What are NLP chatbots and how do they work?

Artificial intelligence (AI)—particularly AI in customer service—has come a long way in a short amount of time. The chatbots of the past have evolved into highly intelligent AI agents capable of providing personalized responses to complex customer issues. According to our Zendesk Customer Experience Trends Report 2024, 70 percent of CX leaders believe bots are becoming skilled architects of highly personalized customer journeys.

AI-powered bots like AI agents use natural language processing (NLP) to provide conversational experiences. The astronomical rise of generative AI marks a new era in NLP development, making these AI agents even more human-like. Discover how NLP chatbots work, their benefits and components, and how you can automate 80 percent of customer interactions with AI agents, the next generation of NLP chatbots.

More in this guide:

• What is an NLP chatbot?
• NLP bot vs. rule-based chatbots
• How a natural language processing chatbot works
• Key components of NLP-powered bots
• Types of NLP chatbots
• Benefits of an NLP bot
• How to automate more than 80 percent of customer interactions with an NLP chatbot
• Frequently asked questions
• Discover the most autonomous bots in CX

What is an NLP chatbot?

A natural language processing chatbot is a software program that can understand and respond to human speech. NLP-powered bots—also known as AI agents—allow people to communicate with computers in a natural and human-like way, mimicking person-to-person conversations.

These clever AI agents have a wide range of applications in the customer support sphere, like:

• Making it easier and more affordable for your business to grow.

• Giving your team valuable time back to focus on more meaningful work, ultimately evolving them into a new kind of role, as a manager, editor, and supervisor of AI.

• Seamlessly connecting with your backend systems, instantly recognizing who they’re talking to. From there, they provide personalized support with key details for an exceptional customer experience.

• Providing 24/7 support in multiple languages, which results in better experiences for your customers.

These applications are just some of the abilities of NLP-powered AI agents.

NLP vs. NLU vs. NLG

Don’t know your NLP from your NLG? Don’t fret—we know there are quite a few acronyms in the world of chatbots and conversational AI. Here are three key terms that will help you understand NLP chatbots, AI, and automation.

• Natural language processing (NLP): A branch of artificial intelligence designed to improve human-bot communication by enabling machines to understand, analyze, and respond to human speech or writing.
• Natural language understanding (NLU): A subset of NLP that focuses on machine comprehension, ensuring bots understand the meaning behind linguistic input (whether verbal or written) so they can convert language into a logical form a computer algorithm can understand.
• Natural language generation (NLG): Another subset of NLP that refers to the automatic replies created by a bot and works like NLU in reverse. After generating a logical response, the bot converts the output to a natural language that a human can easily understand.

While NLU and NLG are subsets of NLP, they all differ in their objectives and complexity. However, all three processes enable AI agents to communicate with humans.

NLP bot vs. rule-based chatbots

When you think of a “chatbot,” you may picture the buggy bots of old, known as rule-based chatbots. These bots aren’t very flexible in interacting with customers because they use simple keywords or pattern matching rather than leveraging AI to understand a customer’s entire message.

For example, a rule-based chatbot may know how to answer the question, “What is the price of your membership?” based on similar messages from previous interactions. You can teach these bots how to respond to this question, but the wording must be an exact match, so your bot builder will need to manually program phrasing nuances for every possible question a customer might ask.

Because of this specific need, rule-based bots often misunderstand what a customer has asked, leaving them unable to offer a resolution. Instead, businesses are now investing more often in NLP AI agents, as these intelligent bots rely on intent systems and pre-built dialogue flows to resolve customer issues. A chatbot using NLP will keep track of information throughout the conversation and use machine or deep learning to learn as it goes, becoming more accurate over time.

