Chatbot vs Live Chat Explained: Which Is Better in 2024?

Digital channels including the web, mobile, messaging, SMS, email, and voice assistants can all be used for conversations, whether they be verbal or text-based. Live chat allows you to have a live conversation with a real person, meaning customers receive highly personalized service. You can get to know them on a personal level and understand their unique needs. Additionally, some live chat solutions have a customer info panel with their browsing and order history. This way, you can provide them with the best possible assistance and get much more out of customer interactions. You can rely on your customer service reps and use live chat—because human support agents understand users best.

There will be times when a customer needs more than what a chatbot can offer. It’s a good idea to add a “Talk to an agent” button as one of the quick decision choices. A bot can also send a mobile notification to your customer support team if there is a customer inquiry waiting for your reply.

Human agents can understand the mood and tone of the customer and are skilled in delivering the right support to the customers. Establishing a customer connection increases customer satisfaction and builds brand loyalty. Though chatbot technology is now powered with Artificial Intelligence (AI) and Machine Learning (ML), chatbots aren’t quite there yet to resolve complex customer queries.

For ecommerce brands that deliver physical products, conversational support is a no-brainer. Imagine your customers get shipping updates via SMS and can just respond to the message if the package isn’t delivered correctly to get immediate help. No need to open up a laptop and log into a support portal or compose an email. Look through your reporting dashboards to see the tickets that are taking up the most time on your support team, and prioritize those requests for automation with Rules, where appropriate.

Everything from integrated apps inside of websites to smart speakers to call centers can use this type of technology for better interactions. With conversational AI technology, you get way more versatility in responding to all kinds of customer complaints, inquiries, calls, and marketing efforts. When a conversational AI is properly designed, it uses a rich blend of UI/UX, interaction design, psychology, copywriting, and much more.

Instead of spending countless hours dealing with returns or product questions, you can use this highly valuable resource to build new relationships or expand point of sale (POS) purchases. There are benefits and disadvantages to both chatbots and conversational AI tools. They have to follow guidelines through a logical workflow to arrive at a response. This is like an automated phone menu you may come across when trying to pay your monthly electricity bills. It works, but it can be frustrating if you have a different inquiry outside the options available. Over time, you train chatbots to respond to a growing list of specific questions.

II. Key Differences Between Chatbot vs. Conversational AI

But there’s a third chat option that you should consider in addition to live chat and chatbot software. The two terms “chatbot” and “conversational AI” are frequently used interchangeably, but the entity to which each term refers is similar but not identical to the other entity. In this blog post, Raffle explains 5 differences between the chatbot and conversational AI. If this post has motivated you, you are probably thinking how can I speed up my deployment and get something up and running quickly? Another situation where you would want to use classical NLP chatbots is where you would like to have exact control of the output text and the lingo of the bot. The LLM-based AI chatbots generate their own text, and that makes it difficult to have exact control over the vocabulary and lingo of the bot.

Navigating the chatbot realm, one must distinguish between the classic traditional chatbots and their more advanced AI-driven counterparts to make informed decisions for business integration. Chatbots powered by AI can connect to external platforms like CRMs or e-commerce systems to offer personalized information by accessing user-specific data points. Rule-based chatbots have paved the way for creative customer engagement across diverse industries.

With a chatbot app, offering immediate response times to customer queries is a much more attainable goal. Best of all, these immediate response times are a 24/7 offering for customers, whereas live chat agents may not always be on the clock. They can be used to discover products, solutions or services, make connections to the right people, automate business processes, and standardise an optimized experience to improve the customer experience. Conversational AI, on the other hand, refers to technologies capable of recognizing and responding to speech and text inputs in real time. These technologies can mimic human interactions and are often used in customer service, making interactions more human-like by understanding user intent and human language. Any advantage of a chatbot can be a disadvantage if the wrong platform, programming, or data are used.

