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.[1] 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.[2] The term "ChatterBot" was originally
coined by Michael Mauldin (creator
of the first Verbot)
in 1994 to describe these conversational programs.[3]
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.[4][5] 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.