The last decade or so has seen a paradigm shift from clicks to conversations in the way we interact with friends, family and even businesses. From messaging apps, to voice assistants, people now increasingly use conversational interfaces not only to communicate, but also to get things done.
It is against this backdrop that Conversational AI has emerged as a powerful tool for enterprises to engage and serve their customers.
The term ‘Conversational AI’ refers to technologies that automate communication and create personalized customer experiences at scale. A Conversational AI solution includes an interface such as a messaging app, chatbot or voice assistant, which customers use to communicate with the AI.
Businesses can use Conversational AI platforms to automate a wide range of customer-facing touchpoints – including their website, app, social media platforms such as Facebook and Twitter, messaging platforms such as WhatsApp, or voice assistants such as Google Home or Amazon Alexa.
While ‘chatbot’ is frequently used to refer to Conversational AI solutions, the term tends to have a limited ‘text-only’ connotation. Conversational AI is a broader term that is more inclusive of conversational solutions, across text and voice.
The earliest chatbots were simply programmed with scripted responses based on a limited number of predefined user inputs (in the form of specific keywords and phrases). These chatbots lacked the ability to learn and were unable to retain context between sessions. They were typically used to automate very basic tasks, such as responding to FAQs.
The advent of Natural Language Understanding (NLU) and Machine Learning (ML) proved to be the turning point in the evolution of the technology.
NLU is what allows Conversational AI to understand a user, regardless of the user’s choice of words. This enables the user to chat with the AI much as they would with a human agent, without being confined to specific keywords and phrases.
ML, on the other hand, allows the AI to train itself on the basis of conversational data. With every customer interaction, the AI becomes more adept at interacting with customers and catering to their needs.
It is owing to NLU and ML that conversational interfaces have evolved from mere ‘chatbots’ to ‘Intelligent Virtual Assistants’ – sophisticated, interactive and truly ‘intelligent’ interfaces that are not bound by a ‘company script’ but have the ability to truly put your customers’ needs first.
Interested in learning more about the evolution of Conversational AI?
Delivering exceptional customer experience is the key to lasting success for any brand. But the on-ground realities often do not live up to this age-old wisdom. Many businesses continue to be plagued by the same customer experience issues, which in turn adversely impacts their brand.
To begin with, it often takes simply too long for customers to get hold of a customer care representative on the phone or through email. This is a very frustrating experience for a customer, particularly one who requires instant assistance. To make matters worse, even when a support agent does come online, they are unable to dedicate much time and attention to solving a customer’s problem. In some cases, they may even lack the knowledge and competence to do so.
These problems stem from the conventional customer support model, which is heavily dependent on contact centers staffed by human agents. These support agents can only help a limited number of customers in a day, and spend a large part of their time resolving the same routine, repetitive queries. This leaves them unable to dedicate time and attention to helping customers facing more complex issues.
Implementing a Conversational AI solution solves these problems for brands:
In addition to enhancing customer experience, Conversational AI can help a brand slash 90% of its support costs – with a single AI Assistant being able to handle the same volume of queries in a month that would require 600 human agents. A business can massively scale up their customer support capacity to deal with increased query volumes in virtually no time, and with no additional expense, if they have implemented a Conversational AI solution.
Businesses across verticals have successfully implemented Conversational AI solutions. Take a deep-dive into the key Conversational AI use cases for each sector with the resources given below.
Conversational AI enables you to drive sales by bringing the experience of interacting with an in-store sales clerk to the virtual world – understanding customer requirements, offering personalized recommendations and strengthening purchase intent . An AI Assistant can enhance post-purchase experience for customers by answering FAQs, and resolving user queries around refunds & cancellations, order tracking, payment etc.
5 Reasons Top E-commerce Businesses Have Made Chat Their Primary Customer Service Medium. From improving user experience, to scaling up support, learn why leading online retailers have increasingly turned to Conversational AI to serve their customers. Read More
4 Ways Conversational AI is Transforming Retail. Immersion, speed, convenience and automation are the pillars of the tech-driven retail revolution. Learn how Conversational AI helps retailers with this. Read More
Conversational AI enables you to automate the entire customer journey from acquisition to support. An AI Assistant can understand your customer’s financial requirements and make personalized recommendations based on their profiling, driving account registrations. You can boost the efficiency of your customer support, by using the AI Assistant to answer FAQs, offer account information, and resolve service requests in real-time.