They can also provide irrelevant or inaccurate information in this scenario, which can lead to users leaving an interaction feeling frustrated. This is because conversational AI offers many benefits that regular chatbots simply cannot provide. Conversational AI is capable of handling a wider variety of requests with more accuracy, and so can help to reduce wait times significantly more than basic chatbots.

If an IVR answers your call and you press a button that doesn’t have an assigned option, it doesn’t know what to do except to read the menu options again to you. When a visitor asks something more complex for which a rule hasn’t yet been written, a rule-based chatbot might ask for the visitor’s contact details for follow-up. Sometimes, they might pass them through to a live agent to continue the conversation. After the page has loaded, a pop-up appears with space for the visitor to ask a question.

For example, if your daily conversation volume is low, you can use a mobile live chat app to receive notifications about new incoming messages and answer them on the go. You don’t have to compromise on your customer service quality just because you’re not available on your computer all day long. This is valuable for companies that want to offer excellent customer service, but can’t afford to have someone manning the live chat around the clock. Chatbots can take care of the majority of customer queries and requests with no human involvement.

Customer experience automation (CXA): Definition + examples

Some chatbots use conversational AI to provide a more natural conversational experience for their users, but not all do. AI Chatbots are created to serve a particular business, automating functions and handling customer inquiries specific to that business. ChatGPT-based chatbots are engineered for broad conversations, encompassing a vast array of subjects, not customized for a particular business. These AI-powered chatbots differ from traditional ones, as they generate context-aware and precise responses based on user input rather than relying on predefined answers. Rule-based chatbots rely on keywords and language identifiers to elicit particular responses from the user – however, these do not depend upon cognitive computing technologies. Automated bots serve as a modern-day equivalent to automated phone menus, providing customers with the answers they seek by navigating through an array of options.

Conversational AI is a broader concept encompassing chatbots but also includes other technologies and applications involving natural language processing and human-machine interaction. With a chatbot solution like Zendesk, companies can deploy bots that sound like real people, all with a few clicks. This enables businesses to increase their support capacity overnight and begin offering 24/7 support without hiring new agents. Businesses will always look for the latest technologies to help reduce their operating costs and provide a better customer experience.

You can also use this data to further fine-tune your chatbot by changing its messages or adding new intents. This bot enables omnichannel customer service with a variety of integrations and tools. The system welcomes store visitors, answers FAQ questions, provides support to customers, and recommends products for users. Companies use this software to streamline workflows and increase the efficiency of teams. This solution is becoming more and more sophisticated which means that, in the future, AI will be able to fully take over customer service conversations. Implementing AI technology in call centers or customer support departments can be very beneficial.

By hooking the artificial intelligence chatbot to your business intelligence platform, you can gather valuable intelligence that can help you manage important decisions for your products and services. This person would talk to you and address your issues, concerns, or queries through a chat conversation. These are chat tools pushed to a website, but there is nothing automated in those so they are not chatbots. There have been recent technological changes to processing, speech recognition, natural voice, smart speakers and internet bandwidth that have made them more accurate and enjoyable solutions. Discover how our Artificial Intelligence Development & Consulting Services can revolutionize your business.

Users can interact with a chatbot, which will interpret the information it is given and attempt to give a relevant response. A travel agency can employ a ChatGPT-powered chatbot to aid customers in planning vacations. This chatbot will gather their travel preferences, budget, and desired destinations, post that it can create a unique itinerary for each client.

In this article, you’ll learn about the principles that differentiate chatbots vs conversational AI, explore their main differences, and gain insights into how artificial intelligence is influencing customer service. In contrast, chatbots rely on written scripts and machine learning algorithms. They can respond accurately to common customer inquiries, but they may struggle with more complex or nuanced inquiries. You can personalize your chatbot customer service interactions using proactive Greetings. They can be sent to customers based on different conditions, like the time the customer spent on a website, their browsing history, or the referring address.

