Chatbots portend a monumental transformation in how businesses engage with customers. The evolution of the chatbot dates back to 1950, when Alan Turing, regarded as the father of theoretical computer science and artificial intelligence, published a paper titled Computing Machinery and Intelligence. In it, Turing asked the most profound question at the time: “Can machines think?” That marked the beginning of a fascinating body of work that fuses human intelligence and smart machines. Joseph Weizenbaum then created ELIZA, regarded as the first chatbot, in the 1960s.
In the decades that followed, chatbots evolved rapidly along two primary paths, each marked by its underlying technical complexity and therefore the kind of interactions it’s able to handle.
Scripted chatbots and rules-based chatbots are more primitive forms that handle a limited scope of simple interactions. They operate on a set of predefined keywords, scripted responses, and decision tree-like flows. Simply, they respond only to specific commands. If you say something wrong, even by a little margin (e.g., a typo), they don’t understand what you mean.
The second form are artificial intelligence (AI) chatbots. They are powered by a number of advanced technologies including AI, natural language processing (NLP), and machine learning (ML). You don’t have to be specific when interacting with AI chatbots. They understand language as humans speak it, not just commands, and they continuously learn and get smarter with every interaction.
Let’s review AI chatbots, still deemed to be in their infancy, in more detail.
What’s an AI Chatbot or AI Virtual Assistant?
You can interact with an AI chatbot via text, voice, or both as you naturally do and get a meaningful response instantly. At its core, the bot has a brain powered by AI. It breaks down what you said, or typed, to identify words, sentences and even the sentiment. It then quickly analyzes the context (e.g., when a caller says “I’d like to book a table for two for dinner,” the bot understands that “book” means “reserve” and not a “publication”) to formulate a relevant response and/or follow-up action. Based on your preferences and past behaviors, the bot provides a personalized, conversational, human-like experience.
We already noted the bot has an AI brain. Along with it comes memory. It not only remembers conversations, but can also learn from them and improve over time. The more interactions, the smarter the bot becomes.
The most popular examples of AI chatbots include Apple’s Siri, Amazon’s Alexa, and Google’s Assistant.
Chatbot/virtual assistant AI: Key components
As you’d imagine, there is a lot going on behind the scenes of an AI chatbot. They’re hard to build, test, deploy, and optimize over time.
Today’s leading chatbots come with a set of seven key capabilities and components. The absence of, or weakness in, one or more can make or break your chatbot project. Consider this your little CX cheat sheet.
An AI Chatbot Offers Omnichannel User Interface
- Supports both voice-based and chat or text-based interfaces and has a customizable user interface (UI) of its own.
- Integrates with messaging platforms such as WhatsApp, Facebook Messenger, Google Business Messages, Apple Messages for Business, WeChat and more; based on your business strategy, you can deploy your bot in one or more channels.
- Supports rich input and output: For example, the bot understands emojis, and can send you rich multimedia content in response (e.g., pairs of shoes shown in a carousel).
- Captures voice, detects language, transcribes speech to text (natively or through an integration), and identifies and isolates speakers such as agent vs. customer, which is key to understanding who said what.
An AI Chatbot Offers Natural Language Processing
- Between capturing user input and generating a response, an AI Chatbot processes massive amounts of input; that’s where NLP comes into play. NLP is the bot’s ability to read or parse human language text.
- Uses NLP to process text captured by the UI or, for voice input, the text that’s converted by the speech-to-text (STT) capability.
- NLP analyzes sentiment to identify and categorize users’ opinions based on what they expressed about a topic/product/experience, etc.
- NLP massages user input: It fixes typos and understands slang, synonyms, unusual sentence structures based on how well it’s trained.
- NLP also contains a vocabulary for out-of-the-box use or it can be custom trained to suit your unique business needs (e.g., vocabulary for different industries or lines of business).
- Translates text from one language to another so it can be appropriately handled (e.g., French Canadian to English for analysis).
- May support unsupervised learning; the bot is not restricted to the training data and can learn in real time.
An AI Chatbot Offers Intent Recognition and Handling
- Understands user intent even when the query is structured in uncommon ways.
- Leverages machine learning to match the appropriate intent “handler”
- Contextualizes and groups intents into structured buckets to better guide the handler to formulate relevant responses
- Handles responses primarily via decision-tree flows, whereby certain intents trigger specific responses.
An AI Chatbot Offers Contextual Awareness
- Learns from previous conversations ad recalls and reuses that information in future, relevant conversations (e.g., customer prefers to be addressed by their first name only).
- Considers user context (e.g., page where the interaction is occurring) and user preferences (e.g., preferred delivery address set in an app).
- Uses data pulled from integrating with operational systems like CRM, billing, case management, etc.
- The stronger the capability, the more human-like and predictive the interactions.
An AI Chatbot Offers Response Generation
- Leverages natural language generation (NLG) to handle multiple intents in a single response (e.g., “I’m looking for a pair of blue denims, ideally a straight fit, in a 34 waist.”). The bot composes a single response that matches all the intents expressed.
- Supports text-to-speech in voice channels to relay back to the customer, often via an external service that integrates with the bot.
- Supports self-personalization, enabling you to add personality characteristics, generate human-like voice, and give it a style and tone that matches your organization’s values.
An AI Chatbot Offers Escalation Management
- Routes requests to a human agent, or an alternative handling method, when it cannot understand or handle an intent.
- This is crucial to ensure interactions although not fulfilled by the bot, gets the attention of another system or human
An AI Chatbot Offers Analytics and Monitoring
- Provides reporting insights, ideally in real time, into the bot’s performance.
- Offers information on intents that the bot was unable to handle so you can work on training the bots for those specific intents.
- Provides insight into the overall quality of interactions regarding intent matching, handling, and escalations.
What’s a Chatbot? Take the Next Step!
[24]7.ai™ offers everything you need to build, test, deploy, and continually optimize AI chatbots for your business. Use them to drive sales growth, supercharge experiences for customers and employees alike, and drive massive cost reductions through automation and self-service.