NLP-powered chatbots use the following keys to interpret interactions:

• Utterances: The ways the user refers to a specific intent
• Intent: The meaning behind the words a user types or says
• Entity: The details important to intent, like order numbers and locations
• Context: The parameters across a session
• Session: A conversation from start to finish, even if interrupted

While rule-based chatbots aren’t entirely useless, bots leveraging conversational AI are significantly better at understanding, processing, and responding to human language. For many organizations, rule-based chatbots are not powerful enough to keep up with the volume and variety of customer queries—but NLP AI agents and bots are.

How a natural language processing chatbot works

Bots using a conversational interface—and those powered by large language models (LLMs)—use major steps to understand, analyze, and respond to human language. For NLP chatbots, there’s also an optional step of recognizing entities.

Let’s take a closer look at how a natural language processing chatbot works:

1. Normalizing: Bots remove irrelevant details and convert words to a standardized version. For example, bots will lowercase language inputs.
2. Tokenizing: Chatbots chop the language input into pieces—or tokens—and remove punctuation.
3. Intent classification: With normalized and tokenized text, the bot uses AI to identify the issue or intent the customer is asking about.
4. Recognizing entities (optional): This optional step is where chatbots identify anything else referred to in a message, such as an order number, email address, or transaction ID.
5. Generation: For next-gen NLP AI agents, the AI model generates a number of responses and selects the most appropriate response to send to the user.

The AI technology behind NLP bots is advanced and powerful. Now that you understand the inner workings of NLP, you can learn about the key elements of this technology.

Key components of NLP-powered bots

NLP bots use AI to process human language. The key components of NLP-powered AI agents enable this technology to analyze interactions and are incredibly important for developing bot personas.

Here are some of the most important elements of an NLP bot:

Types of NLP chatbots

There are different types of NLP bots designed to understand and respond to customer needs in different ways. Below, we explain how NLP AI agents differ from standard NLP bots.

Generative AI NLP bots

Generative AI significantly enhances NLP chatbots by allowing them to provide personalized responses based on the user’s context, handle a broader range of queries, and deliver more accurate and relevant information. Additionally, generative AI continuously learns from each interaction, improving its performance over time, resulting in a more efficient, responsive, and adaptive chatbot experience.

For instance, Zendesk’s generative AI utilizes OpenAI’s GPT-4 model to generate human-like responses from a business’s knowledge base. This capability makes the bots more intuitive and three times faster at resolving issues, leading to more accurate and satisfying customer engagements.

AI agents

AI agents represent the next generation of generative AI NLP bots, designed to autonomously handle complex customer interactions while providing personalized service. They enhance the capabilities of standard generative AI bots by being trained on industry-leading AI models and billions of real customer interactions. This extensive training allows them to accurately detect customer needs and respond with the sophistication and empathy of a human agent, elevating the overall customer experience.

AI agents provide end-to-end resolutions while working alongside human agents, giving them time back to work more efficiently. For example, Grove Collaborative, a cleaning, wellness, and everyday essentials brand, uses AI agents to maintain a 95 percent customer satisfaction (CSAT) score without increasing headcount. With only 25 agents handling 68,000 tickets monthly, the brand relies on independent AI agents to handle various interactions—from common FAQs to complex inquiries.

AI agents have revolutionized customer support by drastically simplifying the bot-building process. They shorten the launch time from months, weeks, or days to just minutes. There’s no need for dialogue flows, initial training, or ongoing maintenance. With AI agents, organizations can quickly start benefiting from support automation and effortlessly scale to meet the growing demand for automated resolutions.

Benefits of an NLP bot

It’s a no-brainer that AI agents purpose-built for CX help support teams provide good customer service. However, these autonomous AI agents can also provide a myriad of other advantages. Below, we cover a few of the best benefits of NLP AI agents.

Reduce operational costs

NLP AI agents can resolve most customer requests independently, lowering operational costs for businesses while improving yield—all without increasing headcount. Plus, AI agents reduce wait times, enabling organizations to answer more queries monthly and scale cost-effectively.

For example, Hello Sugar, a Brazilian wax and sugar salon in the U.S., saves $14,000 a month by automating 66 percent of customer queries. Plus, they’ve received plenty of satisfied reviews about their improved CX as well.

