February 24, 2025
by Sagar Joshi / February 24, 2025
Conversations are the future of interfaces.
Just like Siri or Google Assistant, you write in natural language, and the assistant understands. Your interactions with the software will be similar.
Conversational UI lets technology mimic human conversations. Whether through a chatbot or a virtual agent, you can get your queries answered in a way that feels effortless and natural to you.
Modern text-to-speech technology empowers such user experiences, helping technologies improve comprehension and break down language barriers.
Conversational UI is beyond text or speech. Let’s take a quick dip in the fundamentals before we dig deeper into its true nature.
Conversational user interface (CUI) allows people to interact with technology using natural language, just like they would with another person. The interaction feels intuitive because it happens in human language, not technical commands.
One of the most familiar examples of conversation UI is chatbots. They’re a significant channel in modern customer service strategies for automating routine responses and FAQs.
of consumers believe companies should adopt chatbots instead of traditional customer support.
Source: Statista
This statistic highlights customers’ opinions on conversational artificial intelligence (AI). As AI systems evolve, more innovations will come up to present conversational interfaces beyond the chat options that are now common.
Different types of conversational UI that are relevant to support and service professionals. Here’s a closer look at the key ones:
Chatbots are either traditional (rule-based) or powered by AI. They are usually the first technology modern consumers interact with when they seek support.
AI-based chatbots are powered by large language models which allow them to mimic human conversations. On the contrary, rule-based chatbots are based on a set of rules that govern their conversational flow. The answers are based on a user's fixed set of questions.
For example, when you send in an inquiry outside working hours, the chatbot will provide information on the next available time to connect with support staff. The triggered responses are often based on specific keywords.
Voice assistants are similar to chatbots but interact with voice instead of text messaging. These assistants are generally built into smart speakers (e.g. Amazon Echo) or smartphones (e.g. Siri or Google Bixby). They take voice commands as input and use text-to-speech technology to respond in voice.
Voice assistants are of two types:
Hybrid interfaces combine voice and text interactions in the same system. They allow users to switch between the two, increasing the flexibility with which users engage with the conversational UI and making the system more adaptable.
For example, when sitting in a library, it’s politer to interact using text. On the contrary, when you’re multitasking at your home, the voice option becomes more feasible.
Conversational interfaces are more common than we think they are. When you use voice commands to control your car’s music system, you’re interacting with conversational UI. The system uses a conversational interface to understand your voice and respond with appropriate actions.
A simpler example would be talking to Siri on the iPhone. What if the same convenience came to your products? Many businesses have started using it as:
On the business side, chatbots are popular in customer service. They give 24/7 support, answer routine questions, and save ample time for agents.
Customer service bots are known for instantaneous support regardless of the actual team’s availability. They’re popular in the e-commerce industry, where they act personalized shopping assistants, for example, selecting the perfect outfit for an event.
Many professionals rely on conversational assistants to make their jobs easier. They typically interact with conversational UI to get their internal jobs done. For example, they might interact with a conversational interface to write an email or rely on conversational assistants to get processed information – which might take longer to aggregate if done manually.
There are several other use cases of conversational assistants in internal tasks and activities, like scheduling reminders or appointments. Understanding how these systems work helps us appreciate their potential and the technology driving them.
Any interaction with a conversational user interface starts with user input. The input is in natural language, which is tricky for software that understands mostly 0s and 1s.
This natural language is processed using natural language processing (NLP) and machine learning (ML) to help the software understand what users expect based on their input. Based on it, the software generates a response and gives it to the user through voice or text channels.
A conversational interface has several components. Here’s a breakdown of its process:
Lastly, the model will use ML to learn from the queries and responses, making it further accurate in handling such queries. There is a difference between how conversational UI handles voice-based commands vs text-based. Let’s explore it!
Voice-based conversational UI enables users to give a command in order to accomplish a task. For example, Siri was one of the first widely adopted voice assistants, enabling iPhone users to set reminders, search the web, or control smart home devices.