AI-powered chatbots

A chatbot, however, can answer questions 24 hours a day, seven days a week. It can provide a new first line of support, supplement support during peak periods, or offload tedious repetitive questions so human agents can focus on more complex issues. Chatbots can help reduce the number of users requiring human assistance, helping businesses more efficient scale up staff to meet increased demand or off-hours requests. Unlike chatbots, ChatGPT can enhance customer experience by providing personalized and tailored responses for each user’s unique situation. Additionally, it can automate a wider range of inquiries, freeing up human agents for more complex tasks. Chatbots are computer programs that simulate human conversation through messaging interfaces like websites or mobile apps.

ChatGPT is great example of Generative AI technology, which generates human-like text based on the input it gets. But it does not represent all AI (think facial recognition or self-driving cars). It can be very confusing, making it hard to judge what’s best for your business. Before we jump to the difference between ChatGPT and Chatbots, we want to bust some myths around AI and ChatGPT so that you are well informed. The best part is that it uses the power of Generative AI to ensure that the conversations flow smoothly and are handled intelligently, all without the need for any training.

If the chatbot determines the customer’s question or issue is too complex to resolve, the customer is then connected to a support agent via live chat. One of the biggest advantages of chatbot solutions is the fact that they allow for immediate responses to customer inquiries. Live chat solutions can also help companies reduce their wait times, though not to the same degree.

For example, your team can come up with one main solution (create a new discount code because the previous one is buggy) and easily resolve the entire group of tickets in a single pass. Conversational AI extends its capabilities to data collection, retail, healthcare, IoT devices, finance, banking, sales, marketing, and real estate. In healthcare, it can diagnose health conditions, schedule appointments, and provide therapy sessions online. Learn about how the COVID-19 pandemic rocketed the adoption of virtual agent technology (VAT) into hyperdrive. Whatever the case or project, here are five best practices and tips for selecting a chatbot platform.

Instead of repeatedly checking their email or manually tracking the package, a helpful chatbot comes to their aid. It effortlessly provides real-time updates on their order, including tracking information and estimated delivery times, keeping them informed every step of the way. Now, let’s begin by setting the stage with a few definitions, and then we’ll dive into the fascinating world of chatbots and conversational AI. Together, we’ll explore the similarities and differences that make each of them unique in their own way. On a side note, some conversational AI enable both text and voice-based interactions within the same interface. For example, ChatGPT is rolling out a new, more intuitive type of interface.

Choosing Between Chatbot and Chatbox

Once you click on the button or the icon there, one of several things may happen. In some scenarios, you will be presented with a series of options like a decision tree, such as product names, quantity, size, etc. Businesses will gain valuable insights from interactions, enabling them to enhance future customer engagements and drive satisfaction and loyalty. On the other hand, Generative AI requires chatbot vs chatbot substantial upfront costs and resources during the initial development. But it offers better scalability as it improves over time without much increase in cost or effort, which make it more adaptable and relevant in the long term. Let’s take a deep dive (backed with data-driven insights) into how Chatbots and ChatGPT/Generative AI are different, and help you make an informed decision.

Once polished, the bot can help customers whenever the number of your customer service reps is insufficient to provide timely and effective customer support via live chat. Not to mention the businesses that can’t offer 24/7 live chat support or struggle with optimizing their response time are more likely to achieve unsatisfactory customer satisfaction rates. Live chat lets you connect with customers in real time and offer a personalized and empathetic service. The problem arises when your support team works only during business hours, and customers are left waiting for a response outside those hours. Yes, you can use both live chat and chatbots to provide a comprehensive customer support experience, leveraging the strengths of each to cater to different customer needs and preferences.

Since September 2017, this has also been as part of a pilot program on WhatsApp. Airlines KLM and Aeroméxico both announced their participation in the testing;[32][33][34][35] both airlines had previously launched customer services on the Facebook Messenger platform. Developers can import the ChatBot module into their Python scripts or notebooks and select the appropriate function based on the desired https://chat.openai.com/ data source. Each function comes with specific parameters to customize the chatbot’s behavior according to specific needs[1]. Lyzr is a company that focuses on simplifying and streamlining the integration of generative AI into enterprise systems. They offer a full-stack, low-code SDK platform that allows enterprises to access comprehensive SaaS functionalities through a single, easy-to-integrate SDK.

