Top 10 Use Cases of Conversational AI for Enterprises

• By Sanjeev Verma
• 21-08-2023
• Artificial Intelligence

Conversational AI is rapidly gaining popularity as one of the most sought-after technologies in the Artificial Intelligence domain. Businesses across various industries are increasingly adopting it to enhance team management and deliver better customer service, all while maintaining a competitive edge.

In fact, the conversational AI market is projected to grow significantly, expanding from USD 10.7 billion in 2023 to reach USD 29.8 billion by 2028, exhibiting a forecasted Compound Annual Growth Rate (CAGR) of 22.6% during the period.

Why is So Much Hype Around Conversational AI for Enterprises?

The catch is businesses recognize that without artificial intelligence, their customer service might fall short, leading to potential customer dissatisfaction and loss. To overcome these challenges, many companies have turned to conversational AI solutions, which have shown promising results.

Surveys reveal that integrating conversational AI chatbots into business communication channels has contributed to higher CSAT scores and improved customer experiences.

Conversational AI is now considered essential for businesses aiming to enhance customer service and operational efficiency. Organizations that integrate AI into their multi-channel platforms are projected to experience a 25% increase in operational efficiency by 2025.

Its numerous advantages make it a preferred choice for simplifying and automating customer support worldwide. The adoption of conversational AI has proven to be a strategic move for businesses, enabling them to deliver better customer experiences while optimizing their operational processes.

How Does Conversational AI Work?

To enable a conversational AI chatbot to provide appropriate responses to human users' questions, several essential steps must be undertaken by a chatbot development company.

A. Input and Analysis

The initial step involves processing the input, which in this context refers to the question asked by the user. This processing is accomplished through two key components: Natural Language Processing (NLP) and Natural Language Understanding (NLU).

NLP ensures that the input is coherent, checking for correct spelling and word usage, while NLU undertakes the more complex task of comprehending the meaning behind the words used in the input.

B. Create a Response

After comprehending the user's query, the conversational AI utilizes Natural Language Generation (NLG) - another form of computing - to craft a well-formed and natural language response.

The emphasis on "natural language" is a prevalent aspect in the process of conversational AI, ensuring that the chatbot's responses resemble human language for a more engaging user experience.

C. Personalize the Response

The true brilliance of AI-powered chatbots emerges at this stage. The combined capabilities of NLU, NLP, and NLG allow conversational AI chatbots to generate personalized responses that align with a user's intent, preferences, and tone.

This level of customization and natural language interaction is unattainable for chatbots lacking AI capabilities. It is the synergy of these AI components that enables chatbots to deliver tailored and engaging conversational experiences to users.

D. Analyze the Response

Following the delivery of a response to the user, the AI conducts a thorough review of both the original input and the provided answer to ensure coherence and relevance. Through this iterative process, conversational AI continuously learns and evolves, becoming more intelligent over time.

This enhanced intelligence enables the AI to deliver increasingly personalized responses to even the most intricate and complex user queries.

Top 10 Conversational AI Use Cases

Given the industry trends and needs, business leaders sought to implement AI in the following areas:

1. Interactive Voice Assistants

Source: Cognigy

Interactive Voice Assistants, powered by advanced speech recognition and natural language understanding, offer a hands-free and seamless user experience. They can automate tasks and provide customer support through voice interactions.

For example, Amazon's Alexa and Google Assistant are both IVAs that are widely used by consumers. Enterprises can use IVAs to provide similar services to their customers, 24/7. This can help to improve customer satisfaction and reduce the workload of customer service representatives. A car rental company implements an Interactive Voice Assistant in its mobile app, allowing customers to book vehicles, check availability, and get directions using voice commands while driving.

2. Data Insights

Source: Qlik

Conversational AI can extract valuable insights from large datasets quickly and efficiently. It empowers business users to access data-driven information without the need for specialized data analysis skills. This ensures faster decision-making, data-driven strategies, and improved business performance.

Conversational AI can even be used to collect data about customer interactions. This data can then be used to improve products and services, identify trends, and target marketing campaigns.

This form of is AI not just limited to customers; enterprises can use conversational AI to improve their products or performance. For instance, a retail chain deploys conversational AI to analyze sales data and provide managers with instant insights on top-performing products, customer trends, and sales performance.

3. Employee Training and Onboarding

Source: ebm

Conversational AI simplifies employee training and onboarding processes by providing consistent and scalable training materials. It can answer employee queries, guide them through company policies, and streamline the learning process. It ensures faster onboarding, reduced training costs, and consistent knowledge dissemination.

For instance, as an AI development company, we’ve created a chatbot to train new hires on programming languages, development practices, and company procedures, offering interactive learning and immediate feedback.

4. Account Management

Conversational AI can be used to manage customer accounts. This can include tasks such as updating account information, processing payments, and resolving billing issues. It streamlines processes, reduces wait times, and offers 24/7 support for users.

For example, a telecommunications company could use conversational AI to allow customers to update their account information, make payments, and troubleshoot technical issues. This can help to improve customer satisfaction and reduce the workload of customer service representatives. As a result, the company can enjoy improved customer experience, increased efficiency, and better customer retention.

However, integrating conversational AI with backend systems and ensuring data security are significant challenges. Enterprises would need to partner with an AI development company for this. Partners like Biz4Group know the best architecture for conversational AI and how to integrate it into the existing enterprise ecosystem.

5. Authenticating Customers

Conversational AI solutions can employ biometric verification, voice recognition, or other advanced techniques to authenticate customers securely. This reduces the risk of unauthorized access and enhances security.

