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Chatbot vs Conversational AI – The Key Differences and Examples

Conversational ai vs chatbot
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    We often use the words “chatbots” and “conversational AI” interchangeably believing that both these technologies are synonymous. However, there are some key differences between chatbot vs conversational AI. 

    Despite the differences, both serve entirely the same purposes across sales, support, and marketing. They have the potential to transform the way customer service is delivered, which can ultimately have a big impact on the bottom line of a business. 

    However, as a business leader, you should know the differences between conversational AI vs chatbots. Only then can you  optimize processes and improve customer experiences (CX).  

    In this blog, we will discuss in detail all the differences between a chatbot and a conversational AI technology and also show examples from across industries to ensure absolute clarity on the subject.

    What are Chatbots? 

    Chatbots are computer programs developed to stimulate human conversations. They are a kind of machine that can chat. And this chatting ability is the reason a chatbot can be used across marketing, sales, and support for creating better experiences for customers anytime. 

    what-are-chatbots

    While some chatbots work based on a predefined conversation flow, others use technologies like artificial intelligence (AI) and natural language processing (NLP) to converse with users. Chatbots are often so advanced that they can easily decipher user questions and offer automated responses in real time. They can handle full conversations around 69% of the time.

    More so, chatbots can either be rule-based or AI-based and the latter are more advanced as they do not require pre-scripted rules or questions for sending responses. More so, AI-based chatbots are programmed to deviate from the script and handle queries of any complexity. 

    What is Conversational AI? 

    Conversational AI refers to artificial intelligence-driven communication technology ( such as chatbots and virtual assistants ) that uses machine learning (ML), NLP, and data for conversation. It is advanced enough to recognize vocal and text inputs and mimic human interactions to assist conversational flow. 

    what-is-conversational-ai

    Similarly, conversational AI is a technology that can be used to make chatbots more powerful and smarter. It’s a technology that can recognize and respond to text and speech inputs easily, therefore enabling interactions with customers in a human-like manner. Maybe that’s why 23% of customer service companies use AI chatbots for better responses. 

    When conversational AI technology is used, interactions can happen through a chatbot in a messaging channel or through a voice assistant over the phone. Unlike chatbots, it can determine user intent and also easily understand human language. 

    Conversational AI vs Chatbot-  What are the Differences? 

    From the above, it’s amply clear that conversational AI is a more powerful technology compared to chatbots. In fact, we have learned how a chatbot needs conversational AI technology to act smarter and become more intelligent. However, we should note that not all chatbots use conversational AI technology so not all will be powerful. 

    Chatbot 

    Conversational AI

    Lacks capability beyond performing basic functions

    Can perform complex tasks across sales, support, and marketing 

    Can best answer simple FAQs

    Can make chatbots smarter 

    Unable to interpret human language

    Able to interpret human language

    Supports tex-only command

    Supports both voice and text commands

    Fit for single-channel communication 

    Ideal for omnichannel communication 

    Enables scripted conversational flows

    Has natural language processing ability

    Supports linear interactions 

    Supports dynamic interactions

     

    There are more differences between a chatbot and conversational AI and some of them include –  

    • Limitations in functionality – A conventional chatbot lacks capability beyond performing a limited number of functions. In most cases, its ability stretches to answering basic FAQs. On the other hand, conversational AI is a technology that can boost a chatbot’s ability manifold and make it easily understand and interpret human language. 
    • Text-only command vs Voice and text commands – While a chatbot is capable of text-only commands ( inputs & outputs ), conversational AI can go a step further and enable both, voice as well as text commands at the same time. 
    • Single channel vs Omnichannel – Most chatbots are limited to being used as a chat interface only and this makes it fit for a single channel alone. On the other hand, conversational AI can enable omnichannel communication by being deployed across websites, voice assistants, etc. 
    • Scripted vs natural language processing – Since chatbot is basic in technology it can only enable scripted conversational flow based on pre-defined rules. And when there is conversational AI, it can come with the ability of natural language processing, therefore being easily able to understand and contextualize conversations. 
    • Linear vs dynamic interactions – A chabot can best support linear interactions whereas a conversational AI can go steps up and enable non-linear and dynamic interactions. For that reason, AI-enabled bots are best suited for customer support tasks. 
    • Navigation vs Dialogue – Compared to chatbots which support navigation, conversational AI is obviously more advanced and can support the dialogue of any complexity.  

