Is there a difference between ‘chatbots’ and ‘conversational AI’?

A few examples of conversational AI chatbots include Siri, Cortana, Alexa, etc. Depending on the sophistication level, a chatbot can leverage or not leverage conversational AI technology. REVE Chat is an omnichannel customer communication platform that offers AI-powered chatbot, live chat, video chat, co-browsing, etc.

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. His primary objective was to deliver high-quality content that was actionable and fun to read. From the perspective of business owners and developers, the most important difference between bots and advanced AI systems is that the latter is much harder and more costly to develop.

Rise of Online Shopping

As opposed to relying on a rigid structure, conversational AI utilizes NLP, machine learning, and contextualization to deliver a more dynamic scalable user experience. Businesses are always looking for ways to communicate better with their customers. Whether it’s providing customer service, generating leads, or securing sales, both chatbots and conversational AI can provide a great way to do this. And this chatting ability is the reason a chatbot can be used across marketing, sales, and support for creating better experiences for customers anytime. As natural language processing technology advanced and businesses became more sophisticated in their adoption and use cases, they moved beyond the typical FAQ chatbot and conversational AI chatbots were born.

We predict that 20 percent of customer service will be handled by conversational AI agents in 2022. And Juniper Research forecasts that approximately $12 billion in retail revenue will be driven by conversational AI in 2023. Remember to keep improving it over time to ensure the best customer experience on your website. It may be helpful to extract popular phrases from prior human-to-human interactions. If you don’t have any chat transcripts or data, you can use Tidio’s ready-made chatbot templates.

Customer Engagement Bots

A chatbot will be a suitable tool if your goal is to resolve simple customer queries around the clock. If your business needs a more potent tool to facilitate operations and enhance customer communication, a virtual assistant will benefit you the most. ChatGPT can be used to create personalized virtual assistants that help users with a wide range of tasks, such as scheduling appointments, managing finances, and more. Chatbots can be used to provide automated customer service, answering common questions and providing support to customers. For instance, when it comes to customer service and call centers, human agents can cost quite a bit of money to employ.

• Unlike an AI Chatbot, AI Virtual Assistants can do more because they are empowered by the latest advances in cognitive computing, Natural Language Processing, and Natural Language Understanding (NLP & NLU).
• Basic chatbots, on the other hand, use if/then statements and decision trees to determine what they are being asked and provide a response.
• Leveraging NLP, NLU, and machine learning (ML) capabilities, AI Virtual Assistants can understand and analyze the intricacies and nuances of natural human language.
• Machine learning technology and artificial intelligence program chatbots to work like human beings 24/7.
• These conversational bots should bring down your support and business costs and save you from hiring extra agents to cater to customer queries.
• Using conversational AI can lead to quicker and more precise responses to customer inquiries, resulting in shorter wait times and increased satisfaction.

Thinking about just how your potential customers might wish to engage with your product and the main queries they might have is the first step towards conversational AI. You may then employ conversational AI techniques to guide them to the information they need. Conversational AI’s existing applications, according to experts, are poor AI since they are focused on a very limited scope of jobs. Strong AI, which is still a theoretical idea, concentrates on a human-like consciousness capable of solving a wide range of activities and issues. If you’re confident you can predict customer pain points, common questions, and roadblocks on the way to a purchase decision, you’re ready to set up a chatbot and streamline the process. Thus, your chat widget will turn into a lead generation and conversion tool.

Conversational AI Beyond the Pandemic

However, most of these BI tools lack integration which means deriving insights from the data in different tools is still time-consuming and manual. At the same time, the extended lockdowns and travel restrictions meant consumers spent over 50% more time on messaging services such as Facebook Messenger and WhatsApp. This also became an opportunity to put conversational AI through its paces. Businesses built applications for messaging platforms and social media platforms to bring important services closer to their fingertips.

• They become more accurate with their responses based on their previous conversations.
• Learn how to deliver data-rich personalization at scale by integrating customer insights, apps, and AI in Zendesk.
• As a result, chatbots are often limited to performing specific functions within a narrow domain.
• By utilizing chatbots, customer inquiries can be answered promptly, reducing wait times and increasing customer satisfaction.
• These platforms use the advantages of real-world contact to give the user a more exciting and personalized experience.
• Chatbots use basic rules and pre-existing scripts to respond to questions and commands.

