Communicating with customers is not a trivial task in today’s time. Customer expectations are rising steadily, and they expect unforgettable interactions when interacting with a business. Yet, responding to customers according to their preferred channel at the desired time can be cumbersome.
Conversational AI can become a powerful tool in this context. It helps improve customer communication efficiently by providing fast and accurate responses to their queries.
The importance of the effective use of AI in customer engagement cannot be downplayed anymore. Businesses adopt technology more readily, and conversational AI is no different. As a result, the rate of using AI conversational tools is expected to grow by a CAGR of 21.9% globally over the next three years.
AI-based conversational tools allow businesses to employ virtual assistants and cost-effective solutions to bolster their relationships with their customers across multiple digital channels.
Moreover, these AI-powered tools leverage effective conversational interfaces to capture a more significant chunk of the highly competitive market and improve their presence among peers and competitors.
For example, a chatbot can transform the way companies engage their customers across channels and according to their preferred touchpoints. It presents an entirely new and interactive scenario for businesses across sectors for businesses serving both customers and stakeholders.
Consequently, industry leaders must understand the technology behind AI-based conversational tools to gain insights into customer behavior. In addition, knowing the core principles and working of AI in conversation can help businesses determine the best way to leverage it.
Let’s take a look at how.
What Is Conversational AI?
The term conversational AI refers to artificial intelligence to communicate with customers and visitors according to their online persona. The technology combines several communication technologies, platforms, and channels.
It supports dynamic and fluid response scenarios without a predefined scope. Usually, it communicates with the customers by learning their online behavior and browsing patterns.
Conversational AI leverages its ability to communicate with the customers by offering greater flexibility and a human-like interface than rule-based chatbots.
Subsequently, it allows businesses to provide micro-segments and scalable support to provide personal engagements. Further, using AI in conversations can improve engagement, customer experience, and customer satisfaction by quite a notch.
In other words, conversational AI seeks to simplify interactions, provide better understanding, and simplify processes that help businesses grow more efficiently.
How Does Conversational AI Work?
The Conversational AI platform utilizes the capabilities of multiple cutting-edge technologies, including natural language processing (NLP), intent recognition, entity generation, and text-to-speech.
Typically, an AI-based conversational application deploys the following steps when it receives a communication from customers:
Components Of Conversational AI
Conversational AI applications are created by combining the capabilities of the Natural Language Processing (NLP) algorithm with machine learning algorithms.
It is expected to interact with users intuitively and adapt quickly to their needs and preferences by design. At the base level, the working principle depends on:
- Machine Learning (ML) –Recognizes and analyzes how human agents respond to users and is performed with the assistance of algorithms, features, and data sets.
- Natural Language Processing (NLP) – Help ‘reading’ or parsing, which allows it to understand natural sentence structures rather than simple keywords.
- Integrations – Allow autonomous operations and processes by allowing integration through APIs to enable end-to-end functionality.
The Benefits Of Conversational AI
The exponential growth of internet usage has prompted many businesses to adopt conversational AI in recent years. The increasing demand for fulfilling customer expectations requires enterprises to connect with people personally. The following are a few benefits of conversational AI:
- Increase efficiency in operational costs
Staffing the customer service department can be extremely costly for any business. The issue aggravates further if you need to increase your workforce to respond to customers outside regular business hours. Conversational AI helps small and medium-sized companies to take care of the staffing issues by deploying an AI-based response system, which can respond to queries autonomously irrespective of the business timings.
It can help you optimize the workforce, keeping the budget within pre-planned levels. A virtual assistant or chatbot can respond quickly, giving potential customers 24-hour access to your response system.
- Boost revenue growth via cross-selling and up-selling
A conversational AI helps build loyalty among customers by connecting and engaging with them proactively. It allows you to improve customer experience through relevant product recommendations and promotions, subsequently upsell and cross-sell products.
- Improve adaptability
Conversational AI provides a faster response to customer queries than your human customer support executives do. The immediate response system helps customers feel more valued and attended to, improving the quality of the overall customer interaction.
In addition, since AI leverages machine-learning algorithms, it increases the system’s adaptability with repeated interactions.
- Assist existing customer support agents
Ai-based conversational tools can communicate with your customers without the need for human supervision. Further, it can interact with multiple customers simultaneously, using individual customer data sets. Therefore, it can be “taught” to handle repetitive and less critical tasks without requiring any human agent to intervene.
