A conversational user interface, or conversational UI, allows users to interact with a system using human language, either by text or voice. It incorporates natural language processing (NLP) and natural language understanding (NLU) to communicate with the user in a conversational manner.
In other words, interacting with this technology could be as easy as chatting with a friend.
And this is exactly where conversational interfaces can help you out with enhancing customer experience.
This time around, we’ll break down how these intuitive systems are revolutionizing user experiences.
Get ready to discover the technology behind chatbots, voice assistants, and much more.
In this article:
- How does a conversational UI work
- Types of conversational user interfaces
- Conversational user interface examples
- Benefits of using these technologies
- Best practices for implementing them
- Frequently asked questions
Use Tidio’s conversational interface chatbot and boost customer experience
Interested in exploring the topic of conversational AI? Check out these articles:
- What Is Conversational AI & How It Works? [Guide]
- Meet Lyro: The First Conversational AI for SMBs
- What Is Conversational Commerce? [Benefits & Examples]
First things first—
How does a conversational UI work?
When you interact with a conversational UI, it starts with a user typing or speaking their command or question. The system then takes this input and uses natural language processing (NLP) and machine learning (ML) to understand what the user means. Once it grasps user intent, it generates a relevant response.
Finally, the system delivers that response back to the person, whether it’s through text or voice, making the customer interactions feel seamless and intuitive.
Let’s explore the main components of conversational interfaces:
- Input interface—this can be text input where customers type their questions into a chat window, and voice input where users speak their commands using a microphone
- Natural Language Processing (NLP)—with this technology, the system identifies the user’s goal or intention behind the input
- Context handling—this component keeps track of the conversation’s context, managing the flow and making sure the system remembers previous interactions
- Response generation—based on the recognized intent and entities, the system decides what appropriate response it should generate
- Backend integration—this connects the conversational UI to external systems, databases, or chatbot APIs, i.e. if the user asks for the weather, the system will fetch the data from a weather service API
- Text output/voice synthesis—in the case of chatbots, the system presents the response as text in a chat window, while for voice assistants, the system converts the response into speech using text-to-speech technology
- Learning and adaptation—involves using machine learning to continually improve the system’s accuracy and efficiency by analyzing past interactions
By breaking down these components, you can see how each part plays a crucial role in making conversational interfaces as effective and user-friendly as they are.
Read more: Check out all you need to know about NLP chatbots. In addition, explore the topic of chatbot intents.
Okay—
What about the specific types of conversational interfaces?
Conversational interface types
Conversational interfaces come in a variety of forms, each with its own unique advantages. From chatbots that handle customer service inquiries to voice assistants that manage your daily tasks, these tools keep transforming the way people interact with technology.
Let’s dive into the different types.
Chatbots
Chatbots are perhaps the most familiar type of conversational interface. You’ll find these text-based helpers on websites, within messaging apps, and sometimes as standalone applications. They come in two main types of chatbots: rule-based and AI-powered chatbots.
- Rule-based bots
These bots follow a set of predefined rules, which makes them perfect for handling routine queries or guiding customers through specific tasks. This means that interactions are based on fixed questions and answers.
For instance, if you inquire about store hours, the chatbot might present options like “Monday-Friday,” “Saturday,” and “Sunday” before providing the relevant details. They often rely on recognizing specific keywords to trigger responses.
As such, they’re highly effective for straightforward tasks such as answering FAQs or guiding users through simple processes.
Read more: Learn all about the benefits of using an FAQ chatbot for your business, as well as its different types and use cases.
- AI chatbots
On the other hand, AI chatbots are more advanced, using machine learning and natural language processing to understand and respond to more complex queries. They even learn from each interaction to get better at helping you over time.
These chatbots analyze the user’s input to determine the intent behind the message, even if it’s phrased in various ways. For instance, no matter if you ask “What’s the weather?” or “Can you tell me the weather?”, the chatbot understands that you’re seeking weather information in both cases.
Additionally, they can remember previous interactions in the same conversation, providing coherent and contextually relevant responses. AI chatbot interfaces also learn from each interaction, constantly improving their understanding and capabilities.
This allows them to handle a wide range of questions and more complex queries, making them suitable for personalized customer support, detailed product recommendations, and conversational commerce.
Read more: Check out the core differences between chatbots and conversational AI interfaces. Also, be sure to find out the distinctions between chatbots vs. virtual assistants.
Improve your customer service efforts with conversational AI chatbots
Voice assistants
Voice assistants bring the conversation to life through spoken language. These assistants are typically built into smart speakers, smartphones, and a variety of other IoT devices.
They excel at recognizing and processing your voice commands, converting their responses from text to speech, and even remembering the context of previous conversations to keep things seamless.
These can further be divided into virtual and IVR assistants.
- Virtual assistants
They are the more familiar type of voice assistant, integrated into devices like smartphones, smart speakers, and even cars. Think of Apple’s Siri, Microsoft Cortana, Alexa, and Google Assistant.
