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Nine out of ten (9 out of 10) customers want a quick response from businesses — I know I do. This is why organisations worldwide are turning to chatbots and conversational AI to meet these demands.
Alexa, the well-known virtual chatbot, is the most basic example. They are sequential and do not transmit the conversation’s context from one to the next. This means they can’t have full-fledged conversations like humans, but they can imitate human speech patterns when programmed to respond to specific requests or trigger words.
On the other hand, smart chatbots and virtual assistants, such as Google Assistant and WotNot, leverage AI and machine learning to allow users to conduct longer and more contextual interactions.
What Conversational AI Is All About
Before we delve into this complex technology, let me explain what conversational AI is all about. It is artificial intelligence that enables machines to comprehend, process, and reply to human language. If you’ve ever done any online shopping, you’ve probably come across a chatbot.
Conversational AI includes speech-enabled applications that allow humans and computers to connect naturally. It’s a set-up that will enable a computer to speak like a human by detecting the context of speech and text, decoding other languages, and comprehending the intent.
These AI systems involve science and creativity to create effective applications that include relevance to human and computer interaction.
Different types of conversational AI include:
- Chatbots – A chatbot may imitate a dialogue with nearly human language through social media applications on many websites and messaging systems.
- Voice Assistants – Google Home and Amazon Echo have both benefited from the addition of a voice assistant. Voice assistants are now available in cars, household devices, cellphones, and a variety of other apps, in addition to speakers.
Key Components of Conversational AI
Natural language processing (NLP) and machine learning are combined in conversational artificial intelligence. It uses crucial components to decipher the context of what users say and interact with them in the most natural way possible.
- Machine Learning (ML) is a set of algorithms, features, and data sets that analyse human agent responses to better respond to the user.
- Natural Language Processing (NLP) — It allows you to “read” or parse human language material, which is necessary for recognising natural sentence structures rather than just keyword “triggers.”
- Integrations — Through Application Programming Interfaces (APIs) and other business operations tools, the systems can carry out end-to-end actions. These features allow for more independent actions.
Benefits of Conversational AI
Cuts Down Cost
Conversational AI lowers the company’s overhead costs significantly. Companies can reduce the number of people they hire for tech assistance, customer service, and other tasks by using chatbots and voice assistants.
Minimises Churn
The major goal is to assist clients in resolving their problems to promote customer satisfaction. Customers can also be directed to the next best step by using chatbot AI.
Boosts Revenue
Using a chatbot will allow employees to focus on selling products and services. Virtual agents carry out the most fundamental interactions. It’s critical to build products, offerings, and promotions based on customer preferences and annoyances.
Related: Can AI make customers happy?