As the foundation of NLP, Machine Learning is what helps the bot to better understand customers. Simply put, the bot assesses what went right or wrong in past conversations and can use that knowledge to improve its future interactions. This causes a lot of confusion because both terms are often used interchangeably — and they shouldn’t be! In the following, we explain the two terms, and why it’s important for companies to understand the difference. Group them by their complexity or use a chatbot like Lyro that can do this automatically for you. It may turn out that some of your regular inquiries don’t need an answer from an agent.

Conversational AI systems can also learn and improve over time, enabling them to handle a wider range of queries and provide more engaging and tailored interactions. Chatbots are software applications that are designed to simulate human-like conversations with users through text. They use natural language processing to understand an incoming query and respond accordingly.

Examples of rule-based chatbots: How brands harness the power of rule-based chatbots

While the rules-based chatbot’s conversational flow only supports predefined questions and answer options, AI chatbots can understand user’s questions, no matter how they’re phrased. When the AI-powered chatbot is unsure of what a person is asking and finds more than one action that could fulfill a request, it can ask clarifying questions. Further, it can show a list of possible actions from which the user can select the option that aligns with their needs. The biggest difference between the two types of chatbots is the technology they use to respond to customer requests, which affects the complexity of the tasks they can accomplish.

And forcing customers to dig or compose an email just to know the status of their order is a high-effort experience. The competition to provide customer satisfaction in ecommerce today is fierce. Now, shoppers demand free shipping on every order and expect lightning-fast order processing and fulfillment. What once were “nice to have” differentiators for small businesses have become necessary for growth and success.

A rule-based bot may only answer one of those questions and the customer will have to repeat themselves again. This might irritate the customer, as they didn’t get the info they were looking for, the first time. There is only so much information a rule-based bot can provide to the customer. If they receive a request that is not previously fed into their systems, they will be unable to provide the right answer which can be a major cause of dissatisfaction among customers.

With a user friendly, no-code/low-code platform you can build AI chatbots faster. Operating on basic keyword detection, these kinds of chatbots are relatively easy to train and work well when asked pre-defined questions. However, like the rigid, menu-based chatbots, these chatbots fall short when faced with complex queries. These chatbots struggle to answer questions that haven’t been predicted by the conversation designer, as their output is dependent on the pre-written content programmed by the chatbot’s developers. Despite the technical superiority of conversational AI chatbots, rule-based chatbots still have their uses. If yours is an uncomplicated business with relatively simple products, services and internal processes, a rule-based chatbot will be able to handle nearly all website, phone-based and employee queries.

Many order tracking apps integrate with different ecommerce systems like Shopify, BigCommerce, Magento, 3DCart, or WooCommerce. So, you’ll need to make sure that the tool you choose integrates well with the ecommerce system you use. A custom-built tracking page may require more data entry than necessary with other solutions.

The support agents can have insights into the history of part conversation and have a meaningful conversation with customers. Chatbot keeps track of customer behavior with the help of data collected from past conversations. The data is further used to analyze the taste and preferences of the customers and offer a personalized experience.

Free AI chatbot software

With its ability to generate and convert leads effectively, businesses can expand their customer base and boost revenue. Gaining a clear understanding of these differences is essential in finding the optimal solution for your specific requirements. Providing accurate information helps you build trust with customers and ensure a positive experience with the business. Personalization lets you provide a more customized and relevant experience that resonates with the customer personally. When customers feel valued and understood, they’re more likely to develop loyalty toward your brand and recommend it to friends and family. This way, you can deliver consistent and efficient customer service across many touchpoints.

