Conversational AI is a part of Artificial Intelligence, that enables human-like conversation between the user and the machine. It allows human-like conversations between users with websites, applications, and devices with the help of Natural Processing Language(NLP) via texts, voice, commands.
8 Components of conversational AI:
Privacy & Security
Feedback Loops
Machine Learning Capabilities
Language Technology
Data
Content
Design
Value Proposition for User
When all of the components above are in place, a conversational AI experience can tap into many of the aspects that make human language such a versatile and rich communication medium.
Conversational AI works by understanding the different components of speech with respect to machine learning. By extracting entities ( day to day objects ) from the user’s utterances, we can identify or give a fairly good estimate of what the user wants. This is done by creating a machine learning model for a particular domain and making the user talk to the chatbot that becomes the subject matter expert, thanks to the machine learning model. TL; DR: Conversational AI uses Machine Learning to extract information from the user’s sentences.
CAI works by understanding user input via text or speech which is then processed via different NLP models to determine the intent and entities involved in the conversation. Further Machine learning is utilized to understand domain-specific user context to determine the appropriate response to be given to the users.
Chatbot, Virtual Assistant, or Digital Assistant are interchangeable terms mostly used to describe the automated interface used for automated conversation. Chatbot short for Chatterbot is an application that can be embedded on a website, messaging application, a smart speaker, or all. It is a computer application that enables automated conversations with humans.
Conversational AI can be used for automating customer engagement, customer support, employee engagement (HR Automation), and can also be used for automation of all enterprise business processes.
Artificial Intelligence is a simulation of human intelligence in machines that are programmed to think like humans and mimic human actions.
Machine learning is a part of artificial intelligence based on the theory that machines can learn with data, identifying patterns, and make decisions with minimal human intervention. Machine learning is a set of algorithms learned from data and/or experiences that automates analytic model building.
Natural language processing is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze large amounts of natural language data. NLP is an umbrella term that covers Natural Language Understanding (NLU), Natural Language Generation (NLG), and Dialog Management. It enables Conversational AI to make sense of a user’s language, and recognize their intent and give the appropriate response.
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised, or unsupervised. It is also known as Deep Neural Learning or Deep Neural Network.
Dialog Management is what drives conversation between machines and humans. Management of conversation is handled by Dialog Management in Conversational AI. Dialog management is to find a perfectly suitable response to a human dialog. Grounding the conversation, slot filling, carrying context are some of the key attributes that separate a good dialog manager from others. A dialog manager is a component of a dialog system, responsible for the state and flow of the conversation.
Sentiment Analysis is a part of machine learning and Natural Language Processing that helps conversational AI in classifying emotions of users within texts and voice data as positive, negative, or neutral and other complex emotions that are identified by the user input.
In case the Bot is unable to answer a user, it will seamlessly transfer the conversation to a Live Agent along with the context of the conversation without affecting the quality of the user experience.
General Data Protection Regulation states that businesses are accountable for the protection of their customer’s data. Yellow Messenger Conversational AI Platform complies with GDPR requirements.
Yellow Messenger’s Conversational AI platform leverages deep learning and natural language processing to respond to a wide range of questions in multilinguistic languages.
Yellow Messenger platform has gone through detailed security assessment and certified per OWASP guidelines. The platform has built-in capabilities to offer privacy.
Yellow Messenger has been catering to enterprise-ready Conversational AI needs for customer engagement, customer support, employee engagement, etc.
A good solution has a proven strategy for implementations and to adapt if required. Yellow Messenger not just provides the initial training required for implementations by the support and demo videos. But also is available, 24/7 in case of any query.
Yellow Messenger solution is implemented stepwise starting from testing to complete launch and also 2.0 version if required.
The Platform auto-scales depending upon the volume of interactions coming across from all channels. Our response time for interaction is <1 second.
“Every penny saved is a new investment made”. The cost-efficiency Conversational AI creates on the businesses is remarkable. Offering 360-degree Automation for both internal and external requirements making an impeccable scope of reducing human effort in various verticals including HR, Sales, IT, Marketing, Customer support, etc.
Yellow Messenger can equip you to enhance your businesses with Conversational AI.
Yellow Messenger caters to the following industry both at vertical and horizontal levels:
Our platform is industry agnostic and we have strong consulting experience across multiple different industries:
Automotive industry
Banking
Consumer Goods
Education
Energy and Utilities
Insurance
Media and Entertainment
Pharmaceutical and Healthcare
Real Estate
E-commerce
Telecommunication
Travel and Hospitality
The short answer is Yes! We have out of the box ready-made connectors for leading enterprise applications which help us in reducing the time to go live.
Yellow Messenger’s Conversational AI platforms can be integrated with any CRM in the market like Salesforce, Microsoft Dynamic 365, Zoho, Freshsales, etc
A smart Conversational AI is one that can be deployed seamlessly on any platform. Yellow Messenger’s Conversational AI solution can be deployed on 25+ channels like Facebook Messenger, Twitter, WhatsApp, Website, etc.
We are official partners for Whatsapp Business API globally.
The primary key points where conversational AI enhances the user experience are
No waiting time, User has the ability to access the right data through free text or voice in no time.
Frequently asked questions are handled more efficiently.
Constant Consistency
Optimal data collection
Omni-Channel experience, Customer queries can be handled on multiple channels.
Yellow Messenger is a pioneer in offering the most customizable platform experience, enabling the user to extract data and give analytics on the dashboard in the desired format and UI.
Our solution offers complete customizable analytics to enable business decisions based on the data.
1. Out-of-the-box bot analytics including the number of users, sessions, messages, journeys, etc.
2. Customizable conversational analytics to track the following KPIs
– Bot performance metrics like failure points, goal completion rate, etc. to train the bot further.
– MIS Reporting automation.
Aarti Nair
Aarti Nair is Marketing Manager for Yellow Messenger, an AI-based Cognitive Cloud Engagement Platform startup based out of Bengaluru, with the history of working with SaaS-based companies as a social media expert as well as a content creator.