The Evolution of the CUI
In many industries, customers and employees need access to relevant, contextual information that is quick and convenient. Conversational User Interfaces (CUIs) enable direct, human-like engagement with computers. It completely transforms the way we interact with systems and applications.
CUIs are becoming an increasingly popular tool, which the likes of Amazon, Google Facebook, and Apple, have incorporated into their platforms. With the right approach, you can do the same.
Table of contents
What is Conversational User Interface?
A Conversational User Interface (CUI) is an interface that enables computers to interact with people using voice or text, and mimics real-life human communication. With the help of Natural-Language Understanding (NLU), the technology can recognize and analyze conversational patterns to interpret human speech. The most widely known examples are voice assistants like Siri and Alexa.
Voice interactions can take place via the web, mobile, desktop applications, depending on the device. A unifying factor between the different mediums used to facilitate voice interactions is that they should be easy to use and understand, without a learning curve for the user. It should be as easy as making a call to customer service or asking your colleague to do a task for you. CUIs are essentially a built-in personal assistant within existing digital products and services.
In the past, users didn’t have the option to simply tell a bot what to do. Instead, they had to search for information in the graphical user interface (GUI) – writing specific commands or clicking icons. Past versions of CUI consisted of messenger-like conversations, for example, where bots responded to customers in real-time with rigidly spelled-out scripts.
But now it has evolved into a more versatile, adaptive product that is getting hard to distinguish from actual human interaction.
The technology behind the conversational interface can both learn and self-teach, which makes it a continually evolving, intelligent mechanism.
How Do CUIs Work?
CUI is capable of generating complex, insightful responses. It has long outgrown the binary nature of previous platforms and can articulate messages, ask questions, and even demonstrate curiosity.
Previously, command line interfaces required users to input precise commands using exact syntax, which was then improved with graphical interfaces. Instead of having people learn how to communicate with UI, Conversational UI has been taught how to understand people.
The core technology is based on:
● Natural Language Processing – NLP combines linguistics,
computer science, information engineering, and artificial intelligence to create meaning from user input. It can process the structure of natural human language and handle complex requests.
● Natural Language Understanding – NLU is considered a subtopic of natural language processing and is narrower in purpose. But the line between them is not distinct, and they are mutually beneficial. By combining their efforts, they reinterpret user intent or continue a line of questioning to gather more context.
For example, let’s take a simple request, such as:
“I need to book a hotel room in New York from January 10th to the 15th.”
In order to act on this request, the machine needs to dissect the phrase into smaller subsets of information: book a hotel room (intent) – New York (city) – January 10 (date) – January 15 (date) – overall neutral sentiment.
Conversational UI has to remember and apply previously given context to the subsequent requests. For example, a person may ask about the population of France. CUI provides an answer to that question. Then, if the next phrase is “Who is the president?”, the bot should not require more clarification since it assigns the context from the new request.
In modern software and web development, interactive conversational user interface applications typically consist of the following components:
- Voice recognition (also referred to as speech-to-text) – A computer or mobile device captures what a person says with a microphone and transcribes it into text. Then the mechanism combines knowledge of grammar, language structure, and the composition of audio signals to extract information for further processing. To achieve the best level of accuracy possible, it should be continuously updated and refined.
- NLU – The complexity of human speech makes it harder for the computer to decipher the request. NLU handles unstructured data and converts it into a structured format so that the input can be understood and acted upon. It connects various requests to specific intent and translates them into a clear set of steps.
- Dictionary/samples – People are not as straightforward as computers and often use a variety of ways to communicate the same message. For this reason, CUI needs to have a comprehensive set of examples for each intent. For example, the request “Book Flight”, the dictionary should contain “I need a flight”, “I want to book my travel”, along with all other variants.
- Context – An example with the French president above showed that in a series of questions and answers, CUI needs to make a connection between them. These days, UIs tend to implement an event-driven contextual approach, which accommodates an unstructured conversational flow.
- Business logic – Lastly, the CUI business logic connects to specific use cases to define the rules and limitations of a particular tool.
Types of Conversational User Interfaces
We can distinguish two distinct types of Conversational UI designs. There are bots that you interact with in the text form, and there are voice assistants that you talk to. Bear in mind that there are so-called “chatbots” that merely use this term as a buzzword. These fake chatbots are a regular point-and-click graphical user interface disguising and advertising itself as a CUI. What we’ll be looking at are two categories of conversational interfaces that don’t rely on syntax specific commands.
Chatbots have been in existence for a long time. For example, there was a computer program ELIZA that dates back to the 1960s. But only with recent advancements in machine learning, artificial intelligence and NLP, have chatbots started to make a real contribution in solving user problems.
Since most people are already used to messaging, it takes little effort to send a message to a bot. A chatbot usually takes the form of a messenger inside an app or a specialized window on a web browser. The user describes whatever problem they have or asks questions in written form. The chatbots ask follow-up questions or meaningful answers even without exact commands.
