Surely you have noticed that the use of chatbots has been increasing recently. More and more companies use them to automate different spheres of the visitor experience. By reducing the number of service and live agents, entrepreneurs save significant amounts and make their business more efficient. Let’s talk about what is a chatbot and how to create it.
The definition of chatbot
A chatbot is a software or computer program which uses conversational artificial intelligence (AI) technology to simulate human conversation or «chatter» with people in natural language through messaging applications (Facebook Messenger, Twitter, Whatsapp, etc.), websites, mobile apps, and other systems.
In the simplest form, specialists program chatbots to answer specific, frequent questions and offer an easy way to communicate with visitors. More advanced chatbots study customer behavior and previous agent interactions to predict customer behavior and provide relevant data. Chatbots contribute to interaction automation and provide quick access to sales, marketing, and customer service options.
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Chatbots try to analyze and identify the intent of the user’s request to extract relevant entities. Upon completing the analysis, the user receives an answer to the question.
Chatbots most commonly use three classification methods:
Pattern matching. Bots apply pattern matches to group the text, creating a suitable response from the customers. The traditional structured model of such patterns is Artificial Intelligence Markup Language (AIML). A bot gets the correct answer in the connected pattern.
Natural language understanding (NLU) is the ability of a chatbot to comprehend human speech. It’s the algorithm for transforming text into a machine-understandable structured database. NLU follows three fundamental principles: entities, context, and expectations.
Natural language processing (NLP) bots can transform users’ text or speech into a structured database. Then the computer uses such data to give the correct answer. NLP includes many technologies: tokenization, entity recognition, dependency parsing, and others.
There are chatbots with different levels of complexity; they can be stateful or stateless. Stateless systems perceive every conversation as an interaction with a new visitor. On the other hand, stateful chatbots view interaction history and give new answers in the context of past discussions.
Types of chatbots
Since chatbots are still a new technology, continue discussions about how many types there are and what the industry should call them.
The most common variants of chatbots:
Scripted or quick reply chatbots. It’s one of the simplest chatbots, operating on a hierarchical decision tree principle. Communication with people occurs through predetermined questions; they last until the chatbot answers the customer’s question. Menu-based chatbots process the same way; they offer a person to choose from a predefined list or menu so that the system understands what the client needs.
Keyword recognition-based chatbots. It’s an improved version of quick reply chatbots, which try to listen to what the user types and respond correctly, using keywords from client answers. Such a bot successfully combines customizable keywords and AI tools for appropriate responses. The main problems of this type of chatbot are repetitive keyword use and redundant questions.
Hybrid chatbots. Such algorithms are a mix of menu-based and keyword recognition-based bots. Users can get answers directly or use the chatbot menu to make a selection if the keyword’s recognition fails.
Contextual chatbots. It’s the most complex chatbots that focus on the received information. They use AI and ML techniques to remember human conversation and interplay and utilize such recollections to improve themselves. Instead of considering only keywords, these bots recognize what visitors ask and how they pronounce the words to give answers.
Voice-enabled chatbots. It’s the future of technology; they use human conversations as input to prompt answers and creative challenges. Programmers make these chatbots using text-to-speech and voice recognition APIs, for instance, Alexa from Amazon and Apple’s Siri.
Adding a chatbot to a sales or service department requires zero or minimal programming.
The role of chatbots in business development
Since we have defined, what is a chatbot, it’s time to understand the main reasons why more and more businesses choose the chatbot strategy and why it’s a win-win variant for attracting customers:
Reduces waiting time for customers. According to polls, about 21 percent of customers consider chatbots the easiest way to contact a company. Bots are a clever way to guarantee visitors quickly find the answers to their questions.
The bot is available 24 hours a day, seven days a week. Chatbots are always ready to provide quick answers to the most common questions. Round-the-clock availability is the main competitive advantage of using such algorithms.
It’s a cost-effective decision. Chatbots are a faster and cheaper one-time investment than building a cross-platform application or hiring additional staff. Besides, chatbots reduce costly problems caused by human error.
Proactive interaction with the client. Recently, organizations have preferred passive customer interplay; in other words, they wait for buyers to get in touch first. Advanced chatbots can proactively interact because they can initiate conversations and control potential clients using the websites and landing pages. Companies accumulate such information and then utilize it to offer buyers special incentives and help them navigate the site.
Increase client base. Chatbots have a positive impact on lead generation, qualification, and nurturing. Such algorithms help throughout the buyer’s journey and provide information that can convince the user to make a purchase and attract potential customers. Then chatbots pass information about potential customers to the sales team to improve interaction with the target audience. Such algorithms increase the conversion rate and ensure that the lead moves towards the purchase.
Despite the many benefits, chatbots also face some challenges, including security issues, fending off hacker attacks, unpredictable human behavior, and mood. The user always wants the chatbot to be better than it currently is. Companies that use chatbots must constantly update and improve them so that users feel like they are communicating with an intelligent interlocutor.
Rules for creating a chatbot
It’s not enough to know what is a chatbot; you still need to be able to build it. Bots automate basic business functions, such as sales, support, and marketing. Below, you can see the six basic steps that will help to create your first chatbot:
Define your business goals. It’s essential to understand which functions need to be automated first. What is the purpose of the algorithm?
Choose the best channels for interacting with customers; they include the website of the company, mobile app, Facebook Messenger, Telegram, and other platforms.
Teach the bot to give correct answers; the FAQ tab helps the bot provide relevant solutions to customer questions.
Give your bot a voice and personality. You can give it a name and look that matches the corporate style.
Keep a balance. Most chatbots are not as efficient as a human. Determine at what stage customers can contact the specialist.
Test before launch. After defining your bot flow, check if it works correctly. Measure bot’s performance before launch and add necessary iterations from time to time.
You can build chatbots using a particular platform or create them from scratch.
Future of chatbots
Most experts in computer technology are confident the popularity of chatbots will increase. In the future, AI and ML will be able to offer new opportunities for chatbots and implement new levels of text and voice interaction with customers to change their experience. Such improvements will also affect the information collection and provide a deeper understanding of clients’ needs, leading to predictive visitor behaviors.
Voice services have become an essential element of the IT ecosystem. Nowadays, programmers focus on developing voice-based chatbots that perform like conversational agents, comprehend different languages, and speak in those same languages.