For example, an AI chatbot can help your customers know their account balance or find a store location. This helps save time and effort for agents, which can handle more complex cases requiring their attention.
- Helps to scale as per requirements
Conversational AI tools can be integrated with your technology stack. It improves the usage of the existing technologies and information sets to improve the overall infrastructure.
This, in turn, enhances information processing fast and efficiently at a lower cost, without the need to recruit or onboard new staff. This can prove effective for businesses to scale quickly or handle the momentary spike in business, such as during the end-of-season sale.
Use Cases Of Conversational AI
A conversational AI provides an automated customer support service leveraging omnichannel deployments using chatbots and voice assistants. Further, these apps leverage a vast amount of customer data and use real-time analytics at the back end. Consequently, the apps help in ensuring a human-like interaction for the customers.
Yet, there are several misconceptions regarding the use of conversational AI. In an ideal scenario, artificial intelligence is expected to create a human-like intelligence based on the consciousness that can solve complex issues faced by the customers.
However, AI-based tools emulate human intelligence in real-life scenarios by observing and identifying patterns based on a predefined behavioral set. Still, its enhanced ability to parse data and provide intelligible solutions can benefit businesses immensely.
Further, the “learning ability” of the AI tools can give a near-humanlike experience for the customers and become indistinguishable for them.
Below are some use-case examples:
Online Customer service system
The entire lifecycle of a customer has moved online. From product discovery to conversion, the customer journey now expects seamless support during every stage of the journey.
Utilizing AI-based chatbots can minimize human interventions and respond to customer queries faster. Handling commonly asked questions like FAQs, account information, or other repetitive tasks.
Further, AI tools can use personalized communication using the past customer data to improve the customer experience effectively. Several such chatbots are already available. This includes the bots handling e-commerce site transactions with virtual agents, messenger apps, such as Slack or Facebook Messenger, and bots automating the tasks usually handled by virtual assistants.
Providing accessibility: Companies can become more accessible to their customers by lowering initial entry barriers, particularly for users of assistive technologies. Conversation AI’s most popular features include text-to-speech dictation and translation for these groups.
The HR process: A conversational AI can streamline employees’ training and onboarding processes. It can also update employee information and other HR processes.
Getting health care: A conversational AI system can make affordable healthcare more readily available. It can improve operational efficiency and streamline administrative procedures, such as claim processing.
IoT devices: The use of IoT devices is exponentially rising. Almost every consumer has at least one IoT device, such as Alexa speakers, smartwatches, and smartphones.
These consumers can communicate seamlessly via an automated speech recognition program installed in these devices. The most popular apps are Google Home, Amazon Alexa, and Apple Siri.
Challenges of Conversational AI
The majority of AI-based chatbots and apps already exist. Although they cannot mimic human interactions solving complex problems, they can still reduce the cost and time of repetitive interactions with customers, allowing better utilization of resources.
Businesses are already using AI-based customer engagement solutions in recent years. However, as with any technological development, specific challenges are yet to be solved. These are:
The language Input
Language input can be an obstacle for conversational AI, whether via text or voice. The AI’s ability to interpret raw text and spoken language input is dependent on its understanding of dialects, accents, and background noise.
As well, unscripted and slang words can complicate matters. Further, conversing with AI is a massive challenge due to the human factor. Conversational AI does not understand emotions, context, tone, or sarcasm; these factors are difficult to assess.
Safety and privacy
Conversational AI collects data from users to build their personas. This information helps the AI-based tools answer their queries, posing security and privacy risks if the online database is hacked or leaked.
However, businesses can win end users’ trust by building conversational AI apps that uphold high privacy and security standards while incorporating strict monitoring systems.
Customer Skepticism
Users can be hesitant about sharing sensitive information with machines, particularly if they realize that the conversation is with a computer rather than a human being.
The issue can be tackled by asking for their consent before using a conversational tool to communicate with them. Further, it would help if you looked to alleviate their concerns by educating them on the benefits of the tech stack. In addition, a direct-human response system can be used during complex situations.
Final Thoughts!
The modern-day customer wants a great customer experience when they interact with your business. Providing a fast-response customer support system can help you improve your customer interaction quality.
AI-based conversational tools enable you to leverage customer data at your fingertips and provide a resolution across touchpoints faster.
Additionally, it helps you optimize your workforce requirements, operational budget, and technological stack according to the requirements. Finally, conversational AI enables you to build a brand that the customers trust.