    Chatbot vs Conversational AI – Which Solution is Better for Your Business? 

    As a business, whether you should go with a chatbot or conversational AI technology entirely depends on your goals and requirements. But there is no denying that conversational AI is far better technology than a traditional chatbot. Despite that, there are certain processes and tasks where a bot would seem more suitable and vice versa. 

    Chatbot – Business Suitability

    Conversational AI – Business Suitability

    Fit for answering simple FAQs on the website

    Can automate support across multiple channels and platforms 

    Query resolution with some human intervention 

    Query resolution without any human intervention

    Can’t answer questions beyond the script

    Can offer unscripted responses 

    Not contextually aware

    Contextually aware 

    Can’t comprehend multiple intents from a query

    Can comprehend multiple intents from a query

    Ideal for one-language support 

    Can support multiple languages

    Suitable for basic customer support tasks

    Ideal for complex tasks across sales, support, and marketing

    Parameters are many to choose from when you want to decide whether to take the help of a chatbot or conversational AI. 

    • A traditional chatbot would be perfect when your business needs something that can help answer simple FAQs on the website and take some load off the support team.
    • Conversational AI would be the right choice when your business needs to automate support across multiple channels and platforms using both text and voice. 
    • Basic chatbots may not be the right fit when your topmost priority is to increase user engagement and boost user satisfaction across stages of the customer journey. 
    • Conversational AI is the best fit when your focus is on query resolution with zero or minimum human intervention.  
    • Chatbots can learn on their own and even won’t answer questions that are not already incorporated whereas AI can go beyond the script and react according to past queries and searches. 
    • Conversational AI can be contextually aware which makes them understand the queries better and respond based on past data and searches. All this makes it offer the right answer which can prove valuable for customer service. 
    • Conversational AI platforms are powerful with the ability to comprehend multiple intents from a single question whereas a rule-based chatbot can’t do that. This is why e-commerce sites or websites that are into sales prefer a chatbot with AI capabilities to process customer queries effectively.
    • With chatbots, users can not give voice commands, and neither can they choose more than one language for queries. No such limitations exist with conversational AI technology where users are free to choose any language and voice command. 

    Use Cases for Chatbot vs. Conversational AI in Customer Service

    Chatbots and conversational AI both are helpful for various tasks in customer service. While chatbots are ideal for handling routine tasks, conversational AI is better suited to deal with more complex issues. 

    Let’s look at some of the use cases for chatbots vs conversational AI in customer service – 

    Chatbots

    • Handling Routine and Repetitive Queries – Chatbots are suitable for handling routine and repetitive queries, like those with FAQs. They can quickly provide scripted responses to common questions.  
    • Providing 24/7 Support – Chatbots can provide support to customers at any time of the day or night. They can be used to offer round-the-clock support to customers from any part of the world.  
    • Guiding users through simple tasks –  Chatbots are best suited for scenarios where customers need to be guided through simple tasks and processes. Be it placing orders or scheduling appointments, they can help users and guide them through all the steps. 
    • Routing queries to the right human agents – Chatbots can categorize customer queries and route them to the appropriate teams. They can categorize queries based on relevance and urgency, resulting in human resource optimization for businesses. 

    Conversational AI

    • Resolving complex issues – Conversational AI can handle more complex customer issues requiring nuanced understanding. Their advanced problem-solving capabilities help them strike relevant conversations with customers, ask questions, and offer customized responses
    • Offering personalized recommendations – Unlike chatbots that can’t use machine learning and data analytics, conversational AI can do both. This helps them analyze customer preferences and offer personalized suggestions based on individual needs.  
    • Ability to understand and respond to human emotions – Conversation AI can understand human emotions and offer responses based on that. They have a sentiment analysis feature to extract meaning from texts and audio scripts.  
    • Capability to process natural language and context – Customers today can expect more natural and content-driven conversations with conversational AI systems. This is because conversational AI can process natural language easily and respond based on the context. 