4 Chatbot Solutions For The Financial Services Industry. From scaling up support, to driving sales through intelligent lead generation, learn about some of the Conversational AI solutions that have been implemented by Financial Services brands. Read More
Chatbots in Banking – Examples, Best Use Cases and the Future. Banks have always been early adopters of new technology. Learn about some of the innovative Conversational AI solutions implemented by banks across the globe. Read More
Conversational AI can enhance customer experience by serving as a virtual travel agent for your customers, interacting with and advising customers on their preferred communication channel, be it Website, Messenger or WhatsApp. With an AI Assistant you can offer real-time post-purchase support and resolve queries around booking issues, itinerary changes, local attractions, web check-ins, refunds & cancellations, and more.
4 Ways Chatbots Are Transforming the Travel Industry. Learn why travel & hospitality brands have increasingly turned to Conversational AI to engage and serve their customers. Read More
Conversational AI allows you to triple user engagement and boost retention through personalized content recommendations based on customer intent and previous data. With intelligent prompts and relevant updates, nurture users with relevant content throughout the buyer journey. An AI Assistant enables you to offer 24/7 support, answering queries around subscriptions details, payment issues etc.
4 Use Cases for Conversational AI in the Media & Entertainment Industry. From customer service, to content discovery, learn how digital media brands have leveraged Conversational AI as a powerful customer engagement tool. Read More
Conversational AI can be leveraged to effectively disseminate accurate and timely information about healthcare issues through an engaging interactive interface, as well as answer queries around these issues in real-time. Hospitals, clinics and other medical facilities can use AI Assistants to automate the response to frequently asked patient queries such as appointment bookings, report status etc.
Conversational AI in Healthcare: 2 Key Use Cases. Learn about two of the major ways healthcare providers can leverage Conversational AI – information dissemination and customer care – with case studies for each. Read More
Haptik’s Intelligent Virtual Assistant (IVA) solutions are powered by a full-stack Conversational AI platform, built to comprehensively solve business problems end-to-end, and at scale. You can learn more about the key components of our platform below.
A simple but powerful tool to build, train and deploy IVAs. The Dialog Builder provides a framework, and components, that enables you to build your own conversational flows with minimal effort. In fact, using pre-defined templates, it is possible to develop an IVA in as little as 4 hours using this tool.
The Dialog Builder operates on a node-based graph model and enables the creation of interconnected conversational flows. It also allows the integration of dynamic API’s to enable your IVA to tackle complex use cases. You can test your IVA and check for bugs and other issues in the conversational flow. Once the IVA is live, you can continue to use the tool to iterate and improve the solution on the basis of real data.
A dashboard which enables human agents to monitor conversations between the IVA and customers, and take over the conversation when necessary. It enables seamless auto-routing of conversations involving complex customer issues to human agents – using our proprietary chat assignment logic that is based on agent expertise and traffic.
The dashboard includes tools to help support agents in their resolution of customer queries, such as the ability to fetch user information from the CRM system and ‘Smart Actions’ (including sharing images, attachments, location etc.) It also facilitates monitoring of agent performance and efficiency, including metrics such as First response time and Resolution time
Provides access to real-time conversational analytics, enabling us to drive customer success by measuring and improving the effectiveness of our IVA solutions. The dashboard can be used for real-time review and resolution of issues, including automation failures and customer drop-offs.
It offers a deep-dive into conversations on the IVA, enabling granular analysis of the entire conversation, individual user messages, and even words used. By analyzing node traffic, it provides a detailed insight into how customers move through the conversational flow. The dashboard also provides a CSAT feedback score for all conversations.
The ‘brains’ behind the Conversational AI. Our NLU model has been developed using 3 billion+ consumer data points. It has been from the ground-up separately for Commerce and Customer Care – the two key business functions that Haptik caters to. The NLU Engine replicates the first principles of human behavior through algorithms while performing tasks.
Our Commerce Engine is equipped with industry-specific Domain Knowledge & Information Extraction, can carry out Sentiment Analysis of User Reviews, and make personalized product recommendations. Our Care Engine is equipped with advanced Intent Detection and Named Entity Recognition capabilities, as well as Disambiguation logic, to accurately pinpoint user intent. Both Engines include a Context Manager, to retain the overall context of the conversation, as well as specific user information collected during the conversation.
LEARN MORE: How Does a Chatbot Learn on Its Own?
In keeping with the principle of “Build Once, Deploy Anywhere”, Haptik’s IVA solutions are omnichannel, and can be used by brands to engage customers across a wide range of platforms. Our solutions are also CRM agnostic and can be seamlessly integrated into any Customer Relationship Management system.
What does it take to build a Conversational AI solution end-to-end?
Read our whitepaper to find out!