Conversational AI vs. Chatbots: Understanding the Differences
The terms “chatbots” and “conversational AI” are often used as equivalent terms, but they’re worlds apart. Get the difference right, and you’re not just improving customer service, you’re setting yourself up for the success.
UK retailers are constantly looking out for opportunities to deliver exceptional customer experiences while keeping operational costs in check. By 2025, it’s predicted that the UK retail sector’s use of AI-driven customer service will grow by 35%, helping them deliver better support. In their search for solutions, many are turning to automation technologies like chatbots and conversational AI.
But here’s the catch: automation isn’t the same as AI. Traditional customer support automation relies on fixed, rule-based responses, while AI-driven support offers context-aware, flexible solutions. Therefore, understanding the difference between chatbots and conversational AI is crucial to providing a great customer service experience.
Understanding the differences between chatbots and conversational AI
Chatbots are computer programs that mimic conversations with customers. Some chatbots follow fixed scripts, meaning they can only respond to specific questions in a set way. These chatbots are suitable for handling simple, repetitive tasks like answering frequently asked questions or providing basic information.
Conversational AI is a broader technology that includes chatbots and more advanced systems like virtual assistants. These platforms use AI, machine learning (ML), and NLP to understand and interpret written and spoken language. It can process complex customer inputs, learn from interactions, and engage in more natural, context-aware conversations, offering a more sophisticated level of interaction than basic chatbots.
Moreover, the ROI from AI-driven customer support goes beyond just cost savings. AI-driven customer support boosts sales by offering personalised recommendations and support, enhancing the overall shopping experience. When customers feel well taken care of, they are more likely to return and make additional purchases. This combination of cost savings and increased sales creates strong and measurable returns for retailers.
” TL;DR: Chatbots follow simple scripts, while conversational AI thinks, learns, and adapts. “
What are chatbots?
Chatbots have been around since the 1960s, starting with early examples like ELIZA, a program designed to mimic a therapist. Over time, chatbots evolved with the internet and became widely adopted in the 2000s for handling basic customer service tasks like answering FAQs and assisting with orders.
Their simplicity, based on rule-based scripts, made them easy to implement, and they’ve remained popular for businesses looking to automate repetitive processes. According to Grand View Research, the chatbot market was valued at $2.6 billion in 2020 and is expected to grow rapidly, reflecting their continued use in customer support across industries like retail, banking, and travel.
What is Conversational AI?
Conversational AI emerged in the 2010s as AI technologies like machine learning, NLP, and deep learning advanced. Unlike traditional chatbots, conversational AI systems can understand context, learn from interactions, and adapt in real-time. Virtual assistants like Siri, Alexa, and Google Assistant popularised this shift, allowing for more sophisticated interactions that feel natural and intuitive.
As adoption grows across industries, mainly in retail, companies are leveraging conversational AI to provide more personalised customer experiences, driving efficiency and improving satisfaction. By 2025, it’s expected that conversational AI will power 75% of all customer service interactions, as predicted by Gartner.
The conversational AI market is also forecast to reach $13.9 billion by 2027, growing at a 21% CAGR, as reported by Statista.
Chatbots and Conversational AI: A head-to-head comparison
Here’s a comparison table that outlines the differences between Chatbots and Conversational AI:
Feature
Conversational AI
Chatbots
Overview
Advanced AI-driven systems that enable dynamic, human-like interactions.
Basic programs that simulate simple conversations.
Technology
Uses AI, Machine Learning, and Natural Language Processing.
Primarily rule-based or predefined scripts.
Learning Ability
Learns from interactions, improves over time with ML and data analysis.
No learning capabilities, follows fixed responses.
Response type
Context-aware, dynamic responses that adapt to the conversation.
Fixed, scripted responses to specific queries.
Complexity
Handles dynamic, personalised conversations across various topics.
Handles basic tasks and repetitive queries.
Use cases
Customer service, virtual assistants, personalised shopping assistance, complex problem-solving.
