Back in the 1960’s Joseph Weizenbaum developed the first chatbot ‘ELIZA’ within MIT’s Artificial Intelligence Laboratory. A giant leap for technology, ELIZA was able to simulate computational understanding without any machine learning capabilities utilizing pattern recognition algorithms. From those days there has been a considerable growth in how technology interacts with mankind. It was 2016, that witnessed the true chatbot craze with Facebook’s announcement to offer a developer-friendly platform to build chatbots on Facebook messenger. With this announcement, chatbots were envisaged as the next stage of the conversational revolution.
The Advent of Conversational Revolution
The early experimental days of Conversational AI’s have bought innovative brands think beyond chatbots, voice skills and smart speakers. This has bought multi-device and multi-modal engagements that are driven by contextualized and intelligent intelligence.
Owing to recent developments, digital disruption has influenced the chatbot industry for good. The revolutionary technologies of deep learning and natural language understanding (NLU), has made chatbots smarter, sharper elevating a customer’s experience into something truly transformational.
Conversational chatbots armed with Machine Learning help businesses across geographies to better serve the needs of their customers. Applications of AI-powered chatbots range from commerce, customer services, healthcare and many more industries. AI-powered chatbots lead conversions, help to increase order size or volume, improve customer retention, enhance and encourage revenue generation avenues.
Business geographies have gone much beyond traditional chatbots which assisted with service, support, guidance, and recommendations. Today’s dynamic business needs are different, that requires Conversational AI to work in the background with agents helping them access caller history and increase response accuracy customised to each customer.
The Technology behind Conversational AI
Conversational AI is powered by Machine Learning (ML) algorithms training systems to learn automatically thus improving their performance over time. Conversational AI improves the chatting experience of the user by consistently asking questions to improve its responses. Conversational AI employs various machine learning methods which allow developers to train algorithms capturing data from conversations, operationalize it and ultimately turning it to actionable insight. Machine Learning involves Deep Learning (DL) with its neural networks enabling the mechanical brain behind chatbots to operationalize the available data with higher accuracy to draw better conclusions.
Based on the understanding levels, the chatbots of today are categorised into different levels, ranging from level 1 to level 5.
Level 1: This is the initial level of intelligence. At this level, the chatbot is essentially only a traditional notification assistant which can answer basic questions based on pre-built responses. These chatbots will send notifications involving any events and remind you about things which you are interested in like assisting you with a link to book a flight ticket.
Level 2: At this level, chatbots can answer basic FAQs and handle a simple follow up, like booking insurance along with the ticket.
Level 3: Chatbots at this stage are programmed to engage you with conversations based on your preferences, to offer more than prebuilt answers. The chatbot understands the context and offers tailor-made solutions for instance, a travel bot can offer a few popular destinations and even help with travel arrangements.
Level 4: The bots become more intelligent at this level, and offer you solutions that are more personalised to your preferences. Like booking an airport cab at a time suiting to you.
Level 5 and beyond: These chatbots are the most intelligent, and can monitor and manage changes that influence the enterprise operations like offering tailor made promotions, targeting customers based on historical trends, thus increasing the conversion rates and revenue aspects.
The Era of Intelligent Experience
Conversational AI essentially backed by emotional capabilities continue to shape engagement, connectivity and communication experiences. Conversational AI can interact with multiple platforms, thus bringing the Omnichannel world even closer. The superiority of Conversational AI lies in their adaptability. If built with the right purpose and objectives conversational bots can deliver additional by-products which include –
- Interactive Dashboards
- Intelligent Data Insights
- Purchase and Sales Data
- Historical Data about customer preferences
Conversational AI solution allows customers to have real, immediate interactions. Leading research shows that user’s value conversational AI interfaces more than the regular chatbots because they are intuitive, convenient and fast.
The leading research firm Gartner predicts that “40% of mobile interactions will be managed by smart agents by 2020.” thus explaining the important role these messaging apps will play. Taking customer preferences, users like to message more than talk on the phone and offer more inputs when engaged in emotional customised chats, which clearly explains why Conversational AI is superior than chatbots.
In the future times to come, chatbots powered by AI, NLP will be the game changer to enterprises. Investing in AI-powered Conversational AI surely fulfils a purpose. Embracing the Conversational AI chatbot technology makes for a long-term investment to reap the profits of the future.