These systems are designed to handle a broad range of tasks through conversational dialogue. They can set reminders, assist businesses in scheduling meetings, control smart home devices, play music, answer questions, and much more.
- Interactive Voice Response (IVR) systems
IVR systems are often used in customer service settings, such as when you call a company’s support line and interact with an automated menu. Unlike virtual assistants, which are designed for a wide array of tasks, IVR systems are typically programmed for specific functions related to customer service and support. They can route calls to the appropriate department, provide information and data about account balances, or guide customers through self-service options.
Read more: Learn all you need to know about virtual shopping assistants and using them in your online business.
Hybrid interfaces
Hybrid conversational interfaces combine the best of both worlds by integrating text and voice interactions within the same system.
Imagine that you’re interacting with a smart assistant through a mobile app. You might start by typing a message to find a nearby restaurant, and then seamlessly switch to speaking your next command to make a reservation. This allows you to engage with the interface in the way that feels most natural to you at any given moment.
What makes hybrid interfaces so powerful is their adaptability. They can handle text inputs when you’re in a quiet environment, but switch to voice when you’re on the go or multitasking. This means you’re not limited to just one mode of interaction, making the experience more fluid and intuitive.
For example, a hybrid customer service bot can chat with you via text on a website to troubleshoot an issue, and then escalate the conversation to a phone call if things get too complicated.
Okay—
Let’s go ahead and explore the more hands-on use cases of these technologies.
Conversational UI examples
Whether it’s booking a flight, chatting with customer support, or even controlling your smart home devices, conversational UIs blend seamlessly into various aspects of people’s personal and professional lives.
Let’s explore some practical use cases to see just how versatile and beneficial conversation interfaces can be.
Customer service chatbots
Customer service chatbots are perhaps the most widespread use of conversational UIs. They can answer frequently asked questions, help solve common issues, and guide customers through various processes such as account setup or product returns. These bots offer instant support, reducing the wait time for customers and freeing up human agents to handle more complex queries.
Tidio’s Lyro, an AI-powered customer service chatbot is a perfect example of such a technology. It can provide answers to user queries in a natural manner by pulling the knowledge from an FAQ base.
Read more: Find out how Tidio’s support team achieved 58% automation using Lyro. Also, while you’re at it, be sure to learn how to create a FAQ using Tidio’s Lyro.
Ecommerce assistants
In the world of online shopping, conversational UIs serve as personal shopping assistants. They can recommend products based on your preferences, help you find specific items, and even assist you with the checkout process.
Imagine a chatbot helping you select the perfect outfit by showing you options based on your style and previous purchases. Or even a shopping bot providing a customer with steps on how to pick a perfect shirt size using your shop.
Read more: Explore the best ecommerce chatbots for your online store. Moreover, check out how chatbots for business can benefit your organization.
Virtual healthcare
Healthcare is another sector where conversational UIs are making a big impact. Virtual assistants can help schedule appointments, provide medication reminders, and even offer simple medical advice based on symptoms you describe.
They can also triage symptoms and direct you to the appropriate care, whether it’s booking an appointment with a doctor or suggesting over-the-counter medication.
Smart home control
For smart home enthusiasts, voice assistants like Amazon Alexa and Google Assistant offer unmatched convenience. You can use voice commands to control lights, thermostats, security systems, and more. These assistants can also integrate with various third-party services to play music, set reminders, and even order groceries.
Travel planning
When it comes to planning travel, conversational UIs can make the process much smoother. From finding flights and booking hotels to providing travel recommendations and itinerary management, these interfaces can handle it all.
For instance, you could ask a travel assistant to find the cheapest flights for your chosen dates, recommend hotels in your destination city, and even suggest activities and restaurants to check out while you’re there.
These examples show just how versatile and beneficial conversational UIs can be across different industries and applications. Whether you’re looking to enhance customer support, streamline shopping experiences, or manage your home, conversational interfaces provide a natural and efficient way to interact with technology.
Read more: Explore different chatbot use cases and examples.
With that out of the way, let’s check out key benefits of using these intelligent virtual assistants.
Business benefits of conversational user interfaces
Conversational interfaces offer a range of advantages that can significantly enhance customer experience and streamline operations.
Check out the reasons why these interfaces are becoming increasingly popular across various industries.
- 24/7 availability—AI user interfaces can operate around the clock, ensuring users get assistance anytime they need it, regardless of time zones or business hours. This is especially important since a whopping 83% of customers prefer to receive immediate assistance upon contact.
- Cost efficiency—by automating routine tasks and customer service inquiries, businesses can significantly reduce operational costs while allowing human agents to focus on more complex issues.
- Scalability—these interfaces can handle multiple queries simultaneously, making it easier to scale customer support without compromising quality or response times.
- Personalization—AI-based conversational UIs can offer personalized experiences based on user information and past interactions, leading to enhanced customer satisfaction. In fact, according to research, AI-powered conversational interfaces increase CSAT scores by an average of 12%!
- Improved user engagement—by providing a more interactive and engaging way to interact with technology, conversational UIs reduce friction and make the user experience more enjoyable. In fact, as many as 89% of users would want to buy from a company again after one positive experience.