Customer service for FAQ, basic inquiries, and appointment scheduling.
Human-like Interaction
More natural, intuitive, and context-aware, providing a human-like experience.
Limited to preset patterns, can feel robotic.
Integration
Can be integrated into multiple channels (web, voice assistants, smart devices, etc.) for broader interactions.
Often integrated into websites, apps, or social media for specific tasks.
Scalability
Scalable for handling complex, nuanced interactions, offering broader support.
Good for handling high volumes of simple tasks.
As we discussed earlier, chatbots are great for handling simple, repetitive tasks. Think of them as robots following a script, which works well for simple inquiries or scheduling. But they don’t get smarter with time. Conversational AI, on the other hand, is the real deal. It uses advanced AI technology to understand context, adapt to conversations, and learn from interactions.
This allows for much deeper, more personalised interactions, handling everything from complex customer issues to anticipating their needs. And this is important! Why? Because the modern customer service isn’t about static responses, but it’s about intelligent systems that evolve and get better at helping your customers.
Chatbots and Conversational AI: Handling customer inquiries
Chatbots and Conversational AI handle customer interactions in different ways. Let’s put them into test. Here are common scenarios showcasing how each type responds.
Scenario 1: Product availability
In a scenario, when a user asks about product availability, the chatbot will simply respond with a “yes” or “no” depending on the stock status. If the item is available, it confirms the availability; if not, it suggests buying something else.
However, the chatbot lacks the ability to engage in a deeper conversation, offer alternatives, or provide personalised recommendations.
On the other hand, Conversational AI can guide users through the shopping process by seamlessly integrating with the cart. In this scenario, once the product is confirmed to be in stock, the AI offers the option to add the Nike Air Max to the user’s cart, creating a more interactive and convenient shopping experience. This allows users to take immediate action without needing to navigate the website themselves.
If the product is unavailable, Conversational AI goes beyond a simple “out of stock” message by proactively recommending similar styles. This provides the user with alternative options, helping to keep the shopping experience fluid and engaging.
It encourages further interaction by asking if the user would like to explore these alternatives, increasing the chances of conversion even when the original product isn’t available.
If the user responds with “Yes,” Conversational AI proceeds to present a list of alternative products, saying, “Here are some alternatives: [Product List]. Would you like to order one of these?” This keeps the conversation moving forward by offering options for the user to consider.
If the user says “No,” the AI respectfully acknowledges the response with, “Alright! Let me know if I can assist you with anything else,” leaving the door open for further assistance and maintaining a helpful, conversational tone.
Scenario 2: Order Issue
Consider another scenario where a customer reaches out with an issue about their order. The customer might say, “I’ve received a damaged item,” “I’ve received the wrong item,” or “I need to return an item.”
Here’s how chatbot and Conversational AI will handle these instances:
Chatbot:
- I’ve received a damaged item: We’re sorry! Please upload a photo, and we’ll arrange a replacement.
- I’ve received the wrong item: Apologies! We’ll set up an exchange for the correct item.
- I need to return an item: You can return it within 30 days. Here’s the return process.
Conversational AI
- I’ve received a damaged item: That’s not the experience we want you to have! I sincerely apologise for this. If you could upload a quick photo of the damage, I’ll get started on a solution right away.
- I’ve received the wrong item: Yikes! That’s completely our fault, and I truly apologise. Let’s fix this ASAP. Would you like to exchange it for the correct item or get a full refund?
- I need to return an item: No worries at all! We want you to be happy with your purchase. Let me check your order details to make sure it’s returnable.
A big difference between a regular chatbot and conversational AI is the level of empathy and personalisation. A regular chatbot gives brief, impersonal responses like “Please upload a photo” or “We’ll set up an exchange.” It’s efficient but lacks warmth.
In contrast, conversational AI offers a more friendly, empathetic tone, such as apologizing sincerely and asking how best to resolve the issue (e.g., offering a refund or exchange). It’s also more proactive, guiding users through the process and offering personalised solutions, which makes the experience feel more human and engaging.
