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Into a new dawn of chatbots- Conversational with human feel
Into a new dawn of chatbots- Conversational with human feel

September 21, 2022

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Wasn’t your last chat with a chatbot a bit mundane? And mechanical? But that’s what our experience has been with chatbots, isn’t it? Haven’t we imagined that our conversation with a chatbot can be just as lively as with a friend? A chatbot taking on an anthropomorphic form with sentient abilities is an illusion. But Google’s LaMDA (Language Model for Dialogue Applications) chatbot promises to breach the perimeter of our perception. And change the way we relate to digital machines. LaMDA is Google’s system for building chatbots based on its most advanced large language models, so called because it mimics speech by ingesting trillions of words from the internet. The future of communication with a chatbot is multimodal. The transition from text only to text plus video with a conversational feel! The gap between man and machine conversation may be narrowing swifter than what we thought.

From Menu to Voice bots- here’s how they have evolved

Initially designed to ease workloads and divest people of cumbersome processes, chatbots have come a long way. With chatbots, companies can provide clients with effective and immediate customer service regardless of their location. Customers can express the highest level of customer service available to address any of their needs when organizations eliminate particular hours from the equation. In 2021, the Global Chatbot Market was valued at USD 521 Million, and by 2030, it is forecast to reach USD 3,411 Million, growing at a CAGR of 23.7% from 2022 to 2030. Chatbots started off as menu or button-based chatbots. They allow the user to choose from a variety of options that are shown as menus or buttons. Depending on what the user clicks, the bot will present them with a different set of options to choose from.

Then came keyword recognition-based chatbots that could hear what users are saying or typing. They employ customizable keywords and AI to determine how to react appropriately. Natural Language Processing (NLP) is the technology used by chatbots with keyword recognition to help their users.

The evolution touched an epochal phase with Machine Learning (ML) chatbots. For instance, a contextual chatbot that enables users to place pizza orders will learn the user’s preferred ordering preferences by storing the data from each conversation. This means that eventually, whenever a user chats with this chatbot, it will remember their most frequent order, their delivery address, and their payment details and will only prompt them to repeat this transaction. The ultimate in CX is offered by Voice Chatbots. Voice chatbots record, decode, and understand audio input from speakers to answer in a way similar to natural language. AI chatbots allow users to engage with them using voice commands and receive contextually relevant responses.

The Market Segmentation and Key Players 

In terms of application, the market is divided into bots for social media, bots for service, bots for marketing, bots for payment and order processing, and others. AI, marketing, and human intelligence are the categories based on the product landscape. Meta, Pandorabots, Inc., ToyTalk (PullString Inc.), Google Inc, Yahoo Inc, Haptik Inc, Helpshift, Kasisto Inc, Slack Technologies Inc, Astute Solutions, Kiwi, Inc, and Microsoft Corporation are some of the key players in the global chatbot industry. 

Chatbots will fuel the CX engine in future

In the future, personalized messaging will emerge as one of the foremost channels of customer acquisition and retention. Add to this, the crying need for a secure layer of privacy, and bots are your best bets for communication. Omnichannel messaging will become critical for brands and multimodal chatbots will be crucial for customer engagement. Gartner predicts that by 2027, chatbots will become the primary customer service channel for roughly a quarter of organizations worldwide. The future of communication is arriving faster than you thought. 

The article was first published on CSM Blogs.


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