The Conversational AI allows the program to be a part of human-like interactions. This set of technologies empower the applications to send automated replies. It is yet another example of the exponential rate of innovations happening in the artificial intelligence field.
As a result, businesses are investing in conversational AI technologies like Chatbots to serve customers round-the-clock. Although the benefits of using this advanced technology are innumerable, you need to answer certain questions while assessing a conversational AI solution.
Conversational AI is Still Evolving
We are still undergoing the phase of revolution wherein innovators are bridging the gap between the artificial and natural interactions among humans and computers. Constantly, developers are empowering Conversational AI technologies to decipher human actions and mimic human-like conversations.
According to research, the Conversational AI market size is expected to reach US Dollars 15.7 billion by 2024. This clearly depicts the interest of investors in this technology and gives a sign of a lucrative future scope for businesses.
The incorporation of context, relevance, and personalization after deciphering various languages and tones is the end goal of this set of technologies. Chatbots are integral components of these technologies. Consequently, they undergo continual enhancements.
Conversational AI is not the Same as Traditional Chatbots
What do you like more, scripted TV shows or reality shows? Traditional chatbots are the scripted ones and Conversational AI chatbots are the non-scripted ones. The former one works with scripted dialogues whereas the latter one works with the context.
When scripted traditional chatbots are created, developers feed the dialogues with proper keywords. The bots are able to respond with the most appropriate reply out of the many replies added to their memory.
When a user sends a particular text, the chatbot identifies the keywords and sends in the scripted replies. This adds tons of burden on the owner of the chatbots. Hence, they update the conversations to make them look realistic.
The traditional scripted chatbots are not able to converse in real-time with users by understanding the context of the whole conversation. As a result, this compromises the customer services of the businesses.
This particular loophole is looked after by the chatbots powered by conversational AI. They hold the capability to engage in any dialogue after grasping the context of the whole conversation. They do not follow a script because they have in-built conversational capabilities in the software. Let’s understand how they work in detail.
Work Process of the Conversational AI
Conversational AI works with a combination of technologies. With the integration of advanced technologies, Conversational AI performs the function of interacting like humans. Here are the steps involved in the work process of these technologies:
1. Accept the Inputs
The first step involved in the functioning of Conversational AI is to accept the inputs from users. These inputs can be in the form of text or speech. If the inputs are in the written form, text recognition technology is applied. On the other hand, if inputs are spoken phrases, then voice recognition technology is applied.
Text and voice recognition is done with AI technology natural language understanding (NLU). After the application reads the inputs, the user intent is understood before forming any kind of response. Usually, businesses can use conversational AI for comprehending responses in various languages. In a nutshell, this is one of the most difficult steps in the work process of a chatbot.
3. Creating Response
In this step, the Natural Language Generation (NLG) is used to create responses in a language that humans understand. After deciphering the intent of the human, dialog management is used to create responses. Finally, it converts the computer-generated responses into human-understandable language.
4. Delivering Response
Finally, the response created in the previous step is shared with the users in the expected form. Either the system delivers it as a text or conducts the production of human speech artificially. Are you able to recall the voice of Alexa or Google Assistant? They generate their responses by following this process only.
5. Learn from Experience
Conversational AI also has provisions for improving their responses for future interactions by learning from their experiences. By accepting suggestions, the application learns to deliver better responses in future conversations.
Technologies used in Conversational AI
The Conversational AI platforms use a set of technologies at the right times to complete the work process. All these technologies are empowered by Artificial intelligence. Let’s understand these technologies in brief.
1. Automatic Speech Recognition (ASR)
The application interprets the spoken phrases by deploying this technology. Adding to this, it converts the speech into texts for the app. Voice assistants like Alexa, Google Assistant, etc. use Automatic Speech recognition.
2. Advanced Dialog Management
This technology helps in forming the response to the conversational AI app. Dialog management arranges this response for the next technology. Further, converts it into something which humans can understand.
3. Natural Language Processing (NLP)
Conversational AI uses natural language processing along with its two subsets. The first one is Natural language Understanding which understands the meaning as well as the intent behind any text. It can decipher texts shared in multiple languages as per the programming.
Both chatbots, as well as voice assistants, use this technology. After ASR, voice apps apply NLU. The second one under the NLP technology head is Natural Language Generation. Conversational AI uses this in the last stage of the work process by Conversational AI.
It creates the responses by converting the computer-generated replies into a language that is understandable for humans. This technology deploys dialog management to conduct this task seamlessly.
4. Machine Learning (ML)
Machine learning is great at understanding a set of data. In conversational AI also, machine learning is used to understand the interactions that have happened over time. Also, ML identifies better responses to these interactions.
Therefore, it understands user behavior and guides the app to create better responses. Humans also join machine learning in this task and together make the Conversational AI app a better interactor for customers.
Benefits of Using Conversational AI for Better Customer Engagement
Businesses are struggling for quite a long time to improve their customer engagements. As a consequence, conversational AI tools like Chatbots have become an integral part of websites and apps. Hence, the developers are working hard to incorporate conversational AI in their solutions.
Conversational marketing has become a proven corporate strategy for millions of businesses operating across various domains including healthcare, tourism, education, etc. Let’s find out what exactly can Conversational AI do to empower customer engagement:
1. Never-ending Scalability
Contrary to human customer support executives, Conversational AI can provide solutions to as many customers as possible at one time. Therefore, you can scale up your operations to any limits. Moreover, it can provide human-like interactions around-the-clock without any interruptions.
2. Acts as a Supportive Wing
In an organization, teams work together towards achieving organizational goals. Conversational AI technologies work with human experts and take their burdens away. They do those tasks which are humanly not possible at the same consistency as that of Conversational AI. This leaves room for human experts to entertain customers only when required.
3. Reduces Cost
Investing in conversational AI solutions might seem an added expenditure to you. But in the long run, the functions it performs reduces your cost. You will not have to pay employees for all the shifts to satisfy customers with real-time conversations. These applications prove to be immensely cost-effective for businesses.
4. Offers Data Insights
As mentioned above, machine learning understands the past experiences and interactions to improve your Conversational AI potential for future interactions. This allows businesses to get an insight into the data.
Hence, you will be able to know your customers’ preferences, behavior, and requirements. Furthermore, you can utilize this data for various other purposes to improve your plans and strategies.
5. Improves Productivity
The primary reason for investing in conversational AI solutions should be the need to improve productivity. It enhances overall productivity with uninterrupted, credible, and prompt customer services.
24×7 support and human-like interactions decrease the risk of losing customers. Hence, conversational AI is capable of providing better customer engagement and ultimately a rise in customer retention rate.
Leverage Conversational AI in Omni-Channel Approach
Investing in conversational AI might seem lucrative after reading about its work process and benefits. Before taking the final call, make sure to identify the channels where you are going to leverage this technology.
When it comes to the customer experience journey, we need to take care of many gateways. With conversational AI solutions, you can provide live chats, social media interactions, messaging on various platforms like Whatsapp, SMS, etc., as well as emails.
Therefore, businesses are using the omnichannel approach. Under this approach, they use multiple engagement channels and offer a seamless and intuitive customer experience. It allows businesses to offer their customers a proactive engagement and prompt responses.
Across the world, businesses are deploying high-end artificial intelligence technologies. This, in turn, offers business solutions to enhance the engagement of customers. Therefore, we can these technologies to offer an improved experience to your users. Conversational AI holds the potential to strengthen customer and business relationships. All you need is to explore it efficiently!
The post How is Conversational AI Improving Customer Experience? appeared first on ReadWrite.