Rule-based chatbots don’t learn from their interactions and struggle when posed with questions they don’t understand. These chatbots are programmed to follow a set of rules, whereas conversational AI can recognize and interpret human language when responding to any customer responses. The fact that the two terms are used interchangeably has fueled a lot of confusion. However, some people may refer to simple text-based virtual agents as chatbots and enterprise-level natural language processing assistants as conversational AI.

Reduce operating expenses, lift sales

However, the widespread media buzz around this tech has blurred the lines between chatbots and conversational AI. Even though the terms are often used interchangeably, it’s crucial to understand their differences to make informed decisions for your organization. Because AI doesn’t rely on manually written scripts, it enables companies to automate highly personalized customer service resolutions at scale. This makes every interaction feel unique and relevant, while also reducing effort and resolution time. Businesses use conversational AI for marketing, sales and support to engage along the entire customer journey. One of the most popular and successful implementations is for customer service and customer experience, a $600B industry with a lot of repetitive knowledge work.

More so, AI-based chatbots are programmed to deviate from the script and handle queries of any complexity. By answering simple, frequently seen customer enquiries, they allow customer service agents to spend more time on tasks that require human input. While rule-based chatbots mainly use keywords and basic language to prompt responses that have already been written, a conversational AI chatbot can mirror human responses to improve the customer experience. Early conversational chatbot implementations focused mainly on simple question-and-answer-type scenarios that the natural language processing (NLP) engines could support.

WhatsApp Chatbot in UAE: Top 4 Vendors

As more and more typically ‘dumb’ chatbots use more and more AI capabilities, the temptation will be to call them ‘conversational AI’. That’s what’s led us to this point right now, where people are confused about the two. When I use metadialog.com the word chatbot, it’s often in the context of that website modality and channel, though the term itself is much broader than that. For example, an automated conversation with a WhatsApp ‘bot’ is still a conversation with a chatbot.

Conversational AI chatbots are, for example, very skilled at re-engaging customers that haven’t completed their purchases to drive sales and reduce the number of abandoned shopping carts. Because conversational AI bots have more advanced interaction skills, they can take over more tasks and improve automation processes in companies and organizations. NLU helps the bot understand the context of human language, such as syntax, intent, or semantics. From OpenAI’s GPT chatbots to Google’s Bard , AI-based technology has created quite a buzz lately. Natural language processing strives to build machines that understand text or voice data, and respond with text or speech of their own, in much the same way humans do.

Step 2: Prepare the AI bot conversation flows

Another difference between chatbots and conversational AI is the task span they can complete. As a result, chatbots are often limited to performing specific functions within a narrow domain. At the same time, conversational AI can handle a more comprehensive range of tasks and can be applied to a broader range of applications.

In other words, conversational AI enables the chatbot to talk back to you naturally. 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. Thanks to chatbots, customers can now order food without making a phone call. 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.

Conversational AI Chatbots Vs. Assistants

Although non-conversational AI chatbots may not seem like a beneficial tool, companies such as Facebook have used over 300,000 chatbots to perform tasks. Though some chatbots can be classified as a type of conversational AI – as we know, not all chatbots have this technology. Read about how a platform approach makes it easier to build and manage advanced conversational AI chatbot solutions.

Here’s a side-by-side comparison of the key features of live chat and chatbots. Unlike an AI Chatbot, AI Virtual Assistants can do more because they are empowered by the latest advances in cognitive computing, Natural Language Processing, and Natural Language Understanding (NLP & NLU). AI Virtual Assistants leverage Conversational AI and can engage with end-users in complex, multi-topics, long, and noisy conversations. They are available 24/7, which means that customers can interact with your business at any time. In this blog, we’ll explore the unique features of chatbots and ChatGPT, and help you understand which technology is best suited for your needs. Google’s Google Assistant operates similarly to voice assistants like Alexa and Siri while placing a special emphasis on the smart home.

• Chatbots are computer programs that simulate human conversations to create better experiences for customers.
• According to a report from National Public Media, 24% of people over 18 (around 60 million people) own at least one smart speaker, and there are around 157 million smart speakers in US households.
• Conversational AI combines natural language processing (NLP) with machine learning.
• This type of chatbot will be able to understand that “new wheels” and “new e-bikes” mean the same thing.
• Fintechs need to provide a stellar customer experience across the board.Learn more in our eBook today.
• These bots are like obedient puppies trained to follow a set of predetermined rules for communication.