Voice recognition systems
Voice User Interfaces (VUI) operate similarly to chatbots but communicate with users through audio. They are hitting the mainstream at a similar pace as chatbots and are becoming a staple in how people use smartphones, TVs, smart homes, and a range of other products.
Users can ask a voice assistant for any information that can be found on their smartphones, the internet, or in compatible apps. Depending on the type of voice system and how advanced it is, it may require specific actions, prompts or keywords to activate. The more products and services are connected to the system, the more complex and versatile the assistant becomes.
Business Use Cases
Chatbots and Voice UIs are gaining a foothold in many important industries. These industries are finding new ways to include conversational UI solutions. Its abilities extend far beyond what now dated, in-dialog systems, could do. Here are several areas where these solutions can make an impressive impact.
Retail and e-commerce
A CUI can provide updates on purchases, billing, shipping, address customer questions, navigate through the websites or apps, offer products or service information, along with many other use cases. This is an automated way of personalizing communication with your customers without involving your employees.
Architects, engineers, and construction workers often need to review manuals and other text chunks, which can be assisted by CUI. Applications are diverse: contractor, warehouse, and material details, team performance, machinery management, among others.
Increasing response speed is essential for first responders. CUI can never replace live operators, but it can help improve outcomes in crises by assessing incidents by location, urgency level, and other parameters.
Medical professionals have a limited amount of time and a lot of patients. Chatbots and voice assistants can facilitate the health monitoring of patients, management of medical institutes and outpatient centers, self-service scheduling, and public awareness announcements.
Banking, financial services, and insurance
Conversational interfaces can assist users in account management, reporting lost cards, and other simple tasks and financial operations. It can also help with customer support queries in real-time; plus, it facilitates back-office operations.
Smart homes and IoT
People are starting to increasingly use smart-home connected devices more often. The easiest way to operate them is through vocal commands. Additionally, you can simplify user access to smart vehicles (open the car, plan routes, adjust the temperature).
Benefits of Conversational UI
The primary advantage of Conversational UI is that it helps fully leverage the inherent efficiency of spoken language. In other words, it facilitates communication requiring less effort from users. Below are some of the benefits that attract so many companies to CUI implementations.
Communicating with technology using human language is easier than learning and recalling other methods of interaction. Users can accomplish a task through the channel that’s most convenient to them at the time, which often happens to be through voice. CUI is a perfect option when users are driving or operating equipment.
Voice is an incredibly efficient tool – in almost every case, it is easier and faster to speak rather than to use touch or type. Voice is designed to streamline certain operations and make them less time consuming. For example, CUI can increase productivity by taking over the following tasks:
- Create, assign, and update tasks
- Facilitate communication between enterprises and customers, enterprises and employees, users and devices
- Make appointments, schedule events, manage bookings
- Deliver search results
- Retrieve reports
Many existing applications are already designed to have an intuitive interface. However, conversational interfaces require even less effort to get familiar with because speaking is something everyone does naturally. Voice-operated technologies become a seamless part of a users’ daily life and work.
Since these tools have multiple variations of voice requests, users can communicate with their device as they would with a person. Obviously, it’s something everyone is accustomed to. As a result, it improves human-computer interactivity.
When integrating CUI into your existing product, service, or application, you can decide how to present information to users. You can create unique experiences with questions or statements, use input and context in different ways to fit your objectives.
Additionally, people are hard-wired to equate the sound of human speech with personality. Businesses get the opportunity to demonstrate the human side of their brand. They can tweak the pace, tone, and other voice attributes, which affect how consumers perceive the brand.
Better use of resources
You can maximize your staff skills by directing some tasks to CUI. Since employees are no longer needed for some routine tasks (e.g., customer support or lead qualification), they can focus on higher-value customer engagements.
As for end-users, this technology allows them to make the most out of their time. When used correctly, CUI allows users to invoke a shortcut with their voice instead of typing it out or engaging in a lengthy conversation with a human operator.
There are restrictions no when you can use CUI. Whether it’s first responders looking for the highest priority incidents or customers experiencing common issues, their inquiry can be quickly resolved.
No matter what industry the bot or voice assistant is implemented in, most likely, businesses would rather avoid delayed responses from sales or customer service. It also eliminates the need to have around-the-clock operators for certain tasks.
Conversational UI Challenges
Designing a coherent conversational experience between humans and computers is complex. There are inherent drawbacks in how well a machine can maintain a conversation. Moreover, the lack of awareness of computer behavior by some users might make conversational interactions harder.
Here are some major challenges that need to be solved in design, as well as less evident considerations:
- Accuracy level – The CUI translates sentences into virtual actions. In order to accurately understand a single request and a single intent, it has to recognize multiple variations of it. With more complex requests, there are many parameters involved, and it becomes a very time-consuming part of building the tool.
- Implicit requests – If users don’t say their request explicitly, they might not get the expected results. For example, you could say, “Do the math” to a travel agent, but a conversational UI will not be able to unpack the phrase. It is not necessarily a major flaw, but it is one of the unavoidable obstacles.
