A chatbot is a software application used to conduct an on-line chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human agent. Designed to convincingly simulate the way a human would behave as a conversational partner, chatbot systems typically require continuous tuning and testing, and many in production remain unable to adequately converse or pass the industry standard Turing test. The term "ChatterBot" was originally coined by Michael Mauldin (creator of the first Verbot) in 1994 to describe these conversational programs.
Chatbots are typically used in dialog systems for various purposes including customer service, request routing, or for information gathering. While some chatbot applications use extensive word-classification processes, Natural Language processors, and sophisticated AI, others simply scan for general keywords and generate responses using common phrases obtained from an associated library or database.
Today, most chatbots are accessed on-line via website popups, or through virtual assistants such as Google Assistant, Amazon Alexa, or messaging apps such as Facebook Messenger or WeChat. Chatbots are typically classified into usage categories that include: commerce (e-commerce via chat), education, entertainment, finance, health, news, and productivity.
A chatbot -- sometimes referred to as a chatterbot -- is programming that simulates the conversation or "chatter" of a human being through text or voice interactions. Chatbot virtual assistants are increasingly being used to handle simple, look-up tasks in both business-to-consumer (B2C) and business-to-business (B2B) environments. The addition of chatbot assistants not only reduces overhead costs by making better use of support staff time, it also allows companies to provide a level of customer service during hours when live agents aren't available.
Chatbots can have varying levels of complexity, being either stateless or stateful. A stateless chatbot approaches each conversation as if it was interacting with a new user. In contrast, a stateful chatbot can review past interactions and frame new responses in context. Adding a chatbot to a company's service or sales department requires low or no coding. Today, a number of chatbot service providers allow developers to build conversational user interfaces for third-party business applications.
How chatbots work & How chatbots are changing customer experience
The quickly advancing digitalized world is adjusting and expanding client desires. Numerous buyers anticipate that organizations should be accessible every minute of every day and feel that the client experience gave by an organization is similarly as significant as the nature of items or administrations they give. Moreover, purchasers are increasingly educated about the assortment of accessible items and administrations and, thusly, are less inclined to stay faithful to a particular brand. Chatbots are a reaction to these changing needs and rising desires. They are supplanting live talk and other recently utilized types of contact, for example, messages and calls.
· Chatbots can possibly improve the client experience by:
· decreasing client holding up time and giving quick answers;
· providing clients with all day, every day client assistance;
· removing the risk of disagreeable human-to-human connections that are directed by the disposition and feelings of both the sercice or salesperson and the client;
· limiting the pressure and inconvenience that a few clients feel when reaching client care by diminishing hold up time and smoothing out the discussion;
· improving the redirection of client questions;
· propelling brand character by adding tweaked components to the chatbot; and
· customizing every client involvement in the utilization of AI-empowered chatbots.
Moreover, significant innovation organizations, for example, Google, Apple and Facebook, have formed their informing applications into chatbot stages that can deal with administrations like requests, installments and appointments. Moreover, when utilized with informing applications, chatbots present clients with the capacity to discover answers regardless of where they are and paying little heed to the gadget they're utilizing. The cooperation is additionally simpler in light of the fact that clients don't need to round out structures or waste minutes scanning for answers inside long substance.
Perhaps the most important aspect of implementing a chatbot is selecting the right natural language processing (NLP) engine. If the user interacts with the bot through voice, for example, then the chatbot requires a speech recognition engine. Business owners also must decide whether they want structured or unstructured conversations. Chatbots built for structured conversations are highly scripted, which simplifies programming but restricts the kinds of things that the users can ask.
In B2B environments, chatbots are commonly scripted and used to respond to frequently asked questions or perform simple, repetitive calls to action. In sales, a chatbot may be a quick way for sales reps to get phone numbers.
Types of chatbots
Since chatbots are still a relatively new technology, there is debate around the amount and classification of the available types. However, some common types of chatbots include:
Scripted or quick reply chatbots - These are the most basic chatbots; they act as a hierarchical decision tree. These bots interact with users through a set of predefined questions that progress until the chatbot has answered the user's question. Similar to this chatbot is the menu-based chatbot that requires users to make selections from a predefined list, or menu, to provide the bot with a deeper understanding of what the customer is looking for.
Keyword recognition-based chatbots - These chatbots are a bit more complex; they attempt to listen to what the user types and respond accordingly using keywords picked up from customer responses. Customizable key words and AI are combined in this bot to provide an appropriate response to users. Unfortunately, these chatbots struggle when faced with repetitive keyword use or redundant questions.
Hybrid chatbots - These chatbots combine elements of menu-based and keyword recognition-based bots. Users can choose to have their questions answered directly, but can also access the chatbot's menu to make selections if the keyword recognition process produces ineffective results.
Contextual chatbots - These chatbots are more complex than those listed above and require a data-centric focus. They use ML and AI to remember conversations and interactions with users, and then use these memories to grow and improve over time. Instead of relying on keywords, these bots use what customers ask for and how they ask it to provide answers and self-improve.
Voice-enabled chatbots - This type of chatbot is the future of chatbot technology. Voice-enabled chatbots use spoken dialogue from users as input that prompts responses or creative tasks. They can be created using text-to-speech (TTS) and voice recognition application program interfaces (APIs). Current examples include Amazon Alexa and Apple's Siri.
Future of chatbots
Chatbots are required to keep developing in popularity. A review from computer software company Oracle found that 80% of brands plan to incorporate chatbots by 2020.
Artificial intelligence and machine learning will keep on developing, offering new abilities to chatbots and presenting another degree of content and voice-empowered client encounters that will keep on changing the client experience. These enhancements will likewise affect information collection and will offer further client experiences that can prompt prescient purchaser practices.
Voice solution are relied upon to turn into a typical and important piece of the IT environment. Expanded spotlight is being set on building up a voice-based chatbot that can go about as a conversational operator, comprehend various dialects and react in that equivalent language.