Plan de l'article
- Definition: What is a chatbot?
- Why are more and more companies starting to use chatbots?
- How does a chatbot work?
- How do you build a chatbot?
Definition: What is a chatbot?
Chatbots are software applications that mimic written or spoken human language to simulate a conversation or interaction with a real person. A chatbot is computer software based on rules or natural language processing (NLP) and machine learning to understand a conversation and pretend human interaction.
You can ask questions or give commands to a chatbot, and the bot should respond to these questions or commands with appropriate answers or activities.
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Chatbots can be integrated into any number of chat apps, such as Facebook Messenger, WhatsApp, and other chat services.
The term “chatbot” was first used in 1994 by Michael Mauldin (creator of the first chatbot, Julia) to describe these chat applications.
Today, chatbots are the most common customer service , where the chatbot takes on different roles, such as customer support or taking orders.
The use of chatbots for corporate purposes continues to grow thanks to advances in NLP. Bots are becoming more and more conversation-safe and barriers to entry, such as complex programming knowledge, are becoming more and more unnecessary.
Why are more and more companies starting to use chatbots?
There are several reasons why companies use chatbots. For example, chatbots can take on routine tasks and process multiple requests from users at the same time. The fast turnaround time for recurring tasks and inquiries can not only save employees resources, but also increase customer loyalty. While an employee can only process one request per time, a bot is quite capable of having many conversations at the same time. This could result in long waiting times in the future Customer hotlines are omitted.
Unlike other products that are tailored to specific industries, chatbots can be used by almost any industry. Not least because some business segments, such as customer support, are often overarching business areas.
Chatbots also provide a consistent user experience because these software applications are based on rules that determine behavior. This allows a company to pre-determine the desired user experience and thus communicate the brand message and corporate philosophy in a uniform way. A satisfactory experience for the customer naturally requires that the chatbot correctly understands the customer’s request and acts accordingly sensibly.
Not only companies, but consumers can also benefit from chatbots. On the one hand, waiting time on the customer side is reduced because a bot can answer multiple inquiries at the same time, on the other is a chatbot always available so the customer can interact with the bot around the clock.
How does a chatbot work?
There are several ways a chatbot can work, but there are currently two common ways to build a chatbot: rule-based logic and machine learning.
Chatbot technology focuses on natural language processing, called NLP. This technology is the basis for speech recognition systems from virtual assistants such as Alexa, Siri, and Cortana.
Chatbots process the user typed text using a process known as “parsing.” The bots then respond either with predetermined rule-based answers or with answers based on machine learning, depending on what logic they are based on.
One of the biggest challenges for chatbots is correctly interpreting natural language. In order for chatbots to respond appropriately to requests, they must first correctly interpret the request. It is particularly difficult for programs to recognize subtle nuances in a conversation and to insert the individual words into a coherent overall context.
Some chatbots are already able to have quite authentic conversations and it’s not always easy to tell whether you’re chatting with a bot or a human.
Chatbots based on rules can only have quite limited conversations. Because rule-based bots can only respond to certain pre-built actions and questions with specific answers. These software applications are only as good as the rules you are based on and need to be updated with new rules by programmers for each new situation.
Machine learning based chatbots try to turn on the contrary rule-based bots, create a natural conversation without creating ready-made answers. This means that the bot doesn’t have to use specific words or ready-made phrases. These software applications are self-learning and improve the more learning material, in the form of conversations they get.
How do you build a chatbot?
If you want to create your own chatbot, we’ll give you a few tips to get you started.
1. Define the bot’s goals
What should the chatbot do and what functions should it take on? Create a list of features you want the bot to perform. Think about which tasks are recurring in your company and may therefore be covered by a bot or in which areas a bot could improve the user experience.
2. Select a suitable channel to connect with your customers interact.
Integrate your chatbot where your customers want to communicate — your website, app, Facebook messenger, WhatsApp, or other messaging platforms.
3. What type of bot do you want to create?
You can either use a pre-built chat bot software that takes away some programming effort for you. However, this solution is only customizable up to a certain degree. Of course, you can also create a custom bot from scratch. This software application can then be designed entirely according to your individual wishes and requirements, but is much more complex in programming.
4. Test the bot before you go live
Before you go live with the bot, you should test it extensively to minimize the risk that customers encounter any errors and get a suboptimal user experience.