- Specific use cases – There are many use cases you need to predefine. Even if you break them down into subcategories, the interface will be somewhat limited to a particular context. It works perfectly well for some applications, whereas in other cases, it will pose a challenge.
- Cognitive load – Users may find it difficult to receive and remember long pieces of information if a voice is all they have as an output. At the very least, it will require a decent degree of concentration to comprehend a lot of new information by ear.
- Discomfort of talking in public – Some people prefer not to share information when everyone within earshot can hear them. So, there should be other options for user input in case they don’t want to do it through voice.
- Language restrictions – If you want the solution to support international users, you will need a CUI capable of conversing in different languages. Some assets may not be suitable for reuse, so it might require complete rebuilds to make sure different versions coexist seamlessly.
- Regulations protecting data – Making sure interactions are personalized, you may need to retrieve and store data about your users. There are concerns about how organizations can make it comply with regulation and legislation. It is not impossible but demands attention.
These challenges are important to understand when developing a specific conversational UI design. A lot can be learned from past experiences, which makes it possible to prevent these gaps from reaching their full potential.
The Future of Conversational UI
The chatbot and voice assistant market is expected to grow, both in the frequency of use and complexity of the technology. Some predictions for the coming years show that more and more users and enterprises are going to adopt them, which will unravel opportunities for even more advanced voice technology.
Going into more specific forecasts, the chatbots market is estimated to display a high growth continuing its trajectory since 2016. This expected growth is attributed to the increased use of mobile devices and the adoption of cloud infrastructure and related technologies.
As for the future of voice assistants, the global interest is also expected to rise. The rise of voice control in the internet of things, adoption of smart home technologies, voice search mobile queries, and demand for self-service applications might become key drivers for this development. Plus, the awareness of voice technologies is growing, as is the number of people who would choose a voice over the old ways of communicating.
Naturally, increased consumption goes hand-in-hand with the need for more advanced technologies. Currently, users should be relatively precise when interacting with CUI and keep their requests unambiguous. However, future UIs might head toward the principle of teaching the technology to conform to user requirements rather than the other way around. It would mean that users will be able to operate applications in ways that suits them most with no learning curve.
If the CUI platform finds the user’s request vague and can’t convert it into an actionable parameter, it will ask follow-up questions. It will drastically widen the scope of conversational technologies, making it more adaptable to different channels and enterprises. Less effort required for CUI will result in better convenience for users, which is perhaps the ultimate goal.
The reuse of conversational data will also help to get inside the minds of customers and users. That information can be used to further improve the conversational system as part of the closed-loop machine learning environment.
Checklist for Making a Great Conversational UI for your Applications
There are plenty of reasons to add conversational interfaces to websites, applications, and marketing strategies. Voice AI platforms like Alan, makes adding a CUI to your existing application or service simple. However, even if you are certain that installing CUI will improve the way your service works, you need to plan ahead and follow a few guidelines.
Here are steps to adopt our conversational interface with proper configuration:
1.Define your goals for CUI. The key factor in building a useful tool is to decide which user problem it is going to address.
2. Design the flow of a conversation. Think of how communication with the bot should go – greeting, how it’s going to determine user needs, what options it’s going to suggest, and possible conversation outcomes.
3. Provide alternative statements. As you know, users frame their requests in different ways, sometimes using slang, so you need to include different types of words that the bot will use to recognize the intent.
4. Set statements to trigger some sort of action so that it can make a corresponding API call. What does a user have to say to make the bot respond appropriately for the situation? It is useful to use word tokenization to assign meaning at this point.
5. Add visual and textual clues and hints. If a user feels lost, guide them through other mediums (other than voice). This way, you will improve the discoverability of your service.
6. Make sure there are no conversational dead ends. Bot misunderstandings should trigger a fallback message like “Sorry, I didn’t get that”. Essentially, don’t leave the user waiting without providing any feedback.
Overall, you should research how CUI can support users, which will help you decide on a type of CUI and map their journey through the application. It will help you efficiently fulfill the user’s needs,
keep them loyal to the product or service, and simplify their daily tasks.
Additionally, create a personality for your bot or assistant to make it natural and authentic. It can be a fictional character or even something that is now trying to mimic a human – let it be the personality that will make the right impression for your specific users.
A good, adaptable conversational bot or voice assistant should have a sound, well-thought-out personality, which can significantly improve the user experience. The quality of UX affects how efficiently users can carry out routine operations within the website, service, or application.
In fact, any bot can make a vital contribution to different areas of business. For many tasks, just the availability of a voice-operated interface can increase productivity and drive more users to your product. Many people can’t stand interacting over the phone – whether it’s to report a technical issue, make a doctor’s appointment, or call a taxi.
A significant portion of everyday responsibilities, such as call center operations, are inevitably going to be taken over by technology – partially or fully. The question is not if but when your business will adopt Conversational User Interfaces.