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What is Conversational AI and How is it Different from Chatbots

April 26, 2022 • 5 minute read

AI has given our businesses a new dimension of growth. It has a variety of superintelligent applications. Today big data and automation are on the minds of all the business leaders of the world. With such penetration of technology and artificial intelligence, conversational AI has become a necessity for businesses while serving stakeholders and consumers.

What is conversational AI?

Conversational AI is an AI technology that encompasses conversational agents & natural language technology such as NLP, NLU that enable conversational platforms and are used to build conversational agents. This technology could be integrated with a website, a social media app, or any user interface to simulate human-like conversations.

The growing popularity of conversational AI has created a buzz in the marketplace. As per Gartner’s report, by 2021, 50% of enterprises will spend more per annum on conversational AI than traditional mobile app development.

Conversational AI builds a bridge between customers and enterprises to have conversations more smoothly and intelligently. It helps in the automation of all the business interactions with artificial intelligence and its capabilities of understanding human language, learning, dialog flow management, and data processing.

What is most compelling about conversational AI is its ability to transform the whole process of customer engagement- in marketing, sales, HR, customer support, and complete customer experience. Customers feel more connected with the brands and thus allow them to know more about their habits and behaviors. With this knowledge, brands land more conversions and better deals, and thus, improved revenue.

Now that we know what conversational AI is, let us look at how it works?

Components of conversational AI

Conversational AI uses a few technical aspects of artificial intelligence. For conversations, NLP (Natural Language Processing), ML (Machine Learning), and data mining are important. Also, to enable the voice-chat option, ASR (Automatic Speech Recognition) is used.

Components of conversational AI

Understanding each of these in detail is essential for utilizing conversational AI to its full potential.

1. Machine learning

Machine learning (ML) is a concept of artificial intelligence, made of algorithms, that can improve automatically through experience and by the use of data. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.

In conversational AI, machine learning is used to improve the quality of interactions between customers and enterprises. This process of learning and improving happens automatically without the need for humans to update the source code.

As it receives inputs from customers, the AI platform starts understanding the pattern and intent and starts making predictions. 

2. Data mining

Data mining is another important aspect of artificial intelligence focusing on data analysis through unsupervised learning. Its properties overlap with those of machine learning but however machine learning focuses on predictions using the current data, data mining is a technology used for knowledge discovery of unknown properties.

3. Natural Language Processing (NLP)

Natural language processing is a field of artificial intelligence used by conversational AI to understand and interact with humans in a natural human language. It basically understands what is a customer trying to say and detects the language in which he/she wants to communicate.

NLP consists of four major steps in the process of understanding human language- input generation, input analysis, dialog management, reinforcement learning. Using these processes, a human message is read and understood by a computer, analyzed to generate an appropriate response.

At Yellow.ai, we use NLP to provide the best solutions for conversational AI- text-based or voice-based.

4. Automatic speech recognition

Another technology that comes with conversational AI, speech recognition or automatic speech recognition (ASR) is used for voice-based conversations. It converts speech to text (STT) for the software to understand and respond accordingly.   

Difference between conversational AI and chatbots

Usually used interchangeably, chatbots differ from conversational AI in a lot of ways. 

Difference between a traditional chatbot and conversational AI

1. AI-powered

To begin with, a chatbot does not have any AI capabilities and runs on a basic if-else rule-based tree of questions and answers.

Conversational AI, due to the presence of NLP, understands human language and interacts in a customer-friendly manner.

2. Data trained

Chatbots, or FAQ bots, can only provide answers to a predefined set of questions. For any other query, customers need to interact with human agents as per their availability. This becomes a churn for customers and deteriorates their customer experience.

Conversational AI learns from the training data provided by the organization and understands customers’ queries. It comes up with an appropriate response immediately.

3. Personalized conversations

Chatbots have a lack of personalization capabilities. They can use only a set of data about the customers.

Conversational AI can learn all the new data about customers, understand their sentiments and intent behind the conversation and interact with them personally, humanly. Customers love this feature and easily convert from a potential lead to a customer.

These functional differences of conversational AI give it an edge over chatbots and help businesses improve their customer experience.

With these differences, conversational AI becomes a very powerful tool and has a number of benefits and usability.

4 compelling reasons to use Conversational AI

Using artificial intelligence in business communications has proven to be extremely beneficial and effective for businesses. The growth of the conversational AI market is proof of these benefits. Companies are shifting to providing a customer experience that is favorable for the customers and for this they need conversational AI.

The benefits of conversational AI can be categorized as customer-driven benefits and business-driven benefits. Let us dive deeper into these.

Customer-driven benefits of conversational AI

1. Unstoppable customer support

As you deploy a conversational AI chatbot, customers start to enjoy an excellent customer support experience 24x7, all year. This allows them to contact businesses at their convenience and comfort. 

For example, if a bank uses conversational AI, customers won’t need to visit the bank for concerns like checking their account balance or changing their contact information. With the internet at customers’ fingertips, everything is possible over the web.

2. Personalized guidance

For businesses with complex functions and difficult websites, conversational AI provides the customer a path to follow while completing a task. This is done by prompting messages over the chat window for giving personal guidance to the customer. 

With the help of this feature, customers can complete complex tasks on their own without any human assistance. It saves time and effort and customers feel accomplished and happy.

Conversational AI also understands the intent of the customers while interacting with them. So educating the customer about the products or services also eases the buyers’ journey.

3. No barrier communication

Communicating with conversational AI chatbots is relatively easier as compared to humans. Chatbots are multilingual and interact in more than 100 languages without the need for any translator. Customers can easily communicate in their preferred language and solve their queries.