Scenario 3: Discounts and promotions
In a scenario where a user asks about discounts and promotions, the chatbot would quickly provide brief, specific responses, such as a link to current offers or a discount code, without engaging in a detailed conversation. It doesn’t have the capability to analyse user preferences or provide personalized recommendations, which are key functions of a more advanced shopping assistant.
The chatbot simply offers the exact information it has been programmed to provide based on the user’s selected option, which limits its ability to assist in more complex ways.
- Current discounts: “Here are our latest offers: Link“
- First-time buyer discount: “Yes! Use code WELCOME10 for 10% off.”
- Loyalty program: “Here’s how it works: [link].”
In similar situations, Conversational AI provides a more engaging, contextual experience by adapting its responses based on the user’s specific needs. Unlike a simple rule-based chatbot, it can ask follow-up questions to clarify intent, offer personalised suggestions, and even guide users through applying discounts or signing up for loyalty programs. This level of interactivity enhances user satisfaction and encourages deeper engagement.
Conversational AI agent: “Welcome! How can I assist you today?”
User: “I have a question about discounts & promotions”
Conversational AI agent: “Great! I’d be happy to help with discounts and promotions. What kind of offer are you looking for?”
Case 1: “What discounts do you have right now?”
Conversational AI: “We have some awesome deals! Here’s a list of our latest promotions: [Webpage link]. Do you want me to check if a specific product is on sale?”
Case 2: “Do you have a first-time buyer discount?”
Conversational AI: “Yes! You can use code WELCOME10 for 10% off your first purchase. Would you like me to apply it to your cart?”
Case 3: “Tell me about your loyalty program.”
Conversational AI: “We love rewarding our customers! You can earn points on every purchase and redeem them for discounts. Here’s how it works: [Link]. Would you like to sign up?”
These are just a few example responses. Users can ask about discounts in many ways, with nuances, typos, or even incomplete phrases. A Conversational AI agent understands their intent and responds naturally, adapting to the conversation.
Rule-based chatbots can:
- Answer common questions.
- Provide basic FAQ information.
- Guide users through set conversation paths.
- Use menus for easy navigation.
Conversational AI can:
- Give personalised, context-aware responses.
- Keep conversations natural and flexible.
- Learn and improve from past chats.
- Adjust replies based on user details.
The future of Retail: Conversational AI leading the way
With fast developments in AI, businesses are rethinking customer support strategies. A recent McKinsey report reveals that over the next three years, 92% of companies intend to increase their AI investments. It has great potential to enhance efficiency and customer experience. While rule-based chatbots will continue to play a role, the shift toward Conversational AI is undeniable. Retailers are already seeing the impact.
Companies like Walmart are using conversational AI for retail to enhance customer experiences. For example, through Walmart Voice Order, customers can use voice commands to add items to their shopping carts via smart speakers and mobile devices. As AI continues to improve over time, its role in retail will only grow stronger.
Recap
Rule-based chatbots follow fixed scripts to respond to user input. Every possible conversation is mapped out in advance, so the bot only offers specific replies based on what the user says. It’s like a flowchart: “If the user says ‘X’, the bot replies ‘Y’.“
Conversational AI understands what users mean, even if they ask in different ways, and responds naturally. It adapts to the conversation instead of following a fixed script. While chatbots are good for handling basic inquiries, conversational AI brings the ability to engage customers more intelligently, offering personalised, context-aware conversations.
Meet Converso: Your Conversational AI Agent
Converso’s Conversational AI solution helps retailers like you to offer quick, friendly customer support that improves satisfaction and boosts sales. It provides personalised, context-aware responses that keep conversations natural and flexible while learning from past interactions and adjusting replies based on user details.
Our platform delivers the full benefits of conversational AI. Its fast, accurate, and easy to integrate with your existing systems. Get started today!