Sourav Chowdhury
Principal Enterprise Architect – Insurance at Tech Mahindra
Definition of Conversational AI: Conversational AI is targeted towards executing automated conversations between computers/machines/bots and humans. Being communication-centric, the technology finds natural use-cases in different industrial domains ex: marketing, sales, or customer service frontends in the form of messaging apps, chatbots, and voice-based assistants. By mimicking the essences of human conversations, users get the impression that they are communicating with a human agent instead
of a program, eventually resulting in Hyper personalized user experiences. Ease of use and better accessibility turned conversational AI from a mere trend to a technological pillar. To begin using Conversational AI, a great starting point is to integrate applications/systems with Natural Language Processing (NLP) and Machine Learning (ML). This empowers the tech to accurately interpret user conversations and automatically respond with relevant answers, based on previous experience of interpreting test data samples. Not only does this improve business processes, but it also improves communication experiences at user-ends.
Note: In current context, “User” represents the set of consumers experiencing/utilizing Conversational AI services, relevant to any business domains.
Business reaction towards Conversational AI: Most of the leading businesses today will move ahead of such behavioral shifts and make use of Conversational AI to enhance communication between users and employees. Target benefits of using tools like chatbots, voicebots, interactive interfaces etc:
● Increased user satisfaction and productivity
● Growth in revenue and sales
● Improved user satisfaction across business domains
Merging of Conversational AI and Intelligent Automation: the convergence of Conversational AI and Intelligent, smart automation creates an extended omni-channel experience that is purely meant to facilitate faster, more personalized and responsive customer service.
● Organization to streamline both internal and user-facing processes and incorporate automation when possible.
● Seamless End-to-End Automation utilizing Enterprise Service Bus (ESB), Robotic Process Automation (RPA), or Business Process Management (BPM) practice. Through conversational automation, next-level user interactions can be created with native process automation integration.
● Using an open integration Technology framework, organizations can leverage existing integrations for Kofax, Automation Anywhere, UiPath, BluePrism, SAP, and many more.
● Companies, new to Conversational AI, a smart strategy would be to use it to create a simple FAQ bot (or virtual assistant) and then gradually move toward transactional or conversational automation. It is advised to follow a “learn as you go” model and work on building a repeatable process for new AI projects within organization.
● Seek to make data-driven decisions that are based on user inputs. It pays (both in short and long terms) to learn what users are struggling with and address their most profound concerns via AI analytics.
● Bridge the gap between Intelligent Automation stack through Hyper Automation
Benefits of intelligent automation powered Conversational AI: Users are much more familiar with technology, from streaming platforms to after-sales services, the main point of contact with most preferred brands is somehow handled through AI and response has become immediate, so they demand instant resolution and more control over the process. This is why integrating Conversational AI into the customer service process has become kind of mandatory.
● Win over target Audience
o Nothing strengthens user bonds more than timely and efficient service. Consumers value ability to provide a good experience as much as they value the quality of product or service. It's essential to answer their queries instantly if user retention is the goal and they fall in love with brand providing such experience. Users are demanding these days: if service offering doesn’t meet their expectations, they might choose different product/brand/services.
● Round the clock efficient service
o With Conversational AI, all communication channels are available to the user 24/7. That feeling of quick and constant support is key for users these days. There's nothing more frustrating than waiting hours to solve an urgent problem, explaining the same problem to different operators in different conversations, or having to guess if a product is available or not. Conversational AI becomes a possibility for many consumers whenever they need: purchasing, sorting out paperwork, solving problems or asking questions.
● Answers across all channels
o It's no surprise that people like to communicate over instant messaging or on their favorite social media site. Whether users contact on Instagram Messenger or send a WhatsApp audio, businesses need to have the ability to answer.
o Automating customer service across all channels with Conversational AI lets businesses offer a personalized and complete service for each interaction while staying true to company's voice and tone. Answers can be further enhanced with complements like videos, carousels, buttons or forms, to create a cooler experience.
● Privacy and security
o Guaranteeing secure transactions and protecting users' data is a fundamental part of the service on digital channels. Key elements for offering good service include a security incident management policy, data isolation and data protection in compliance with privacy and auditing regulations. Integrating AI gets essential when it comes to guaranteeing the detection of threats and handling them correctly.
● Superior personalization
o One of the best benefits of having bot with Conversational AI is personalization: knowing user, having a clear profile and being able to offer them a product or service according to their needs will provide significant competitive advantage.
o Integrating AI lets to provide the right answer for each user in an empathetic way and make recommendations based on their preferences. The more personalized the service, the greater are chances of converting prospects into users.
● Valuable Metrics
o Conversational AI helps to increase sales, provides more insights about target audience and gives them what they really need anytime, anywhere. This becomes possible with increased volume of Data captured through AI.
o Getting real-time metrics, reports and statistics on user satisfaction is easier than it sounds and is a key part of a true user-centric service. This way, organizations get valuable information and can make data-driven business decisions.