Offer nonstop multilingual service

AI agents are never off the clock. With the ability to provide 24/7 support in multiple languages, this intelligent technology helps improve customer loyalty and satisfaction. Take Jackpots.ch, the first-ever online casino in Switzerland, for example. With the help of an AI agent, Jackpost.ch uses multilingual chat automation to provide consistent support in German, English, Italian, and French.

Personalize every interaction

NLP AI agents can integrate with your backend systems such as an e-commerce tool or CRM, allowing them to access key customer context so they instantly know who they’re interacting with. With this data, AI agents are able to weave personalization into their responses, providing contextual support for your customers.

Elevate your agent’s role

We’ve said it before, and we’ll say it again—AI agents give your agents valuable time to focus on more meaningful, nuanced work. By rethinking the role of your agents—from question masters to AI managers, editors, and supervisors—you can elevate their responsibilities and improve agent productivity and efficiency. With AI and automation resolving up to 80 percent of customer questions, your agents can take on the remaining cases that require a human touch.

Provide admins with actionable insights

AI-powered analytics and reporting tools can provide specific metrics on AI agent performance, such as resolved vs. unresolved conversations and topic suggestions for automation. With these insights, leaders can more confidently automate a wide spectrum of customer service issues and interactions.

How to automate more than 80 percent of customer interactions with an NLP chatbot

With AI agents from Zendesk, you can automate more than 80 percent of your customer interactions. Below, we’ve outlined a roadmap to guide your automation journey.

Start quickly with generative AI

Use generative AI to build a knowledge base quickly and effortlessly. AI can take just a few bullet points and create detailed articles, bolstering the information in your help desk. Plus, generative AI can help simplify text, making your help center content easier to consume. Once you have a robust knowledge base, you can launch an AI agent in minutes and achieve automation rates of more than 10 percent.

Related reading: Using generative AI to expand and enhance help center content

Personalize interactions with a hybrid approach

To achieve automation rates of more than 20 percent, identify topics where customers require additional guidance. Build conversation flows based on these topics that provide step-by-step guides to an appropriate resolution. This approach enables you to tackle more sophisticated queries, adds control and customization to your responses, and increases response accuracy.

Unlock end-to-end automation with backend integrations

Now is when your automation rate can soar to more than 40 percent. Connect your backend systems using APIs that push, pull, and parse data from your backend systems. With this setup, your AI agent can resolve queries from start to finish and provide consistent, accurate responses to various inquiries.

Optimize with analytics and QA

After you’ve automated your responses, you can automate your data analysis. A robust analytics suite gives you the insights needed to fine-tune conversation flows and optimize support processes. You can also automate quality assurance (QA) with solutions like Zendesk QA, allowing you to detect issues across all support interactions. By improving automation workflows with robust analytics, you can achieve automation rates of more than 60 percent.

Make AI your CX differentiator

Drive continued success by using customer insights to optimize your conversation flows. Harness the power of your AI agent to expand to new use cases, channels, languages, and markets to achieve automation rates of more than 80 percent.

Frequently asked questions

Discover the most autonomous bots in CX

With the right software and tools, NLP bots can significantly boost customer satisfaction, enhance efficiency, and reduce costs. However, not all NLP solutions are created equal.

In this era of AI-enhanced customer experiences, the focus should be on what truly matters: the human on the other end. Poor experiences can lead to customer loss, making AI specifically designed for CX essential.

Zendesk AI agents are the most autonomous NLP bots in CX, capable of fully resolving even the most complex customer requests. Trained on over 18 billion customer interactions, Zendesk AI agents understand the nuances of the customer experience and are designed to enhance human connection. Plus, no technical expertise is needed, allowing you to deliver seamless AI-powered experiences from day one and effortlessly scale to growing automation needs.

Invest in Zendesk AI agents to exceed customer expectations and meet growing interaction volumes today.