Conversational AI Use Cases to Enhance Engagement and Efficiency

According to Zendesk CX Trends research, approximately 67% of consumers prefer voice-based interactions with AI and chatbots. Moreover, the demand for this advanced technology has been growing, and its market value is expected to reach $32 billion by 2030.

Conversational AI applications such as chatbots and virtual assistants have significantly impacted businesses’ operational systems. This technology supports companies in enhancing agent productivity, addressing customer issues faster, and reducing costs.

In this article, we’ll outline the definition, benefits, and popular conversational AI use cases to help businesses properly align this technology with their current operational system.

What is a Conversational AI?

Conversational AI is the technology that enables chatbots and virtual agents to interact with users naturally. It combines machine learning and natural language processing with a large volume of data to create human-like text responding to users’ queries.

In detail, the algorithms under a conversational AI platform allow the tool to recognize users’ text inputs and generate relevant results in multiple languages. Practically, various businesses have applied this technology in diverse domains, such as financial services, healthcare, retail, and sales and marketing.

Two components contributing to conversational AI’s mechanism include machine learning and natural language processing (NLP). Machine learning models are essential for developing and adapting AI platforms with different inputs. Meanwhile, NLP improves natural language understanding by analyzing language through a 4-step process, ensuring accurate and relevant answers to users’ queries.

Benefits of Conversational AI Solution

Conversational Artificial Intelligence benefits businesses in terms of internal and external operating processes. Here are typical advantages of Conversational AI that enhance companies’ operational systems.

Increase Customer Engagement and Satisfaction

Conversational AI tools facilitate 24/7 support to quickly answer user queries, satisfying customers with less waiting time. The supporting process will be more interactive due to the advanced messaging techniques. Specifically, conversational bots can generate carousels for product displays and embedded apps for seamless integration with external services to enhance customer experience.

Provide More Personalized Experiences

Customers’ demographics, actions, and other previous interaction data can guide conversational AI tools to provide personalized experiences for users. Typical approaches to personalizing each user’s buying journey include recommending relevant products to end users, tracking and updating orders’ status, and supporting in person.

Support Human Agents and Reduce Operating Costs

Conversational AI can relieve human workload by handling routine tasks effectively, reducing hiring and training costs for AI-domain staff. Various small- or medium-sized companies leverage virtual assistants and chatbots to respond automatically to simple user queries.

Conversational AI technology can help businesses allocate human agents to higher-value tasks requiring strategic-level skill sets to deal with complex user queries. The internal business team will have more time to deliver more value for customers, increasing Return on Investment.

For example, Unity, a leading 3D development platform, successfully implemented AI-driven ticket deflection solutions to automate routine inquiries and prioritize critical issues. This strategic decision resulted in a $1.3 million cost reduction and an 83% improvement in first response time.

Boost Sales Revenue

By personalizing customers’ purchasing experience, conversational AI tools can accelerate their time considering the right products, increasing the average order value. Moreover, businesses can upsell by recommending add-on products that might not be in customers’ initial consideration.

This approach is an organic way to sell products without providing customers with overpromising sales pitches and also allows businesses to target the correct audience.

Improve Accessibility for Customers

Conversational AI enables businesses to address diverse cases for different types of users. Indeed, it can accommodate a wide range of users, from AI experts to those with limited technical knowledge. It can also support multilingual interactions and address non-standard use cases, enhancing user satisfaction.

For example, users can quickly become familiar with a new website or mobile app through detailed instructions provided by artificial intelligence tools. By leveraging Generative AI technology, users can obtain answers to their questions and locate desired information efficiently, regardless of their technical proficiency.

Differences Between Traditional and Conversational AI Chatbots

While traditional chatbots serve as navigators, guiding users to relevant pages based on pre-defined terms, conversational AI is more about helping users learn, understand, and solve issues with back-and-forth interactions. The table below will clarify the differences between traditional and conversational AI bots regarding functions and requirements.

6 Conversational AI Use Cases

Conversational AI platforms earn applications in various domains, from simple customer support to complex operations. The top industries businesses have leveraged conversational AI platforms to enhance customer experience.

1. Conversational AI in Financial Services

Due to the expectation to reach 73% of digital banking in 2024, more financial services invest in conversational AI to offer users self-service options. These applications help businesses give their customers the flexibility to interact with employees when needed.

Conversational AI chatbots support financial services in the following use cases:

• Support human resource management: Streamline HR operations by automating repetitive tasks like onboarding and ticket generation. This practice empowers HR managers to focus on strategic initiatives like enhancing employee satisfaction and gathering valuable feedback to drive insightful organizational change.
• Monitor security awareness: Provide personalized feedback, address employee inquiries, and deliver timely notifications about cybersecurity updates and best practices. This proactive approach promotes better compliance with security guidelines and empowers employees to make informed AI-driven decisions.
• Support employee education: Enhance employee education by providing personalized learning experiences, tracking progress, and generating performance reports. Similar to the DuoLingo model, it can also automate lessons, quizzes, and interactive conversations to improve employee skills and knowledge retention.
• Replace FAQ sections: Traditional FAQ sections often lack specific and up-to-date information. Conversational AI chatbots offer a dynamic solution by engaging in real-time conversations, delivering tailored responses, and adapting to changing information. Businesses can ensure accurate and effective customer support by continuously training these AI assistants with new data.