Finally, let’s take a look at strategies you can implement to make the most out of this technology.
Best practices for using a conversational user interface
Implementing a conversational user interface can significantly enhance customer engagement and streamline various processes. However, to maximize its effectiveness, it’s essential to follow some best practices.
Here are tips that will help you design a conversational UI that offers a seamless user experience:
1. Focus on user experience
Prioritize creating an intuitive and engaging user experience. Use natural language and a human-like chatting style that feels conversational, and ensure the system can handle various ways users might phrase questions or commands. Incorporate context awareness so that the interface remembers previous interactions, making the conversation feel more fluid and coherent.
2. Balance automation with human touch
While customer service automation offers efficiency, it’s essential to provide an easy way for users to escalate issues to human agents when needed. Your conversational interface should provide options for speaking with a real person, especially for complex or sensitive matters. This balance enhances user trust and ensures they don’t feel abandoned by the technology.
Read more: Find out the benefits and main features of chatbot automation.
3. Provide multichannel support
Modern users interact with brands across multiple platforms, from websites and mobile apps to social media and messaging services like WhatsApp and Facebook Messenger. A robust conversational interface should be capable of seamlessly operating across these various channels.
Multichannel customer service allows users to engage with the chatbot wherever they are most comfortable, providing a consistent and uninterrupted experience. By integrating the chatbot into multiple touchpoints, businesses can ensure they are accessible to a broader audience.
Read more: Find out how to create a WhatsApp chatbot for your business. Also, make sure to check out the best Instagram chatbots and Facebook chatbots.
4. Continuously improve with feedback
Your conversational interface should allow you to collect customer feedback and use it to improve the conversational UI further. Then, you can monitor interactions to identify common issues or areas for enhancement. Machine learning models can be updated based on this data to improve accuracy and relevancy, leading to a continually evolving and improving system.
5. Analyze key metrics and KPIs
Analyzing essential metrics is a critical best practice when implementing conversational interfaces. This involves continuously monitoring and evaluating various performance indicators to gauge the effectiveness of your smart technology.
Important customer service metrics you should be able to track with your conversational UI include engagement rates, which reveal how often users interact with the interface. Also, you should keep up with conversion rates which measure the tool’s success in driving desired actions, such as purchases or sign-ups.
With these metrics, businesses can identify strengths and opportunities for improvement, optimize the conversational chat flows, and enhance the overall user experience.
And there you have it. By following these best practices, you can create a conversational UI that meets user expectations and enhances satisfaction as a whole.
Read more: Explore key chatbot analytics and metrics you should track.
The future of conversational user interfaces
The future of conversational user interfaces is incredibly promising, as advancements in artificial intelligence and natural language understanding continue to evolve. These technologies are making conversational UIs more intuitive, context-aware, and capable of understanding complex human interactions.
As a result, we can expect these interfaces to become even more integral to our daily lives, seamlessly blending into applications ranging from customer service and ecommerce to healthcare and smart home control. Moreover, their increasing personalization capabilities will enable them to offer more tailored and relevant conversational experiences.
In addition, as privacy and data security technologies advance, users will feel more comfortable sharing information, allowing conversational interfaces to become trusted partners in managing everything from personal tasks to business operations.
As these trends continue, the boundary between human and computer interactions will blur, paving the way for more natural and efficient ways for customers to engage with brands.
Why not be a trailblazer and try incorporating a conversational interface into your business strategy today?
Improve your customer service efforts with conversational AI chatbots
FAQs
A conversational interface is a user interface that allows users to interact with technology using natural language, either through text or voice. These interfaces mimic human conversation, making it easier and more intuitive for users to get information and data, complete tasks, or solve problems without navigating complex menus or interfaces.
Conversational interfaces work by using natural language processing (NLP) to understand user input, whether it’s typed or spoken. The system analyzes the input to determine the user’s intent and extracts relevant information. It then generates a suitable response, either through text or voice, and delivers it back to the user. Advanced conversational interfaces use machine learning (ML) to continuously develop and improve from each interaction.
Conversational UIs offer several benefits, including 24/7 availability, cost efficiency, and scalability. They provide personalized user experiences based on previous interactions and information. Additionally, they improve user engagement by offering a more interactive and intuitive way to interact with technology.
While conversational interfaces can handle many routine inquiries and tasks efficiently, they are not a complete replacement for human agents. They help in solving straightforward issues and provide quick responses, but complex or sensitive matters often still require the empathy and problem-solving abilities of a human live agent.
Common use cases for conversational interfaces include customer service and ecommerce chatbots, virtual healthcare assistants, smart home control, and travel planning.
You type your query into the website’s chat window, asking, “Can you help me find running shoes?” The chatbot, powered by a conversational interface, understands your request and responds with a selection of running shoes available on the site.
Another popular example is a voice-based assistant like Amazon Alexa. You might say, “Alexa, turn off the living room lights,” and Alexa will understand and execute your request.
