A conversational user interface (CUI) allows users to interact with computer systems using natural language. It relies on natural language processing (NLP) and natural language understanding (NLU) to enable users to communicate with the computer system like they would converse with another person.
When was the last time you spoke to your phone? Yes, not on the phone but to your phone. Maybe you asked Siri to update you on the weather or set a reminder for your dental appointment.
The phone or desktop application interface you used to "speak" to Siri is what we call a conversational user interface.
With these interfaces, instead of typing out commands like "Click here," you can use natural phrases like "Show me my account balance." The goal is for users to interact with the computer system as they would talk to another person—without learning complicated commands or formulas.
In this article, we’ll discuss the underlying mechanism of CUI, types of CUI, typical use cases, and benefits and challenges of the same.
How does a Conversational UI work?
As these interfaces are required to facilitate conversations between humans and machines, they use intuitive artificial intelligence (AI) technologies to achieve that.
NLP analyzes the linguistic structure of text inputs, such as word order, sentence structure, and so on. NLU, on the other hand, is used to extract meaning from words and sentences, such as recognizing entities or understanding the user's intent. The CUI then combines these two pieces of information to interpret and generate an appropriate response that fits the context of what was asked.
It also uses memory capabilities to remember previous conversations and apply them to future ones. This way, it can provide users with relevant content even though they may not have specified it explicitly.
It also consists of additional components such as:
- Voice recognition: This technology leverages powerful machine learning algorithms, NLP, and acoustic modeling. Using that, it accurately converts audio signals into text with high speed and accuracy. The combination of these technologies has allowed for increased accuracy when decoding complex sentences spoken with multiple speakers or languages.
- Dictionary: A library of phrases the AI model draws from to be trained. It includes examples from everyday conversation, including colloquialisms, idioms, grammar and syntax. It also consists of all the variations and variants of a particular phrase, such as "Book Flight," which might include "I need a flight" or "I want to book my travel." It ensures that the AI model can recognize different ways of expressing the same intent.
- Context: To properly respond to users, chatbots must learn to understand the context behind their queries. It requires training the AI system with examples of conversations and their corresponding contexts to recognize when different topics should be discussed.
- Business logic: By leveraging business logic, chatbots can efficiently process complex conversations and training scenarios. In turn, it provides users with tailored conversational experiences through interactions that simulate human communication.
Types of Conversational UI
There are three main categories of CUIs: rule-based chatbots, text-based chatbots, and voice assistants. Here's how they work:
Rule-based chatbots are conversational user interfaces that use a set of rules and patterns to interact with a user. These bots rely on the same principles as general conversational AI agents, but instead of applying machine learning algorithms and analyzing conversational data in real time, they follow predetermined rules.
For example, Smartling, a translation management SaaS, uses a rule-based chatbot to identify the user's intent on its website. It offers options to understand whether you're a prospect, translator, current customer, or just browsing. Based on that, it offers tailored options to satisfy the intent.
Text-based AI chatbots have opened up conversational user interfaces that provide customers with 24/7 immediate assistance. These chatbots can understand natural language, respond to questions accurately, and even guide people through complex tasks.
For example, Duolingo’s AI-powered text-based chatbots offer users an interactive learning experience. The chatbot allows them to converse with different personalities like Chef Robert, Renée the Driver, and Officer Ada. The user can choose their preferred personality and language (French, Spanish, and German) and converse with it to quickly pick up the language.
Voice assistant chatbots are CUIs that allow a computer to understand human voice and language. They can provide users with services ranging from answers to general questions to playing music and setting reminders. There are two types: virtual assistants and interactive voice recognition apps.
These conversational bots allow users to communicate with a virtual agent to complete tasks efficiently and accurately. Typically, they're used for customer support but are also present in mobile/desktop devices. Examples include Microsoft's Cortana, Apple's Siri, and Android's OK Google.
