In 2023, conversational AI is on the rise. ChatGPT, an AI-powered chatbot, has won over millions of people and thousands of businesses worldwide. A powerful conversational AI platform can truly transform your business, so if you haven't yet, you should get on board soon.
In this blog post, we explore the concept of conversational AI and the ways businesses can benefit from it. We also give tips on how to successfully implement a conversational AI solution and explain the difference between chatbots and conversational AI.
What Is Conversational AI?
Conversational AI is technology that enables computers or software to engage in human-like conversations. Conversational AI uses artificial intelligence (AI) and natural language processing (NLP) techniques to simulate human conversation. They are designed to understand and answer questions, provide relevant information, and respond in a way that feels natural and human-like. Conversational AI solutions can take the form of chatbots, virtual assistants, voice assistants, or messaging platforms.
Conversational AI relies on advanced algorithms and machine learning techniques to process and analyze language, learn from previous interactions, and generate appropriate responses. It continually improves through training on large amounts of data, allowing it to improve its performance over time.
Conversational AI Use Cases
Businesses can use conversational AI in various departments to improve efficiency, enhance customer experience, and streamline operations. Here are some examples of how conversational AI can be applied across different departments:
Conversational AI for customer service
Conversational AI in the form of chatbots or virtual assistants can handle common customer inquiries and provide round-the-clock customer support. Since they can handle multiple tasks at once and access large datasets in seconds, conversational AI solutions reduce customer wait times, improve service availability, and enhance customer satisfaction.
Conversational Al for sales and marketing
Conversational AI supports sales and marketing teams by engaging with prospects and providing personalized recommendations based on historical data. The primary goal of sales virtual assistants is to automate and streamline processes, but they are also useful for capturing customer data that can later be used for targeted marketing campaigns.
Conversational AI for market research and analytics
Conversational AI can be used to collect customer feedback, conduct surveys, and gather market insights. AI-powered chatbots can engage users in conversations and find out what they feel and think about your product. Conversational AI analytics can then be applied to analyze these interactions and extract actionable customer insights.
Conversational AI for HR
HR processes can also benefit from conversational AI by automating routine tasks and providing self-service options for employees. For example, AI-powered chatbots can handle employee onboarding, assist with benefits enrollment, answer HR policy questions, and provide information about company policies.
Conversational AI for IT support
In IT support, conversational AI can be used to troubleshoot common technical issues. Chatbots or virtual assistants can help employees resolve basic IT problems, such as password resets, software installations, or network connection issues. By offering immediate round-the-clock support, conversational AI improves overall response times and boosts employee satisfaction.
Conversational AI voice bot
A voice bot is a type of conversational AI that uses natural language understanding (NLU) to interpret speech commands and respond to them. Also known as conversational interactive voice response (IVR), this technology provides businesses with an additional way to interact with customers and make customer experience more convenient. One of the most well-known conversational AI examples, Siri and Amazon Alexa, are actually voice bots.
Conversational AI vs Chatbot
Chatbots and conversational AI are often used to perform similar tasks, so it can be difficult to tell them apart and decide which solution is right for you. Essentially, both chatbots and conversational AI are designed to streamline simple interactions with the help of NLP techniques. NLP allows chatbots and conversational AI to understand user input, process it, and give an appropriate response.
While conversational AI is a broader concept and can take many forms, chatbots are more simple and have limited capabilities. Conversational AI employs advanced AI and ML techniques to handle more complex and sophisticated conversations. Chatbots, on the other hand, can range from simple rule-based bots to more advanced bots with limited AI capabilities. Since chatbots rely on predefined rules or patterns, they are usually designed for specific use cases, such as customer support, lead generation, or e-commerce. Conversational AI systems are more complex, flexible, and versatile, so they can be integrated across various platforms. Besides, they also learn and adapt over time, improving the quality of responses and interactions over time.
Conversational AI strategy
Creating a successful conversational AI strategy requires a deep understanding of customer needs and your business’s capabilities. Here are some additional tips on how to implement an effective conversational AI program.
Incorporate human handoff
There are scenarios where even sophisticated conversational AI is not enough. Your AI system should be able to recognize them and transfer the customer to a support agent. During the handoff, AI should provide the agent with the necessary content and relevant materials that can help resolve the issue.
To stay effective, conversational AI needs constant refining and updating. Analyze user feedback, monitor the performance of your solution, and update the system whenever your product goes through a major upgrade. Besides, keep an eye on the new trends in AI and NLP to stay on top of your conversational AI game.
Support multiple languages
Allowing customers to interact with your AI in their preferred language is a great way to demonstrate your dedication to providing seamless customer experience. Conversational AI can usually detect a customer’s preferred language by accessing their IP address or browser settings. Some solutions can translate their responses themselves, while others might require training in different languages.
Best Conversational AI Platforms
If you want to start using conversational AI software, look into these solutions that are widely considered to be the best options on the market.
- IBM Watson Assistant
- Google Dialogflow
- Amazon Lex
- Oracle Digital Assistant
- SAP conversational AI
Conversational AI Analytics
Interactions with conversational AI tools can be a valuable source of customer data for any business. Through conversational AI analytics, businesses can analyze data and extract insights from conversations between users and conversational AI systems. Conversational AI analysis allows businesses to gain a deeper understanding of user behavior and improve the performance of the conversational AI system.
Behavior analysis can help companies discover the type of queries users have and the paths they take in conversations. Such data is useful for identifying user intent and areas for improvement for the AI system. To assess customer satisfaction, businesses can also use sentiment analysis techniques.
To get a holistic understanding of customer experience, businesses should analyze user feedback received through various channels alongside conversational AI data. If you’re looking for a straightforward feedback analysis tool, Essense might be a perfect fit for you. Upload your sources, generate multi-source reports, and get ready-to-use customer insights for your business.