• Chatbot interfaces with generative AI can recognize, summarize, translate, predict and create content in response to a user’s query without the need for human interaction.
• This results in a frustrating user experience and often leads the chatbot to transfer the user to a live support agent.
• For that reason, we recommend setting up your contact page and information so that text and other live channels are your first line of communication — well, after self-service support.
• The ability to better understand sentiment and context enables it to provide more relevant, accurate information to customers.
• Modern AI chatbots now use natural language understanding (NLU) to discern the meaning of open-ended user input, overcoming anything from typos to translation issues.
• In this blog, we’ll touch on different types of chatbots with various degrees of technological sophistication and discuss which makes the most sense for your business.

The HR department of an enterprise organization might ask a developer to find a chatbot that can give employees integrated access to all of their self-service benefits. Software engineers might want to integrate an AI chatbot directly into their complex product. The terms chatbot, AI chatbot and virtual agent are often used interchangeably, which can cause confusion. While the technologies these terms refer to are closely related, subtle distinctions yield important differences in their respective capabilities. By combining the two technologies, businesses can develop AI Agents that strategically avoid the risks of pure Generative AI (like giving irrelevant or harmful responses).

The natural language processing functionalities of artificial intelligence engines allow them to understand human emotions and intents better, giving them the ability to hold more complex conversations. At their core, these systems are powered by natural language processing (NLP), which is the ability of a computer to understand human language. NLP is a field of AI that is growing rapidly, and chatbots and voice assistants are two of its most visible applications.

Response rate is always an issue with email surveys, and other channels see higher response rates. Using a multichannel approach will supply you with more responses and help you make more data-driven decisions with the results. Beyond prioritizing tickets, it’s also helpful to categorize them if they share similarities.

Consider how conversational AI technology could help your business—and don’t get stuck behind the curve. Whether you use rule-based chatbots or some type of conversational AI, automated messaging technology goes a long way in helping brands offer quick customer support. Domino’s Pizza, Bank of America, and a number of other major companies are leading the way in using this tech to resolve customer requests efficiently and effectively.

They work best when paired with menu-based systems, enabling them to direct users to specific, predetermined responses. Embrace the future of customer interaction with chatbot technology, and revolutionize the way your business engages with its audience. Conventional chatbots depend on preset responses and identify keywords to generate appropriate answers. ChatGPT-driven chatbots employ natural language processing (NLP) to comprehend the context and subtle aspects of a user’s input.

You could even prompt your chatbot to ask the visitor about preferred warranties and after-care packages. Ultimately, the AI takes them through to the shopping cart to complete the purchase. One of those could be helping your website customers to find what they want. A visitor might ask a question like “Do you have wireless headphones in stock?

One of the biggest drawbacks of conversational AI is its limitation to text-only input and output. Conversational AI is a technology that enables machines to understand, interpret, and respond to natural language in a way that mimics human conversation. When most people talk about chatbots, they’re referring to rules-based chatbots.

Lyzr’s SDKs encapsulate the full spectrum of a software product’s capabilities, making it easier for enterprises to adopt and use generative AI applications. 3 min read – This ground-breaking technology is revolutionizing software development and offering tangible benefits for businesses and enterprises. Upload your product catalog and detailed product descriptions into your chatbot. Tell it that its mission is to provide customers with the best possible advice on which products they should buy. There are, in fact, many different types of bots, such as malware bots or construction robots that help workers with dangerous tasks — and then there are also chatbots.

You can foun additiona information about ai customer service and artificial intelligence and NLP. Last but not least, consider which solution will be easier for your team to implement and use. But if customers receive incorrect information or advice, it can lead to frustration and dissatisfaction. That can result in negative reviews, lost revenue, and damage to the company’s reputation. You can edit it the way you want and set your bot in motion within minutes without coding. ChatGPT is a large language model trained on the third generation of GPT (Generative Pre-trained Transformer) architecture, with hundreds of billions of words.

