This post will delve deeper into how smart chatbots work and what’s behind the “black magic” superpowering their performance. We’ll also discuss the advantages they offer businesses over other widely-used chatbots so you can decide about your bot implementation.
To relieve the support department, process customer requests faster, and collect information about orders, chatbots are connected to messengers or websites. However, regular chatbots may not be able to perform all tasks. For example, they may not always understand the customer’s goals, provide irrelevant answers, break down, and transfer the customer to a support agent.
If the chatbot cannot handle the task and human agents are already overloaded, another way is to develop an AI-based chatbot that can maintain a conversation and logically answer non-standard user questions.
AI-based chatbots are programs that simulate human answers using messages. For example, when a person orders a pizza or purchases a product in a messenger, they often communicate with a bot without even knowing it.
By contrast, when standard, non-AI-powered chatbots respond to customer requests, their answers may look very awkward, as they often do not understand and correspond to the user’s needs.
An AI-powered chatbot, or smart chatbot, understands natural language. It reads user messages, analyses them, and finds familiar keywords and synonyms. Then, it processes them using a neural network and generates answers. The response is similar to one that a living person would write.
In addition, smart chatbots can predict, analyse, and identify user preferences. Based on this data, they can recommend content, products, etc.
AI-based chatbots can be used in different channels: messengers and social networks, mobile applications and games, as mobile support operators.
Essentially, an AI-based chatbot can handle the same tasks as a regular bot:
- Process requests for appointments with a doctor, in a beauty salon, or book tickets.
- Answer customer questions instead of technical support.
- Select related products for a customer’s main order.
- Send SMS, push, and email notifications to customers about upcoming appointments.
- Collect customer contact information and transfer it to CRM.
For an AI-based chatbot to understand human speech, it needs to convert it into a format that is convenient for a computer. This is where the natural language processing (NLP) algorithm comes into play.
Simply put, the NLP algorithm first breaks down human speech or messages into sentences and then into individual words, throwing out all stop words from sentences. As a result, the remaining necessary words are converted into sets of numbers (vectors), which the bot uses to understand what the user is saying.
When the chatbot understands the user’s message, it gathers important information such as dates, times, locations, or geolocation from the message fragment to prepare the most accurate answer.
Natural language understanding (NLU) is necessary for the bot to recognise live human speech with errors, typos, stumbles, abbreviations, and slang. For example, it will understand if a person says “NY” instead of “New York” or “Jon” instead of “John.”
In addition, bots use machine learning (ML) algorithms. The neural network analyses large amounts of data, improves its responses, and better understands human language. Thanks to machine learning, humans do not have to teach the bot to understand human speech. The bot does this based on data from thousands of conversations between humans and machines.
As a result, the robot begins to recognise certain words or phrases. And when the user inputs these keywords, the system answers accordingly.
For example, if you train the algorithm to recognise speech patterns, over time, it will automatically understand what the person is saying. And you don’t have to add different keywords to the robot’s database – it will learn them on its own.
See the demo of Tovie AI’s most popular solution – a smart claim processing bot for insurance:
Interested to know more about how they design virtual assistants that people want to talk to? Check out our article to learn all about the ins and outs of natural dialogue script building.
AI-based chatbots have several advantages over other types of bots:
- They understand typical conversational language.
- They maintain the context of the conversation rather than communicating in terms of specific phrases.
- They learn on their own, so they don’t require as many variations of phrases and responses to add as ordinary bots.
- They gather information from all open sources and use it to answer users. It happens in seconds, so these bots can be used in real-time conversations.
- Cost. A smart chatbot costs an average of $3,800, while a regular one with average functionality ranges from $450 to $1,300. The high price of smart bots is not always justified. For example, if you need to provide answers from an FAQ, developing a regular chatbot using a constructor at a meagre cost is sufficient.
- Difficulty in training. If a smart bot is given little data and insufficient training, it may respond incorrectly to user questions. In addition, the created bot needs to be constantly retrained and its database expanded. Otherwise, it will eventually malfunction.
- Limited range of topics. Even if a chatbot is well-trained and given a vast database, it still won’t be able to answer questions or understand context outside its area. And if a customer asks a non-typical question, the bot may not understand it.
Moreover, a sophisticated smart chatbot may not always be necessary for a business. For instance, a restaurant might need a tool to simply process orders and deliveries, while a beauty salon may only need to respond to common queries about procedures and schedule appointments. In such situations, AI is unnecessary, and a regular FAQ or rule-based bot can handle these tasks.
Smart chatbots are versatile tools with applications spanning various industries and functions. Let’s see just some of these scenarios:
1. Customer support: Smart chatbots offer round-the-clock assistance, tackling common queries and resolving issues. They are adept at guiding customers through websites or mobile apps.
2. Sales. Utilise smart chatbots to assess leads, suggest products and facilitate purchases. These bots can also execute upselling and cross-selling strategies.
3. Marketing. Engage customers personally through tailored messages, promote products, and collect valuable feedback. You can also employ chatbots for surveys and quizzes.
4. Human resources. Streamline HR operations like onboarding, training, and performance evaluations with chatbot automation. Employees can get quick answers and support.
5. E-commerce. Enhance the shopping experience by offering product recommendations, processing orders, and managing returns. Customers can seek assistance and answers promptly.
6. Banking and finance. Chatbots provide account updates, transaction processing, and financial guidance. They serve as reliable sources for customer queries and support.
7. Telecom. Handle customer inquiries, sales support, and technical assistance with chatbots. They facilitate plan upgrades and deliver account information.
These scenarios show how adaptable smart chatbots are. They can be customised to suit any business’s specific needs and goals.
The introduction of ChatGPT has significantly sped up the integration of AI technologies in businesses, reshaping both brand dynamics and employee workflows. Even those without programming experience now have accessible tools to boost their productivity. With Large Language Models (LLMs), ordinary text prompts can be used to create original posts, generate images or entire presentations, summarise meetings, and much more.
We’re already familiar with ChatGPT and similar tools generating texts, images, music, and videos. Companies can utilise this content to develop new products and attract customers. Generative AI enhances the quality of creative tasks, reduces routine work, identifies new product value for customers, and even transforms entire processes within a company.
These systems can handle vast amounts of data, unveil hidden connections and patterns, and provide CEOs with valuable information for strategic decision-making.
If you’re eager to learn more about how businesses can leverage Generative AI, check out this article.
The chatbot industry is undergoing a rapid transformation thanks to the advancements in generative AI and the emergence of powerful language models like GPT. These technologies have enabled chatbots to understand and respond to complex queries, provide personalised recommendations, and engage in natural, human-like conversations with users.
Because of their ability to learn from vast amounts of data, smart chatbots are becoming more sophisticated and intelligent every day. Taking advantage of this technology will enhance your business customer experience, streamline operations, and improve overall performance. However, the decision to implement it depends entirely on your customer communication strategy and your ultimate goals.
| Want to see a smart Tovie AI chatbot in action? Schedule a free demo.
FAQs
What is the smart chatbot?
Powered by sophisticated AI and NLP technologies, a smart chatbot can understand and respond to complex queries with human-like accuracy, learn from interactions, and provide personalised user experiences.
What is the most advanced chatbot?
The most advanced chatbots leverage state-of-the-art natural language processing and AI technology, offering dynamic responses and learning from interactions. Examples include OpenAI’s GPT-3, which excels in generating human-like text based on given prompts.