This is the age of automation and self-learning machines — and conversational AI is enabling machines to understand the spoken human languages and respond to them. Developments in deep learning and natural language-based processing also have the power to create game-changing customer experiences. This is amply highlighted by platforms such as Mihup which has already handled over 100 million customer interactions for numerous respected clients including some Fortune 500 brands. Conversational AI assistants are taking things far beyond the simple chatbot responses to deliver a number of services to customers autonomously. For instance, you can get a lost bank card blocked, request for a product servicing, register a complaint, and generate invoices, among other things directly from the chat window. At the front end, almost all major B2C companies are now adding tools such as chatbots into their websites. However, due to lack of focus on revamping the backend analytics of customer interactions, the true potential of big data is not being realized by the chatbots.
Despite having been around for only a few years, chatbots have become commonplace now and their range is quite limited. A chatbot is essentially a text interface operating on pre-defined linear interactions which makes them useful for performing specific functions only. Further, they operate on a canned version of information with a pre-defined flow of conversation/set of responses. Hence, unless the user puts in specific inputs, chatbots can turn out to be an irritant instead of real help. They offer responses based on the database, don’t learn, and can’t generate contextual information based on their past-conversations. A regular chatbot:
· Is keyword-based
· Provides 24/7 access
· Gives pre-defined responses
· Helps in faster setup and activation
· Provides a limited set of responses
Conversational AI platforms like Mihup offer automation of written as well as spoken communication in a natural, near human way. A platform like Mihup Automated Virtual Agent (AVA) — Call Center integrates machine learning, deep learning, natural language processing and predictive analytics to create one holistic experience for the consumers and the brands. It offers a host of features to the users such as the following.
· Ability to understand natural languages
· Round-the-clock deployment
· Ability to respond in natural human like manner
· Easy and quick activation
· Can be trained to handle thousands of customer intents
· No limit to scalability
· Ability to handle multiple languages simultaneously
· Seamless integration with different APIs
Natural Language Processing Advantage
The basic rule to assisting a person is to understand what they need and this is where machine learning has unlimited potential in discovering the customer intent. When coupled with natural language processing, these smart conversational platforms are able to seamlessly communicate between machines, services, customers and service providers etc. Mihup has built three key products to fulfil different needs through the usage of voice AI and AI powered interaction analytics.
Depending on the use cases, you can deploy them to respond to customers as Automated Virtual Agent — Call Center or use them to analyse the recorded customer conversations and generate actionable insights for business process enhancement. Similarly, Mihup also offers AVA-Auto, an in-vehicle virtual assistant that can control various vehicle functions automatically by simple voice commands. The USP of Mihup’s technology is that it can understand natural conversations, English, Hindi, Bengali languages as well as a mixture of any two or all three of these. If you are keen to optimize your business performance and customer satisfaction, choosing voice AI over a chatbot might be the best option for you!