If you’re in an industry that offers pickup services (whether curbside pickup, custom goods like eyeglasses, or anything else), a text message is a great way to let someone know their order is ready for pickup. SMS reaches customers when they’re on the go in a way that email frequently doesn’t. This tactic can buy your team time to finish up a previous interaction or send an email, yet it shows you’re on top of the interaction and will be back soon. Text messages are an effective method for collecting feedback from existing customers, too.

When integrated into a customer relationship management (CRM), such chatbots can do even more. Once a customer has logged in, chatbots can be trained to fetch basic information, like whether payment on an order has been taken and when it was dispatched. If 90% of your target audience is using Messenger to communicate with businesses, then you should try to make the most out of this channel.

Upon transfer, the live support agent can get the chatbot conversation history and be able to start the call informed. As we’ve seen, the technology that powers rule-based chatbots and AI chatbots is very different but they still share much in common. Now it has in-depth knowledge of each of your products, your conversational AI agents can come into their own. Because your chatbot knows the visitor wants to edit videos, it anticipates the visitor will need a minimum level of screen quality, processing power and graphics capabilities. The origins of rule-based chatbots go back to the 1960s with the invention of the computer program ELIZA at the Massachusetts Institute of Technology’s Artificial Intelligence Laboratory. So, the technology that powers these chatbots is now more than 60 years old.

These tools optimize the response time and increase the instances of a positive customer experience. The problem with relying solely on chatbots to reduce customer wait times is the fact that even the best and most intelligent Chat GPT chatbots are often unable to resolve complex issues. Chatbots are excellent at pulling information from internal databases to answer common questions, such as providing the status of a customer’s order or editing it.

On the other hand, Copilot is proficient in a wide range of languages and can handle data in a variety of forms. There has been a lot of hype around Microsoft Copilot and its potential to transform business operations. – Many entrepreneurs and business executives, who already invested in AI chatbots, have asked me this question lately. In this blog post, I’ll try to break down how Microsoft Copilot stacks up against the existing AI chatbots  technology. Before we talk about the difference between Copilot and AI chatbots, let me briefly explain Microsoft Copilot. After recognizing the effort businesses put into enriching user experiences, customers feel valued and respected, leaving them happy and loyal to the brand.

With chatbots taking care of all your routine queries, live chat agents can focus completely on resolving complex issues and bringing down average resolution time. Having a chatbot integrated with your live chat software will enable you to offer support beyond your business hours. If any complex issue arises, the chatbots can collect the information and pass it on to your agents during your next business hour to resolve the issue. On the other hand, live chat boosts agent productivity compared to other traditional support channels. It offers all your customer data and your integrations on a single screen without having agents switch between tabs to find the right information.

• This module enhances the extraction of valuable insights from PDF files and other document types, providing functionalities for question-answering and document processing.
• ChatGPT is a large language model trained on the third generation of GPT (Generative Pre-trained Transformer) architecture, with hundreds of billions of words.
• That automation can improve a business’s customer experience by delivering immediate responses to common questions.
• Follow the steps in the registration tour to set up your website chat widget or connect social media accounts.
• With ChatGPT and GPT-4 making recent headlines, conversational AI has gained popularity across industries due to the wide range of use cases it can help with.

Although they’re similar concepts, chatbots and conversational AI differ in some key ways. We’re going to take a look at the basics of chatbots and conversational AI, what makes them different, and how each can be deployed to help businesses. From traditional rule-based chatbots to AI chatbots and cutting-edge ChatGPT-trained custom AI chatbots, each type offers its unique advantages and drawbacks, depending on the intended application. Sephora, the prominent beauty retailer, developed its Facebook Messenger chatbot to provide customized beauty product suggestions.

Your customers may ask a lot of unique questions about the product descriptions or recommendations for their specific needs. They would prefer to chat with a human representative who knows the products inside and out. Both solutions can offer a great user experience when approached the right way. Unfortunately, most rule-based chatbots will fall into a single, typically text-based interface. With so much use of such tech around a broad range of industries, it can be a little confusing whenever competing terms like chatbot vs. conversational AI (artificial intelligence) come up.