For example, a bank could use conversational AI to authenticate customers when they login to their online banking accounts. This can help to prevent fraud and protect customer data.

6. Booking and Reservation

Source: BotStar

Conversational AI simplifies the booking and reservation process by understanding customer preferences and providing real-time updates. It reduces manual intervention and enhances user convenience.

I've seen travel companies deploying a chatbot on their website to assist customers in booking flights, hotels, and tours, providing personalized recommendations based on individual preferences. And being the customer, I liked the convenience. Hopefully, more and more enterprises will adopt this conversational AI use case.

7. Intent Detection

Conversational AI with intent detection capabilities improves user experience by understanding the context and purpose behind user queries. It leads to more relevant and accurate responses where customers are directed to the correct resources and their questions are answered promptly.

For example, a customer service chatbot could use intent detection to determine if a customer is asking about a product, making a complaint, or requesting help with a technical issue. This information can then be used to route the customer to the appropriate department or resource.

If you wonder how it works – the chatbot analyzes the meaning of the user's input and determines the intent based on the context of the conversation. For example, if the user's input is "I want to buy a new phone," the chatbot might infer that the user is trying to make a purchase.

8. Multilingual Support

Conversational AI with multilingual support enables businesses to cater to a diverse customer base globally. It improves customer satisfaction and expands market reach.

For example, telecommunications companies could use conversational AI to provide support in multiple languages. This would allow customers to speak to a representative in their preferred language, regardless of where they are located.

9. Troubleshooting

Conversational AI assists users in troubleshooting technical issues with products or services, providing step-by-step guidance. It reduces the load on human support agents and enhances customer service.

A conversational AI chatbot can significantly assist enterprises in troubleshooting by offering a range of benefits:

• First, it reduces the workload on IT support staff by handling simple troubleshooting queries, allowing human agents to focus on more complex issues.
• Additionally, the chatbot's availability 24/7 ensures continuous support, leading to improved customer satisfaction with prompt responses and assistance.
• Moreover, the automation of troubleshooting tasks by chatbots helps cut down the overall cost of troubleshooting, making operations more efficient.

By leveraging natural language processing capabilities, chatbots can better understand customers' queries, leading to more accurate and personalized troubleshooting advice.

Furthermore, these intelligent bots can proactively monitor systems and applications, swiftly identifying potential issues and notifying the IT team, enabling prompt resolutions before customer experiences are impacted.

10. Payment Management

Conversational AI offers valuable assistance to customers in payment management tasks, encompassing setting up automatic payments, modifying payment methods, and addressing billing-related concerns.

Moreover, customers can rely on conversational AI to gain clarity on their bills or invoices, receive guidance on payment procedures, and resolve any discrepancies that may arise.

I can clearly envision an online retail store using a chatbot to assist customers in making purchases, handling payment options, and providing payment confirmation details securely.

Best Approaches to Implement Conversational AI

Conversational AI Chatbots, in particular, have the potential to revolutionize the entire customer experience and business operations. Previously in this article, we’ve discussed the versatility of conversational AI in transforming and enhancing enterprise operations.

Use Automated Ticket Classification for Customer Service

To initiate the process of resolving customer issues, companies can employ artificial intelligence techniques such as natural language processing (NLP) and machine learning (ML) to identify problems. By automating social media monitoring and tracking customer activity across various channels, businesses can efficiently respond to customer complaints and avoid potential criticism.

Chatbots play a crucial role in this process by routing inquiries to the relevant departments through automated ticket classification, based on keywords extracted from NLP-processed tickets. Leveraging conversational AI for recognizing and analyzing customer queries enables brands to swiftly address issues, leading to an optimized and streamlined customer support process.

Suggest Responses Proactively

Most customer inquiries are simple and can be efficiently handled by standard chatbots. However, when faced with complex questions, conversational AI can provide helpful suggestions, easing the burden on customer service agents.

Chatbots can assist agents by thoroughly analyzing the intent behind customer inquiries and offering relevant customer information, significantly reducing the time required to resolve and close issues.

Employing conversational AI platforms enables businesses to deliver a world-class customer service experience by automating call routing to the appropriate departments and facilitating seamless agent hand-offs when needed.

Make Use of Data Analysis

Conversational AI platforms come equipped with comprehensive analytics dashboards, empowering businesses to scrutinize every aspect of chatbot interactions. This includes tracking customer satisfaction, identifying the number of satisfied customers who have their issues resolved, and understanding where customers may leave the website or other touchpoints feeling content with the resolution.

With the flexibility to measure metrics based on their specific needs, businesses can even access customized dashboards tailored to display the most relevant information. Chatbots can play an essential role in gathering customer survey forms and feedback, allowing companies to maintain a close track of their customer satisfaction ratings.

Focus on CSAT

Conversational AI engages in an iterative learning process, continuously improving its intelligence over time. After providing a response to a user, the AI analyzes both the original input and its own answer for coherence and relevance.

This learning loop allows conversational AI to evolve and deliver ever-more personalized and accurate responses to complex user queries, enhancing the overall user experience.

Conclusion

Having explored the benefits and implementation of artificial intelligence in enterprise operations, it becomes evident why its adoption is critical for businesses at present.

Conversational AI not only improves customer support but also facilitates data-driven decision-making, enhances customer satisfaction, and strengthens overall business performance. As customer expectations continue to evolve, embracing AI-powered customer service becomes indispensable for staying competitive in today's dynamic market.