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There was a time when businesses were exploring how to integrate AI in their chat systems to make customer experience more real-time and satisfaction-inclined. Across industries, they were making different user journeys and were drafting dialogues to address each of them. Now, while AI continues to be a part of the customer experience journey, both on voice and text mediums, digital customers are now asking for something more.
Today’s customers are looking for a more seamless, more rich conversation session with digital brands. Session where they don’t have to wait for a human to get into the picture to address their queries. This need in itself, has created a new segment – Conversational AI. And the demand which the space is witnessing has projected a growth trajectory from $6.8 billion in 2021 to $18.4 billion by 2026.
In this article, we are going to deep dive into the world of conversational AI, where we are going to look into what it is, how it works, and what are the different benefits businesses can derive from it.
In the most basic terms, conversational AI solution is a blend of technologies which enable the computers to gather and process natural language input. It makes it possible for computers to interact with humans in a way that humans interact with each other.
Now, in order to truly understand what a conversational AI solution does, it is important to dissect how humans interact.
As humans, when we have a conversation, we –
In comparison to all this, machines talk directly. Now, the essence of conversational AI software lies in bridging this gap between machines and humans to create more natural interactions. What makes this possible is a combination of two technologies –
Natural Language Processing – NLP is a technology that works around interpreting language, modeling to help machines interact with humans more naturally.
Machine Learning – The technology integrates software with algorithms that makes it possible for them to automatically improve themselves with every user input. Know how ML development is disrupting the mobile app industry.
While the what of what is conversational AI addressed, it is now time to move to the why. Why should businesses care about investing in conversational AI software?
Although there are growing applications of conversational AI in the business world, its impact has been most visible in the customer experience domain. Businesses, across countries, have started exploring the technology for the benefits it offers to their customers, a peek of which can be seen through this graph –
Modern day customers expect state-of-the-art experience from every business they interact with. The technology helps with delivering a personalized conversation across every channel where the customer is active, for example – company app/website, social media, messenger app, etc.
A number of conversational AI platforms come with the facility of categorizing calls on the basis of user query and their emotions – this helps businesses prioritize the calls when they are in the middle of a call spike. These platforms also enable routing of interactions to an IVR (Intelligent Virtual Assistant) which lowers the cost of high-touch interactions.
Armored with the knowledge of why and in what mood a customer is contacting a business can help them proactively plan out the solution to not just acquire new customers but also retain the existing ones. They can either push visitors through the sales funnel or apply customer retention strategies – all at the back of the information they gather from the conversational AI platform.
Not every task requires human intervention. Conversational AI helps with identifying and addressing low-efforts texts or calls, giving the executives the space to focus on complex interactions. Through the automation of these tasks, the technology drastically lowers the operational cost of the contact center and the time it takes to perform manual data entry.
Conversational AI platforms give businesses a deeper understanding into their customers – concerns, background of the interaction, context of their message, etc. Backed by this information, businesses can make decisions which would impact not just the customer journey but also their revenue.
Businesses, across the globe, have increased their efforts behind providing high accessibility to their customers, making their brand more diversity friendly. By using conversational AI platforms with powerful NLP systems, they will be able to add in features like translate audio to text or even text to speech – making it easy for people with disabilities to interact with their business.
These are only the surface-level benefits that businesses can get from conversational AI platforms. The fact is, the more the technology will grow, the wider the use cases will be. For a business, however, it is equally crucial to understand which version of the conversational AI would help them attain the most benefits.
Mainly, conversational AI capabilities can be integrated into these different versions – Conversational AI Chatbots, Voice Assistants, Interactive Voice Recognition Systems, and Mobile Assistants. Now, out of all these different versions of conversational AI, there is one which is often used synonymously with the technology – chabots.
[You may like reading: How ChatGPT integration helps an enterprise business improve its operations]
Let us look into the difference in Chatbot vs. conversational AI in the next section.
It is true that conversational AI is usually incorporated into chatbots as they have been time-tested to offer immediate, convenient replies. However, not every chatbot has a conversational AI in it.
Have you ever experienced interacting with an annoying chatbot that keeps asking you the same information on every visit? There are very high chances that what you are interacting with is indeed a non-conversational AI powered chatbot.
Conversational AI chatbots are built to be more intuitive and natural, baked with the ability to map your previous interactions, details with the bot. On the other hand, chatbot developers write all the probable responses and feed them into the bot. Next, the user inputs are matched with the keywords in the response and the scripted answers are provided to them.
The working of conversational AI, as we will see later, is very different.
|Powered by deep learning||Powered by keywords and phrases|
|Acts on the context and emotion of the user||Acts on manually crafted rules|
|Learns from interactions||Difficulty in training|
|Understand the different language nuances||Difficult to scale|
|Reinforcement learning is possible||Rules have to be explicitly updated|
As you must have gathered, the key difference between conversational AI and chatbots lies in the way they work. Let us look at how different the working of a conversational AI actually is.
Here are the step-by-step versions of how a conversational AI chatbot works.
The user provides input through text or voice.
If the input has come in in a textual format, natural language understanding is applied to derive the meaning. If the input is based on speech, ASR automatic speech recognition is applied to analyze the language.
Natural language generation technology is applied for creating a response to the users’ query.
The user inputs are constantly analyzed for refining the replies over time, ensuring that the responses become as natural as possible.
Up until this point, we have looked into the many aspects of conversational AI, including the basics of how to build conversational AI platforms. I am sure you would have gotten an idea of how it would benefit your brand. Now to take this understanding ahead, let us look into the top industry-wide use cases of the technologies.
It is true that conversational AI is still in its infancy stage. But what cannot be ignored is the growing global adoption of the technology by businesses looking to elevate their customer experience efforts.
Being a renowned AI development services provider, we understand that there are some challenges which remain, like analysis of the language input, apprehension of the users around the information that the technology uses, etc. However, in our portfolio we have more answers around ‘what is an example of conversational AI’ than ‘how can the technology turn off my customers’, meaning we have been witnessing a rise in curiosity and demand among the entrepreneurs for the technology than the apprehensions.
Our aim as a software development firm is to make entrepreneurs confident when investing in disruptive technologies. So, when we use the technology of generative AI services, we answer the question ‘how to build a conversational AI platform’, we answer it through these stages –
With this, we have looked into everything that an entrepreneur needs to know about conversational AI to get started with the technology. And we have also stated what would make us your best technology partner as you explore the technology.
What are you waiting for? Reach out to us and give your customers what they need – a listening ear that works according to their needs.