Along with this, the time barrier is also lifted in the case of conversational AI. Customers and businesses can interact with each other at any time of the day (without thinking about the time zones), even if it is a public holiday.

Multilingual no barrier communication with Conversational AI

4. Lightning fast, appropriate responses

Conversational AI chatbots are fed with training data at the time of their deployment. That data contains details about all the existing customers, their orders, and the issues they faced while ordering, tracking, or paying for the product.

With all this data, conversational AI derives useful information and uses it at the right time. 

For example, if a customer tries to track their order, a conversational chatbot would directly provide the tracking information without any delay in asking for customer details or product information.

Business benefits of conversational AI and customer benefits of conversational AI

Business-driven benefits of conversational AI:

Conversational AI, ideally, provides communication solutions to businesses, by answering questions, providing recommendations, simplifying transactions, and most importantly supporting customers throughout their buyers' journeys.

1. Reduced operational time and costs

Conversational AI saves a lot of time for the human personnel working in the customer service of a business. It considerably reduces the number of customer support calls and emails and helps companies save efforts of solving mundane and repetitive customer queries.

It also saves costs of hiring and training employees for the customer experience department. Most of the tasks can partially or completely be automated using conversational AI.

2. Improved CSAT and CLV

With better customer engagement and support comes better customer satisfaction. Conversational AI definitely increases customer satisfaction (CSAT) score for a company and also improves customer lifetime value.

If a conversational AI chatbot is nicely configured, it can help companies with a higher customer retention rate and customer loyalty. Basically, it can make customers like your business more because of a good customer experience.

3. Effective lead generation

Conversational AI understands the intent and sentiment of a customer behind the conversation. And also it has a previous record (if any) of the customer to understand the requirements and choices.

With this data, conversational AI generates insights about the customer and helps in the upselling of products and services.

Apart from that, customers are comfortable sharing their details with AI chatbots. So with conversational AI, companies can generate qualified leads.

4. Data collection and analysis

Businesses can track their improvement in customer experience. There is a chance of missing data with human agents, but with conversational AI, data analytics is easier.

Especially, with Yellow.ai’s conversational AI chatbot, analytics and insights dashboard is separately provided to understand customer session duration, calling of human agents, and other metrics like the number of messages, reviews, and ratings. Companies can also get a customized dashboard with custom analytics of their choice.

These benefits are extremely tempting but deploying conversational chatbots come with some challenges.

Challenges assigned with Conversational AI

Conversational AI needs advanced technology to overcome some of the challenges that come with it. These challenges include:

1. Constantly changing communication 

Constantly changing communication is a task for conversational AI. With new acronyms like FOMO (fear of missing out), rn (right now), and others coming to conversational AI as a natural language, it can be difficult to understand and keep up with the trends.

Accommodating these changes regularly and understanding each and every word of every dialect is not possible even for conversational AI.

2. Privacy and security concerns 

Privacy and security concerns need to be addressed with conversational AI in action. All the conversation platforms must be secure and trustworthy for the customers.

Especially when sharing sensitive personal information, companies must make conversations and platforms heavily guarded so the customers feel safe and freely share information over all channels.

3. Language input 

Language input can be difficult for conversational AI, both text and voice. Regional tone and dialect, background noise, slang, sarcasm, are some of the challenges that artificial intelligence faces.

Appropriate responses become difficult with these challenges and sometimes interactions can get weird and dissatisfying for customers.

The top players of conversational AI in the market are constantly trying to overcome these challenges and will be able to find a solution soon. However, the current versions of conversational AI have all these challenges in consideration are far better than the traditional chatbots even in case of challenges.

We have covered almost all the aspects of conversational AI in this blog. Let us look at some of the examples where conversational AI has played a major role.

Use cases of conversational AI

Out of hundreds of thousands of conversational AI chatbots currently running in the world, here are a few examples for your reference.

1. Sayurbox improved CSAT by 45%

Sayurbox is a farm-to-fork, mobile-first e-commerce platform for purchasing fresh produce that is cherry-picked, and delivered directly from farms to consumers (B2C) and restaurants (B2B).

Their major challenge was managing the large volume of incoming queries and lack of agent availability. With Yellow.ai, Sayurbox automated end-to-end customer experience and boosted their CSAT by 45%.

2. ZALORA saved $250k in man-hours per quarter

ZALORA is a premium Fashion & Retail destination in Southeast Asia with a perpetually growing presence in the fashion, beauty and lifestyle space.

They wanted to improve their support operations while working within the limitations of their current workforce.

With Yellow.ai they introduced multilingual support and omnichannel customer experience.

The use cases of conversational AI chatbots are endless. To understand the immense possibilities of the application of conversational AI to your business, you need to try to create your own chatbot.

Conversational AI and automation is the next step in CX and business communications. Take that step and win the hearts of your customers. Businesses from all industries are actively using conversational AI and are extremely happy with the results. Begin the process of automation for your business today.

Implement conversational AI to automate your operations

Yellow.ai can help you with all the solutions that you need to implement to automate your CX and be a leader in your industry.

Experience the capabilities and understand the growth of your business by implementing conversational AI.

If you need more information or are confused about if this technology can help your business, schedule a demo with us. Our experts will get in touch with you and clarify your queries.

Namrata Narsinghani

Content Writer at Yellow.ai, comes with a zeal to write content that educates audiences, creates brand awareness, and ranks on SERP. A digital marketing enthusiast, she loves to learn all new trends in the industry. Apart from work, she loves to swim, read, and travel.

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