market value will exceed 127 billion US dollars (up from $20.98 billion in 2021).
NLP chatbots for customer service
One segment of the market that has exploded in recent years is conversational AI and NLP-powered chatbots and virtual agents for customer support. This is because customer service inherently has a lot of repetitive inquiries that NLP bots can understand and often completely resolve without human intervention.
The statistics on NLP and AI in customer service tell a persuasive story:
- By 2025, advancements in virtual agents will automate up to 80% of call center agents’ tasks, up from 30-50% in 2021.
- 79% of contact center leaders plan to invest in greater AI capabilities in the next two years.
- The way chatbots are rising it is predicted that it can curtail the business costs by $8 billion by 2022.
As an NLP and AI-powered virtual agent platform, we here at Ultimate have also seen a dramatic increase in customer support teams adopting our product. Customer service leaders clearly see the value of allowing NLP bots and virtual agents to take over repetitive and time consuming tasks so they can easily scale their customer service operations and their human agents can concentrate on more complex cases.