    Benefits of Conversational AI over Traditional Chatbots

    There has been an ongoing debate about conversational AI vs chatbots. However, experts are unanimous in their opinions because conversational AI is a more advanced and sophisticated technology than chatbots.  

    Let’s look at some of the key benefits of conversational AI over traditional chatbots – 

    • Natural Language Understanding (NLU) – Conversational AI can interpret user inputs more accurately as it uses advanced natural language processing (NLP) techniques. This helps them grasp human language more clearly, resulting in more meaningful interactions with users.  
    • Context-Driven Responses – Basic chatbots can’t remember previous user interactions nor can they maintain context during conversations. On the other hand, conversational AI has contextual awareness, so it can have more relevant and meaningful conversations with users.  
    • Machine Learning (ML) and Artificial Intelligence Algorithms (AI) – Conversational AI can leverage ML and AI algorithms. It makes it capable of handling complex issues easily. This ability enables it to offer tailored responses to users. 
    • Use of Data Analytics –  Traditional chatbots can’t leverage data analytics and machine learning models. Conversational AI can do that. This feature helps them offer targeted and relevant content to users, resulting in improved engagement. 
    • Continuous Learning – Conversational AI systems can learn and evolve through analysis of user feedback. So, their relevance and effectiveness can be increased aligning with the needs of customer interactions. 
    • Ease of Integration with Various Platforms –  Conversational AI can be integrated with websites, social channels, messaging apps, and voice-based devices. This feature makes it a valuable tool for customer service delivery.  

    Examples of AI Chatbot Uses Across Industries

    Chatbots have become a key tool across industries for customer engagement, customer satisfaction, and conversions. They can serve a variety of purposes across processes, therefore extending their usages as wide as the airline industry, financial services, banking, pharma, etc. 

    Some of the top examples of chatbot use across industries include – 

    BB Chatbot for KLM Royal Dutch Airlines 

    KLM Airlines is a good example of how to use a chatbot to simplify travel plans for users and also streamline procedures for businesses. The chatbot named BB will be accessible 24×7,  can support multiple languages, and provide faster responses. Using the chatbot, the airline is able to handle hundreds of travel queries efficiently, offer all the booking information with a click, and make customer support as effortless as it could get.   

    H&M Fashion Chatbot 

    Some of the top luxury brands in the world use chatbots to scale shopping services and provide great experiences to buyers. H&M is a good example, which is also a global fashion brand, in how to use a chatbot to successfully engage millennials and Gen Z customers and guide them through myriad outfit possibilities. The use of a chatbot has helped the brand increase sales and market its products more effectively. 

    Domino’s Messenger Bot

    Thanks to chatbots, customers can now order food without making a phone call. All they need to do is click a few buttons and choose what they want. Domino’s messenger bot is a good example of how to make the best of chatbot technology and ensure amazing service to customers. Since this chatbot lives in Facebook Messenger, customers will have the flexibility to order from different devices. More so, the chatbot can also track previous purchases and make the entire food ordering procedure as smooth as it can get.   

    EVA for HDFC Bank 

    When it comes to the chatbot in banking, there can’t be a better example than EVA by HDFC. It’s an AI-powered bot in the true sense that uses Natural Language Processing (NLP) and makes support as fast and effortless as it can get.  

    EVA can converse with users, answer queries quickly and offer accurate responses most of the time. Ever since this bank has started using EVA, its customer support has improved manifold and more queries handled than ever before.   

    The Future of Chatbots Vs Conversational AI

    Chatbots and conversational AI are two of the most innovative technologies of modern times. Both continue to evolve with immense potential in the coming years. Even today, both technologies impact various aspects of our lives.

