https://www.techtarget.com/searchcustomerexperience/definition/chatbot
A chatbot is a software or computer program that simulates human conversation or chatter through text or voice interactions.
Users in both business-to-consumer (B2C) and business-to-business (B2B) environments increasingly use chatbot virtual assistants to handle simple tasks. Adding chatbot assistants reduces overhead costs, better utilizes support staff time and enables organizations to provide customer service around the clock.
Chatbots range from simplistic models that operate off of scripts to provide quick responses to specific questions, to artificial intelligence (AI) and machine learning (ML) models that can converse with users and complete more complex tasks. Chatbots also simulate human conversation in either written or spoken form.
How a chatbot works depends on the type of chatbot. Early chatbots followed predefined scripts. In a customer support setting, this included commonly asked questions with corresponding answers. The chatbot would look for a set of keywords a user would input and it would respond with the corresponding information. This type of chatbot couldn't interpret natural language or answer complex or unscripted questions.
More modern chatbots can use AI and ML to be much more flexible. These chatbots use natural language processing (NLP) and natural language understanding to interpret user inputs and respond similarly. They also use ML and large language models to learn and improve their service.
Chatbots have varying levels of complexity, being either stateless or stateful. Stateless chatbots approach each conversation as if interacting with a new user. In contrast, stateful chatbots can review past interactions and frame new responses in context.
Adding a chatbot to a service or sales department requires no or minimal coding. Many chatbot service providers use developers to build conversational user interfaces for third-party business applications.
A critical aspect of chatbot implementation is selecting the right NLP engine. If the user interacts with the bot through voice, for example, that chatbot requires a speech recognition engine.
The organization implementing the chatbot must also decide whether it wants structured or unstructured conversations. Chatbots built for structured conversations are highly scripted, which simplifies programming but restricts what users can ask. In B2B environments, chatbots are commonly scripted to respond to frequently asked questions or perform simple, repetitive tasks. For example, chatbots can enable sales reps to get phone numbers quickly.
Organizations looking to increase sales or service productivity might adopt chatbots for time savings and efficiency, as AI chatbots can converse with users and answer recurring questions. These services are also typically available 24/7.
As consumers move away from traditional forms of communication, many experts expect chat-based communication methods to rise. Organizations increasingly use chatbot-based virtual assistants to handle simple tasks, allowing human agents to focus on other responsibilities.
Chatbot use is increasing in business and consumer markets. As chatbots improve, consumers have less cause for dispute while interacting with them. Between advanced technology and a societal transition to more passive, text-based communication, chatbots help fill a niche that phone calls used to.
Chatbots such as Eliza and PARRY were early attempts to create programs that could at least temporarily make a real person think they were conversing with another person. PARRY's effectiveness was benchmarked in the early 1970s using a version of the Turing Test; testers only correctly identified a human vs. a chatbot at a level consistent with making random guesses.
Chatbots have come a long way since then. The implementation of ML and other AI processes prompted a major step forward for chatbots in the early 2000s. ML and NLP processes found their way into several technologies in the 2010s, such as IBM Watson, Amazon Alexa and Apple Siri. Chatbots like Alexa and Siri, which focus on understanding natural language through voice, have become prominent AI assistants.
The next jump in chatbot technology occurred in 2016 with transformer neural networks -- also called transformer architectures. Chatbots like ChatGPT use this and neural network architectures. These chatbots require massive amounts of data to be properly trained. However, the transformer architecture is more efficient when compared to feedforward neural networks.
As chatbots are still a relatively new business technology, debate surrounds how many different types of chatbots exist and what the industry should call them.
Some common types of chatbots include the following:
The integration of ML and AI has increased the quality and function of chatbots. Rule-based chatbots, by comparison, can only give simplistic responses to specific questions. These systems are limited by their understanding of language and follow predefined scripts. AI-powered chatbots, however, can understand and respond to users in a much more natural sense because of their ability to process natural language.
Integrating chatbots with AI also enables chatbots to learn from their interactions with users. These chatbots learn from the data they collect to then provide increasingly accurate and personalized answers.
Chatbots have been used in instant messaging apps and online interactive games for many years and only recently segued into B2C and B2B sales and services.
Organizations can use chatbots in the following ways:
The rapidly evolving digital world is altering and increasing customer expectations. Many consumers expect organizations to be available 24/7 and believe an organization's CX is as important as its product or service quality. Buyers are more informed about the variety of products and services available, making them less likely to remain loyal to a specific brand.
Chatbots serve as a response to these changing needs and rising expectations. They can replace live chat and other forms of contact, such as emails and phone calls.
Chatbots can enhance CX in the following ways:
In addition, major technology companies, such as Apple, Google and Meta, have developed their messaging apps into chatbot platforms to handle services including orders, payments and bookings. When used with messaging apps, chatbots let users find answers, regardless of location or the devices they use. This interaction is also easier because customers don't have to fill out forms or waste time searching for answers within the content.
Chatbots provide many benefits for customers and companies. For example, improved CX and more satisfied customers due to chatbots increase the likelihood that an organization will profit from loyal customers.
Other benefits include the following:
While chatbots improve CX and benefit organizations, they also present the following challenges:
Chatbots won't be fully replacing humans in contact centers any time soon; however, the technology will continue to improve, evolve and grow in relevance.
Although public sentiment toward AI replacing human jobs is currently viewed negatively, many people still choose to interact with chatbots in scenarios like asking simple-to-answer questions on a product page. Likewise, many people interact with a chatbot before being transferred to a human. In these cases, it's common for the chatbot to collect data on user inquiries and then direct them to the right department.
Many experts expect chatbots to continue growing in popularity. In the future, AI and ML will continue to evolve, offer new capabilities to chatbots, and introduce new levels of text and voice-enabled user experiences that will transform CX. These improvements could also affect data collection and offer deeper customer insights that lead to predictive buying behaviors.
Voice services have also become common and necessary parts of the IT ecosystem. Many developers place an increased focus on developing voice-based chatbots that can act as conversational agents, understand numerous languages and respond in those same languages.
Chatbots are a technology that has grown and improved over time. Learn more about the evolution of chatbots and generative AI.
01 May 2024