Interactive Voice Recognition (IVR)
Interactive Voice Recognition (IVR) chatbots are conversational user interfaces that enable automated conversations with customers over the phone. They use AI to interpret human speech and conversational dialogues, allowing customers to get answers to their queries without waiting for an operator. IVR chatbots can make customer service faster and more efficient through their conversational interface by providing instant responses to customers' inquiries.
Popular use cases of conversational UI
CUIs have already been employed in many industries for several purposes. Here are a few common use cases that you might’ve come across previously:
Retail and e-commerce industry
Companies in these sectors utilize CUIs to create more engaging customer interactions and streamline tedious tasks such as quickly finding product information. It also includes virtual assistants guiding customers through product selections and payment processes, allowing them to make their purchases quickly and conveniently.
Banking and insurance services
These conversational systems provide a platform for customers to get their questions answered, efficiently make payments, or receive automated support in the form of personalized advice. It allows customers to manage their accounts, report fraudulent activity or lost cards, request PIN changes, and use such interfaces.
Connected devices (IoT) for smart homes
Conversational user interfaces help operate smart homes powered by the Internet of Things (IoT) technology. This technology is transforming how we interact with everyday appliances, allowing individuals to control their lights, thermostat, security cameras, and other connected devices.
For example, Amazon's Alexa can help you do mundane tasks like switching off lights or playing a random song using simple commands such as "turn off my living room lights" or “Alexa, play AC/DC’s Highway to Hell.”
Benefits of conversational UI
There are several critical benefits of using such interfaces for your business:
Personalization of customer experience
They help create a more engaging and tailored experience compared to traditional interfaces. For example, they can understand the context of user queries or conversations, allowing them to provide accurate answers quickly. It helps users feel their needs are being catered to with personalized customer service that increases customer satisfaction.
Plus, it can remember preferences and past interactions, making it easy for users to have follow-up conversations with more relevant information.
Efficient use of existing resources
Another advantage of these interfaces is their ability to optimize resources. As conversations are conducted in natural language, there's no need for users to invest time in learning a different set of commands or navigating complex menus. Instead, these systems rely on automated processes to interpret user requests, reducing manual labor while improving accuracy, efficiency, and scalability.
Plus, you can save costs associated with developing new user interfaces as this technology has built-in components that you can easily integrate into existing systems.
Accessible to technical and non-technical users
These interfaces are simple, making it easier for non-technical users as they don't require specific instructions like graphical or command line-based applications. It allows people who don't have the technical expertise to learn how the system works.
Moreover, it capitalizes on humans' innate capacity to understand a sentence's context. So, users can get accurate results when inquiring about a product or service, and it's easier to integrate it into their daily lives too.
Challenges of conversational UI
One of the most significant challenges is enabling accurate natural language understanding. It means that the CUI needs to understand the user's intent and correctly interpret their commands, no matter how they are phrased or what words they use. This can be difficult, as there are often many ways to express the same idea, and users may use various slang terms or colloquialisms that need to be accounted for.
Another challenge is creating an interface that delivers a seamless user experience. It means designing an intuitive flow of conversation that allows users to reach their goals without repeating themselves or becoming confused.
Plus, it can be difficult for developers to measure success when using conversational user interfaces due to their inherently qualitative nature. Traditional quantifiable metrics like click-through rates and conversions don't apply here, so companies must create other ways of gauging success, such as customer feedback surveys or analyzing sentiment analysis data from conversations.
The future of conversational interfaces
Conversational user interfaces have become increasingly popular in recent years. As it offers many advantages:
- Increased customer engagement
- Access to valuable data for marketing
- Ability to reduce hiring and labor costs
With CUIs, users don't have to learn complex commands or formulas. Instead, they can speak naturally and get answers quickly. Additionally, these UIs provide a more personalized experience for each user since the system remembers previous conversations and responds accordingly.
In the near future, the way we interact with the software will drastically change because of rapid developments in CUIs. If you're looking for ways to improve for a cost-efficient conversational solution, these interfaces are what you need.