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:
These applications are just some of the abilities of NLP-powered AI agents.
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.
A branch of artificial intelligence designed to improve human-bot communication by enabling machines to understand, analyze, and respond to human speech or writing.
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.
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.
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.
NLP-powered chatbots use the following keys to interpret interactions:
The ways the user refers to a specific intent
The meaning behind the words a user types or says
The details important to intent, like order numbers and locations
The parameters across a 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.
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:
Bots remove irrelevant details and convert words to a standardized version. For example, bots will lowercase language inputs.
Chatbots chop the language input into pieces—or tokens—and remove punctuation..
With normalized and tokenized text, the bot uses AI to identify the issue or intent the customer is asking about.
This optional step is where chatbots identify anything else referred to in a message, such as an order number, email address, or transaction ID.
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.
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.
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:
Dialogue management in AI agent includes context and session, and it tracks the state of the conversation.
The seamless communication and execution of a handoff from the AI agent to a human agent.
A set of algorithms and rules that define how data is created, stored, modified, and managed and how a business should behave and make decisions.
An AI agent’s ability to streamline the customer experience, its programmability, and help customers find the fastest route to the right solution.
The systematic training and feedback to improve an AI agent’s understanding of customer intents using real-world conversation data generated across channels.
The functionalities and flexibility of an AI agent to meet a business’s needs, ensuring the solution is easy to use yet powerful enough to grow alongside your business and automation requirements.
Advanced NLP chatbots like Zendesk AI agents offer cutting-edge features like:Advanced NLP chatbots like Zendesk AI agents offer cutting-edge features like:
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 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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Empower your operations with human-like AI agents, seamless integrations, and intelligent workflows for unmatched efficiency.
Achieved 4x efficiency with automated appointment scheduling and follow-ups.
Increased lead conversions by 5x using personalized AI interactions.
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