Modern day voice-based conversational UI allows you to command systems to perform actions like switching on a fan, or increasing a speaker’s volume.
Text-based conversational UI, on the other hand, allows users to input text and receive output in text format. It’s like a chatbot that enables users to ask questions and retrieve information. It empowers professionals to automate simple questions or routine inquiries, helping businesses get more hours back that were spent addressing simple queries.
The interfaces can pass a conversation to a live human agent when it becomes complex for them to automate. Some also offer an option for users to choose if they would like to speak to a human agent for immediate support requirements.
Both voice and text-based interfaces offer unique advantages, but the benefits of conversational UI as a whole extend beyond these formats.
The obvious benefit of conversations UI is 24/7 availability regardless of timezone or working hours limitations. You always have a functional conversational interface on the website for any doubts or confusion users are dealing with.
This eliminates the delay a customer needs to wait before they get the support they seek. Moreover, the conversational interfaces deliver curated information, saving the time a user spends looking for what they want.
Aside from the common ones, here are a few notable benefits of conversational UI:
Whether you use conversational UI on the sales or support side, it helps you effectively use resources. It automates simple tasks like qualifying leads based on set criteria in sales or answering simple questions on the support side, freeing up more time and focus for human agents to deal with critical opportunities and issues.
Conversational UI can be integrated with channels like WhatsApp or Facebook Messenger. This brings brands closer to users when they support them on channels that they enjoy using and interacting with.
Chatbots that have a personality similar to the brand, and are programmed to complement the brand’s standards significantly impact users’ experience. It makes their experience memorable, and delightful, adding additional points for customer satisfaction.
Despite their many advantages, conversational UIs come with their own set of challenges that can hinder the user experience if not addressed.
Not all conversational interfaces are developed the same way in the backend. The backend development, technology, learning, and various other factors play a role in determining the accuracy and quality of responses delivered by the UI.
When any of these factors aren’t up to the mark, users face some challenges with conversational UI. These can include:
When customers are in a rush, they don’t want to spend time typing or speaking out every minute detail of their experience to get the support they desire. Automated conversational interfaces need those inputs in order to deliver the right output, making them less effective in issue resolution.
This can become frustrating for customers as they are already in a rush, and would have to retype or repeat information they’ve already shared. The major challenge is here is the lack of clarity about how much users should share when they input a query.
An essential feature of any conversational UI is the ability to escalate to a human agent. When it isn’t easily accessible, it can lead to customer dissatisfaction, especially when they have to dig deeper to find out a way to connect with actual people from the company.
Matthew Gertner, CEO and Founder of Salsita Software, stated how the biggest difficulty they had encountered was users not expecting to be presented with a chat window as one of the primary components of an application user interface.
Matthew continued, “Their (users) first impulse when they see a chat pop up in their face is to close it as quickly as possible so they can get at the “real” interface of the software."
The learnings of large language models (LLMs) that power the conversational interfaces determine their responses’ accuracy. Not all, but some conversational UI systems tend to hallucinate when they don’t have enough inputs or learnings in place to deliver the expected output. How to design impressive conversational UI interfaces.
To overcome these challenges and maximize the potential of conversational UI, implementing strategies and best practices is essential.
Designing great conversational experiences involves a few best practices that help make the users’ experience memorable.
When you balance human and automated conversations while interacting, you help engage users at scale. This gives users the best of both worlds.
For example, when they desire simple information or action, the automated experience supports them immediately. When they need support for more complicated issues, the conversational UI lets them connect with an expert agent who’s well-versed in different attributes of their issue.
Ultimately, conversational interfaces offer an easier way to interact with a business digitally, as if you were talking to someone on their team. Text-to-speech technology facilitates such interactions while delivering several other opportunities to offer users a delightful experience.
Learn more about how modern technology like speech recognition software can further help improve these conversational experiences in business.
Edited by Monishka Agrawal
Sagar Joshi is a former content marketing specialist at G2 in India. He is an engineer with a keen interest in data analytics and cybersecurity. He writes about topics related to them. You can find him reading books, learning a new language, or playing pool in his free time.
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