Chatbots are an effective tool for helping businesses streamline their customer and employee interactions. The best chatbots communicate with users in a natural way that mimics the feel of human conversations. If a chatbot can do that successfully, it's probably an artificial intelligence chatbot instead of a simple rule-based bot.
But what is an artificial intelligence chatbot? Essentially, it's a chatbot that uses conversational AI to power its interactions with users. Because artificial intelligence chatbots are available at all hours of the day and can interact with multiple customers at once, they're a great way to improve customer service and boost brand loyalty.
An NLP chatbot is a more precise way of describing an artificial intelligence chatbot, but it can help us understand why chatbots powered by AI are important and how they work. Essentially, NLP is the specific type of artificial intelligence used in chatbots.
NLP stands for Natural Language Processing. It's the technology that allows chatbots to communicate with people in their own language. In other words, it's what makes a chatbot feel human. NLP achieves this by helping chatbots interpret human language the way a person would, grasping important nuances like a sentence's context.
In a more technical sense, NLP transforms text into structured data that the computer can understand. To do that, it must process large amounts of linguistic data. Keeping track of and interpreting that data allows chatbots to understand and respond to a customer's queries in a fluid, comprehensive way, just like a person would.
As we've just seen, NLP chatbots use artificial intelligence to mimic human conversation. Standard bots don't use AI, which means their interactions usually feel less natural and human.
Most standard bots are what we call "rule-based" bots. They're designed to strictly follow conversational rules set up by their creator. If a user inputs a specific command, a rule-based bot will churn out a preformed response. However, outside of those rules, a standard bot can have trouble providing useful information to the user. What's missing is the flexibility that's such an important part of human conversations.
So what sets NLP chatbots apart? Here are a few of the characteristics of NLP chatbots that give them the edge over more traditional bots:
The benefits offered by NLP chatbots won't just lead to better results for your customers. They'll make them feel more comfortable and valued as well.
As we pointed out earlier, simple bots can only take you so far. A simple bot can handle simple commands, but conversations are complex and fluid things, as we all know. If a user isn't entirely sure what their problem is or what they're looking for, a simple but likely won't be up to the task.
A natural language processing chatbot can serve your clients the same way an agent would. Natural Language Processing chatbots provide a better experience for your users, leading to higher customer satisfaction levels. And while that's often a good enough goal in its own right, once you've decided to create an NLP chatbot for your business, there are plenty of other benefits it can offer.
NLP chatbots can often serve as effective stand-ins for more expensive apps, for instance, saving your business time and money in terms of development costs. And in addition to customer support, NPL chatbots can be deployed for conversational marketing, recognizing a customer's intent and providing a seamless and immediate transaction. They can even be integrated with analytics platforms to simplify your business's data collection and aggregation.
But you don't have to take our word for it. Tech giants like Amazon and Google have been investing heavily in at-home assistants like Alexa and Google Home for several years. Though you might not realize it, these assistants rely on conversational AI to interact with their owners, offering their users conversations that feel dynamic and, most importantly, human.
Different types of chatbots have diverse use cases. Chatbots are generally personalized according to an organization's needs and preferences, so you're the one that really decides what skills to give your chatbot. Businesses that leverage this technology must ask themselves the following questions to define their chatbot's key competencies:
An AI chatbot uses its artificial intelligence skills to understand whether the text that the user enters corresponds to one of the chatbot's competencies. There are a series of factors that enable NLP chatbots to understand:
To start a conversation with a user, businesses need to develop the most efficient way to guide users. They have to make sure their chatbot understands the context of the conversation to provide the appropriate answer. To achieve this, organizations need to define:
This is a key part of designing a chatbot. Businesses need to define the channel where the bot will interact with users. A user who talks through an application such as Facebook is not in the same situation as a desktop user who interacts through a bot on a website. There are several different channels, so it's essential to identify how your channel's users behave.
Machine learning is a subfield of Artificial Intelligence (AI), which aims to develop methodologies and techniques that allow machines to learn. Learning is carried out through algorithms and heuristics that analyze data by equating it with human experience. This makes it possible to develop programs that are capable of identifying patterns in data.
Thanks to machine learning, artificial intelligent chatbots can predict future behaviors, and those predictions are of high value. One of the most important elements of machine learning is automation; that is, the machine improves its predictions over time and without its programmers' intervention.
Even though intelligent chatbots rely on machine learning, businesses also need to train their chatbots. They need constant attention to provide the best response. Thanks to demos and user tests, organizations can find out what needs to be improved. Here are some key questions businesses should ask themselves to improve their virtual assistants:
Four main acronyms are used in the world of artificial intelligence, and that will help you further understand chatbots:
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