2. Conversational AI in Banking

American Bankers Association’s survey estimated that 48% of US bank customers utilized mobile devices, and 23% used online banking through a laptop or PC. This significant number of digital customers has promoted businesses to invest in AI technology and other fintech solutions. For example, organizations like JP Morgan Chase are optimizing their operations by transitioning from labor-intensive call centers to more efficient AI-powered systems.

Here are typical use cases for integrating conversational AI platforms to enhance customer experience without mitigating data security:

• Provide voice-based virtual assistants: Deliver 24/7 support, automate tasks, and resolve inquiries.
• Report fraudulent activities: Enhance security via monitoring access attempts, detecting suspicious activity, and implementing fraud prevention measures like voice biometrics to safeguard customer accounts.

3. Conversational AI in Healthcare

More businesses allocate their budget to conversational AI platforms to adapt to higher expectations of customers when approaching healthcare service providers. This technology eases booking appointments, managing documents, and checking patients’ insurance, leading to a higher satisfaction score.

However, a Pew Research Center survey found that 60% of Americans express discomfort with healthcare providers that are over-reliant on AI. This fact requires healthcare providers to guarantee the involvement of healthcare professionals in delivering services.

The applications of conversational AI in the healthcare domain include:

• Automate administrative tasks: Handling routine tasks, offering self-service options, and answering patient inquiries can address staffing shortages and improve patient experience.
• Improve hospital logistics: Facilitating communication and providing real-time insights. Consequently, it enables healthcare professionals to prioritize critical cases and deliver timely care.
• Gather patient insights: Analyzing patient interactions to identify trends, improving resource allocation, and increasing patient experience.

4. Conversational AI in Retail

Due to more consumers engaging in online shopping and seeking personalized services, retailers are turning to AI-powered chatbots and virtual assistants to boost customer experiences. A Statista survey indicates that 34% of retail consumers are comfortable using AI chatbots to locate nearby stores, access daily deals, and track order statuses.

By leveraging natural language processing and ML models, these conversational AI solutions can provide real-time support, answer queries, and recommend relevant products to drive customer satisfaction and loyalty.

Practically, retailers use conversational AI systems to generate customer data insight, recommend relevant products, enhance multi-channel support, and track inventory automatically.

5. Conversational AI in Customer Service

Conversational AI chatbots help businesses automate customer support in various actions, such as booking tickets, scheduling appointments, managing orders, or supporting billing. According to the Tidio survey, 62% of customers prefer interacting with chatbots over human agents to experience faster response times. This shift increases customer satisfaction and brand loyalty through efficient communication channels.

Conversational AI platforms can enhance customer experience in the following use cases:

• Support the travel industry: An intelligent virtual assistant can help users book flights and manage appointments or reservations with minimal effort. Moreover, it can support human agents in answering customers’ queries, such as traveling with a pet or a baby.
• Manage billing and complaints: The virtual agent can provide real-time assistance, offer additional services, and resolve complaints efficiently while engaging with customers.

6. Conversational AI in Real Estate

Conversational AI assists real estate firms in tracking deals efficiently and increasing sales. Practically, this technology contributes its benefits to the following use cases:

• Identify upsell/cross-sell opportunities: Identifying upsell and cross-sell opportunities in real time enables businesses to drive revenue and enhance customer satisfaction.
• Make better recommendations: Revolutionizing real estate by analyzing vast amounts of data to provide personalized property recommendations, enhancing customer satisfaction and engagement.
• Record and analyze calls: identify sales patterns, improve agent performance, and optimize sales strategies to enhance real estate operations.

How to Develop Conversational AI Models

A well-designed conversational AI model should address different issues in human interactions and relationships between vendors and clients. The following roadmap will help companies cover all considerations to align the models with businesses’ goals and objectives.

1. Establish Discovery Phase

The initial phase involves collaborative discussions between the delivery manager, AI architect, and business analyst to define the client’s needs, goals, and pain points. This information is used to develop a detailed product vision, outlining features, platform selection, and project scope. Throughout this process, transparent and regular communication with stakeholders is crucial to align expectations, and in some cases, it may include a simple product demo.

2. Training Conversational AI Model

Developing a sophisticated conversational AI requires extensive data training. AI trainers feed the model with large volumes of data, including diverse queries and requests, to enable it to recognize intent and sentiment for appropriate responses. Concurrently, developers integrate the AI into the company’s systems, configuring triggers for seamless interaction with users and system processes. This collaborative effort ensures the AI delivers a human-like experience without compromising system functionality.

3. Conduct User Experience Testing

The team rigorously tests the conversational AI’s performance, response time, and adaptability to diverse queries. Simultaneously, user experience testing is conducted to ensure intuitive and seamless integration with websites and messaging platforms. Stakeholder feedback is invaluable throughout this phase in refining and aligning the AI’s capabilities with user expectations.

4. Implement Post-Production Support

Post-deployment monitoring and technical support are crucial for the ongoing success of a conversational AI. AI trainers play a pivotal role in mitigating data and concept drift by continuously updating the model with relevant data and adapting it to new situations. This proactive approach ensures the AI’s accuracy and effectiveness in assisting users, safeguarding the company’s workflow and operations.

Develop Conversational AI Models Effectively with Neurond

Conversational AI solutions are rapidly transforming industries by revolutionizing customer interactions, automating tasks, and providing personalized experiences. Neurond leverages advanced AI techniques to develop intelligent chatbots and virtual assistants that can understand and respond to natural language, analyze complex data, and make informed decisions.

Integrating conversational AI into your business can enhance customer satisfaction, increase efficiency, and gain a competitive edge in today’s digital landscape. Contact Neurond today to explore how our AI solutions can help your business thrive.