● Reduce Customer Service Cost
o Automation in customer service helps to optimize time, among other things. The bot can handle FAQs, manage processes, sales and after-sales service, while the call center or agents can be ready to deal with complex cases.
o Plus, with several no-code/Low-code solutions available to choose from, companies save on implementation and getting started: anyone from any team in organization can set up the bot, without having to hire an outside provider or create a new IT team.
Conversational use cases in the Insurance Industry:
With conversational AI and machine learning, users who wish to purchase an insurance policy, renew an insurance policy, issue a claim, or pay a premium can easily do so.
Additionally, an insurer using AI technology can improve the customer support provided by a human agent. Here are various use cases in which conversational AI can improve the insurance sector.
1) Use Keywords to Observe Opportunities and Trends: Conversational AI can:
a. Identify upselling and cross-selling opportunities
b. Pinpoint which phrases lead to a sale
c. Highlight what leads to call drop-offs
d. Scan calls at scale without skyrocketing costs etc.
2) Improve Agent Performance:
a. Simple search for a keyword in a conversation from past user interactions, and AI can find the call transcript needed.
b. Can turn highly satisfactory calls into scripts to use as a learning tool for new agents.
c. Using recordings as a script can make training and evaluating call center employees easy, as can maintain a standard script for everyone. These recordings will also help to confirm if a human agent follows script properly.
3) Automate Redundant Queries:
a. The most repetitive and frequently asked questions can be automated thanks to conversational AI solutions
b. These systems provide the first level of support for incoming queries through an AI chatbot or interactive voice response (IVR), giving users self-service options, like an interactive Q&A with a virtual assistant to make users aware of an insurance claim or policy details.
c. This enables a live agent to tend to more critical tasks that benefit the insurance customer and generate revenue for the company.
4) Provide a Constant Communication Thread:
a. With a conversational AI platform, Users can talk to the same insurance agent, regardless of being cut off or losing connection.
b. These applications are employed primarily if an insurance provider uses asynchronous communication, such as commonly used messaging platforms like WhatsApp.
c. For insurance firms, offering asynchronous communication options to users is invaluable, as AI and human insurance agents may not resolve every query on their first attempt.
5) Better User Experience with 24/7 Assistance:
a. Conversational AI platforms implementing Natural Language Processing (NLP) can offer real-time assistance to your human agents to quickly answer insurance user queries through live chat, an AI insurance chatbot, etc. This can reduce user call duration and boost user satisfaction and retention.
b. A chatbot can handle calls even when a live agent isn’t available. It does this by assuming the role of a virtual agent, giving the user suitable prompts and redirects.
6) Lead Profiling and Conversion Optimization:
a. When users provide specific inputs, AI-driven insurance chatbots can categorize user data depending on age, income group, risk, job stability, etc.
b. AI bots can also help capture the full context of a potential user’s needs and wants. The user-generated data can help sales teams spot promising leads and achieve better
conversion rates.
Conversational AI- Beyond FAQ bots: Due to recent technological advancements, Conversational AI bots lie poles apart from simple FAQ bots. Here are the leading factors that set them apart:
● Uses natural language processing to understand user needs
● Understands the context and nuances of every conversation
● Solves problems instead of doubling as a search engine
● Engages and connects with users through personalized conversations
● Makes use of automation capabilities to bridge process gaps
Working method of Conversational AI: In order to enable companies to develop and successfully operate chatbots and to constantly adapt them to the needs of the users, a suitable conversational platform must cover many different functional areas. This is the processing of natural language, integration possibilities and functionalities to operate the virtual assistants.
Conversational AI is a critical component of a Metaverse Experience:
Metaverse is characterized as an expansive virtual space where users can interact with 3D digital objects and virtual avatars in a complex manner that mimics the real world.
However, it will require a plethora of new technologies, protocols, enterprises, breakthroughs, and discoveries. It will develop gradually over time as various products, services, and capabilities connect and meld.
● By merging augmented and virtual reality (AR/VR) with artificial intelligence, the metaverse will create scalable and realistic virtual worlds. This combination would undoubtedly open the door to incredible experiences, but it would also raise many questions, such as how brands would enter, operate, and survive in this metaverse, what role digital humans will have in this digital world, and how will customer service function in a newly minted metaverse?
● The metaverse is uncharted ground for any industry. If big tech experts are correct about the metaverse being the successor to mobile, customer service might well become virtual-first and this fuels the need for Conversational AI.
o Conversational AI: Bridging the gap between virtual and real
o Sophisticated virtual characters are key for immersion
o An immersive world for business channels
o Concierge services will move the horizon from chatbots to digital humans
o The metaverse is still away, but parts of it can already be felt
