How many times have you used chatbots and conversational AI interchangeably? Let me guess; you’re probably thinking, were they any different?
I wouldn’t really blame you. On the surface, these two terminologies appear similar. Their core value is to enhance customer experience through automated conversations. However, their differences lie in how they achieve their goal.
Let’s understand both these concepts more clearly, shall we?
What are chatbots?
These days businesses are using the word chatbots for describing all type of their automated customer interaction. In the simplest of terms, chatbots are automated conversational tools. They have a predetermined or a rule-based conversational flow where the user picks options, and then chatbots take the conversation further based on their inputs. Each answer to a question is automated in advance to lead to the next question.
The wide use of chatbots is attributed to its DIY framework. Chatbots are thriving, and the chatbot market is expected to grow from $2.99 billion in 2020 to $9.4 billion in 2024.
Building a chatbot doesn’t require any technical expertise and can be constructed quickly on bot builders, and they can also be deployed independently.
An example of a rule-based conversational flow is given above. Let’s consider an example where a realtor wants to schedule a site visit. The bot will first send an automated greeting message from the company and then ask if the user wants to make a site visit. Since a bot builder has a calendar integration, a user can immediately pick a date and confirm the appointment. Furthermore, rule-based bots can generate qualified leads by asking for their names, phone numbers, and email addresses. If in case customer queries are complex in nature, a bot can always suggest a human handover where the query is handed over to a company representative.
Chatbots have created a space for them in the marketplace for assisting with rudimentary questions. But at their core, are they truly artificial intelligence?
The answer is no. A prime characteristic of AI is self-learning. A rule-based chatbot doesn’t fall out from their navigated path, and they will only answer what’s asked of them. They do not learn from their previous conversations, and their functions are limited within their set parameters- but they fulfill their purpose of aiding with the basics. 74% of the consumers feel they prefer chatbots to answer simple questions, and 64% think that chatbots’ most significant benefit is quick replies.
Taking a step forward with Conversational AI
While chatbots aim to provide enhanced customer service with a simple rule-based conversational flow, conversational AI’s approach is more sophisticated with its natural language processing and machine learning capabilities. Conversational AI is not just about rule-based interactions; they’re more advanced and nuanced with their conversations.
Conversational AI can offer a more dynamic experience in bot-human interaction through a dialog flow system.
Natural language Processing
With the introduction of Natural Language Processing (NLP), we achieved a new milestone in human-computer interaction. The computer’s ability to decipher and understand the human language and create value may seem futuristic, but it’s already here and is, in fact, widely used. NLP algorithm software majorly depends on Machine learning to derive meaning from languages. NLP has four main components:
The users provide input through a website or a mobile application, and the input can be over voice or text.
For a text-based input, Conversational AI will decipher the intention through Natural Language Understanding (NLU). NLU is a sub-branch of NLP which involves transforming & analyzing human language into machine-readable text. For a voice-based interpretation, Conversational AI will use a combination of NLU and Automatic Speech Recognition.
This is when the conversational AI solution app generates meaningful dialog in natural language using Natural Language Generation (NLG).
Finally, over time, conversational AI algorithms will pick up on patterns and learn without being programmed to do so. They become more accurate with their responses based on their previous conversations.
Today, some of the top NLP engines are Dialog Flow by Google, Watson by IBM, Amazon Lex, and Wit.ai by Facebook. A text-based conversational AI using Dialogflow is given below.
While chatbots’ prime use is to cater to simple queries, conversational AI is used for more complex functions. For example, you can book flights, make reservations, payments, get product recommendations, and get balance information of your credit cards using text and voice conversational AI bots.
Chatbots vs. Conversational AI
What is best for you?
Is conversational AI more advanced than chatbots? Yes! 100%!
Does that mean it’s the best choice for your business? No, not always.
Ultimately, it’s your business type that decides what the best bet for you is.
Companies are investing in conversational AI because of their ability to have highly personalized, fluid conversations with customers. Conversational AI mimics human-to-human interaction to the level that it’s difficult to tell whether the user is talking to a human or an AI. But first, think about it. Does your business really need that level of personalization? Can you achieve all your objectives with chatbots instead?
Chatbots can also personalize conversations to an extent. They can talk to the user with their name and have a personality too. For a small business loaded with repetitive queries, chatbots are very useful for filtering out leads and providing relevant information to the users. You don’t need conversational AI to qualify leads; you can simply develop a questionnaire flow on a chatbot without coding. For example, suppose if a property manager needs to screen rental prospects. In that case, it can build a chatbot that asks questions like the prospect’s credit score, number of bedrooms, roommate preference, lifestyle choices, location preferences, etc.
However, if your business involves a more personalized conversation style, you have to integrate conversational AI into your operations. Conversational AI can aid with a myriad of eCommerce activities. Try asking a conversational AI bot, “Where’s the nearest fast food joint?” or “Which hotels are available in Miami on 20th May 2021?” Conversational AI can provide answers to all these open-ended questions using NLP that a simple bot cannot answer.
Having said that, you don’t need to choose either of the two. You can adopt both conversational AI and a chatbot, considering that both offer their set of advantages. Depending on your budget, team acceptance of new technologies, and your level of operations, figure out what would work best for you. Your ultimate goal is to have engaging conversations with your customer. You get to decide how you want to achieve it.
How can WotNot help?
Be it conversational AI or chatbot, WotNot provides all sorts of solutions for your business. You can integrate Dialogflow in your bot to build conversational AI bots and also build rule-based chatbots without coding. Get started with WotNot and enhance your customer engagement online!