Today’s businesses are always looking for ways to improve customer experiences while cutting service costs. Chatbots and conversational AI are two technologies that can help achieve these goals, but they are often misunderstood and used interchangeably. It’s important to understand the differences between them to determine which technology will have the most impact on your customer service and bottom line.

What’s the Difference Between Chatbots and Conversational AI?

Chatbots are computer programs designed to simulate human conversation. They come in two main types: rule-based and AI-driven. Rule-based chatbots operate on predefined conversation flows and are ideal for answering FAQs and handling basic customer inquiries. AI-driven chatbots, or virtual agents, use machine learning (ML) and natural language processing (NLP) to understand user intent and provide more accurate, context-aware responses.

Conversational AI is a broader term encompassing AI-driven communication technologies, including chatbots and virtual assistants like Siri and Amazon Alexa. These platforms use ML, NLP, and data to recognize vocal and text inputs, mimic human interactions, and maintain conversational flow. Conversational AI is particularly effective at replicating human interactions, enhancing user experience, and reducing the workload on human agents by handling simpler inquiries.

What is a Chatbot?

Rule-based Chatbots: Also known as decision-tree, menu-based, script-based, button-based, or basic chatbots, these are the simplest form of chatbots. They follow predefined rules to respond to user queries. These chatbots are perfect for addressing common questions and providing basic customer support.

AI Chatbots: Also called contextual chatbots or virtual agents, these use ML and NLP to understand user queries and improve their responses over time. They offer a more advanced level of interaction, continually learning from customer conversations to provide more accurate and helpful responses.

What is Conversational AI?

Conversational AI technologies can recognize and respond to both speech and text inputs. This technology is used in customer service to interact with customers in a human-like manner, whether through a chatbot in a chat interface or a voice assistant on the phone. By analyzing large sets of training data, conversational AI helps deep learning algorithms better understand human language and user intent.

How Chatbots Relate to Conversational AI

While all chatbots are a form of conversational AI, not all chatbots use conversational AI technology. Rule-based chatbots use simple keyword matching and predefined responses. In contrast, conversational AI chatbots use advanced algorithms to provide more natural and effective interactions. This leads to improved user experience and higher agent satisfaction, as AI handles routine queries and human agents focus on more complex issues.

Chatbots and Conversational AI in Customer Service

Businesses of all sizes benefit from automated messaging technology. Whether using rule-based chatbots or conversational AI, companies can offer quick and efficient customer support. For example, Domino’s Pizza and other major brands use this technology to handle customer requests promptly and effectively.

Chatbots in Customer Service: According to Zendesk, customer service teams handling 20,000 support requests monthly can save over 240 hours per month by using chatbots. This significant time saving allows teams to focus on higher-value tasks.

Conversational AI in Customer Service: Conversational AI is becoming a standard in customer service. Juniper Research predicts that conversational AI will drive approximately $12 billion in retail revenue by 2023. Furthermore, a PwC study found that 52% of companies ramped up their adoption of automation and conversational interfaces due to COVID-19, with 86% considering AI as mainstream technology.

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