    Let’s look at the future of chatbots vs conversational AI – 

    • Specialization – In the coming years, we might see chatbots for specific industries or tasks. The same might happen with conversational AI which can also specialize in integration across industries. 
    • Integration with IoT Devices – Both technologies will integrate with IoT devices where chatbots can facilitate basic interactions while conversational AI enables complex tasks. 
    • Improved NLP Capabilities – In the future, we can expect chatbots and conversational AI to have improved NLP capabilities for more human-like interactions. 
    • Enhanced Sentiment Analysis – Chatbots may soon have the feature to understand human emotions while conversational AI will adapt conversations based on user emotions. 
    • Advanced Potential for Natural Conversations –  The days are not far when chatbots will get adept at more natural conversations and conversational AI bridges the gap between human and AI interactions. 
    • Higher Levels of Autonomy – Chatbots will soon become more advanced and can handle tasks autonomously with less reliance on scripts. Conversational AI may soon get advanced enough to make complex decisions.
    • AR/VR Integration – Conversational AI is set to expand on virtual interactions and immersive experiences. Chatbots may not have more than limited integration with AR or VR.

    Power Your Business Ahead with REVE’s AI-driven Chatbot

    Rule-based chatbots have some limitations and they are surely not the best option when a business thinks of catering to modern customers and needs. 

    We, at REVE Chat, are aware of the shortcomings that scripted chatbots can have and therefore help businesses easily design the best chatbot they can.

    Using our platform, it’s quite simple to design an AI-powered chatbot in quick time, and that too, without writing a line of code. 

    The bot can be customized to meet the specific needs of the business whether in support, sales, or conversion. 

    More so, bots are not the only engagement tools that are available on this platform you can also get other ones as well, including co-browsing software and video software. 

    What’s more, you can combine the live chat software with the chatbot and ensure hybrid support to users across the journey with your brand.

    Design a Conversational AI Chatbot with REVE and Grow Your Business

    A business can definitely excel to new heights when it has the best tools at its disposal for executing tasks across various departments. 

    Having a conversational AI chatbot thus becomes important when the main focus of a business is on customer engagement and experience.

    With REVE Chat, you can start a free trial of a chatbot and other support tools and see how they would fit into the specific needs of your business. 

    So, take the right step ahead and get a chatbot that can serve all your business needs as perfectly as it can be. 

    Frequently Asked Questions?

    How do Conversational AI and Chatbots differ in their capabilities?

    Chatbots rely on scripted or pre-defined responses and have limited functionalities. So, they are ideal for basic interactions only. On the other hand, conversational AI integrates advanced natural language understanding and can engage in sophisticated conversations.   

    What are some examples of Conversational AI applications?

    Virtual assistants like Siri, Alexa, and Google Assistant are top examples of conversational AI applications. 

    Do Conversational AI and Chatbots impact user experience differently? If yes, then how?

    Yes, both impact user experience differently. While chatbots focus on handling basic queries and automating routine tasks, conversational AI can engage in human-like interactions and offer natural responses. 

    How are Conversational AI and Chatbots Different in Approaching Complex Queries? 

    Chatbots rely on pre-scripted responses and therefore are suited for simpler queries only. In contrast, conversational AI can understand context and language, and offer personalized solutions.

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    Praveen Singh
    AUTHOR’S BIO

    Praveen Singh is a content marketer, blogger, and professional with 15 years of passion for ideas, stats, and insights into customers. An MBA Graduate in marketing and a researcher by disposition, he has a knack for everything related to customer engagement and customer happiness.

    As a writer and analyst, he pours the heart out on a blog that is informative, detailed, and often digs deep into the heart of customer psychology. He’s written extensively on a range of topics including, marketing, AI chatbots, omnichannel messaging platforms, and many more.

    Mr. Singh also has a passion for subjects that excite new-age customers, be it social media engagement, artificial intelligence, machine learning. He takes great pride in his learning-filled journey of adding value to the industry through consistent research, analysis, and sharing of customer-driven ideas.

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