The market for chatbots is expanding and is expected to continue growing. Did you know that IBM Watson can help build intelligent and efficient AI-based chatbot solutions?
AI-powered chatbots provide a more human-like experience, can carry on a natural conversation, and continuously improve over time. Their popularity stems from the improvements they bring to customer experiences, their 24/7 availability, cost-effective customer support, enhanced operational efficiency, easy scalability, support for multiple channels, data collection and analysis capabilities, continuous learning, and task automation. These benefits make them valuable tools for businesses across various industries. The working of an AI-based chatbot is demonstrated in Figure 1. As shown, the chatbot evaluates the users’ requests, ascertains their intent, determines what they require, and then automatically generates and replies to them with the most relevant response.
Top industries using AI-based chatbots for their business
Various industries widely adopt AI-based chatbots to enhance customer engagement, improve operational efficiency, and provide personalised assistance. For example, chatbots are utilised in the travel industry for tasks like booking flights, hotels, or rental cars. They can also offer travel recommendations and information about destinations and answer frequently asked questions. Chatbots can assist in itinerary management and provide real-time updates about travel schedules. In the insurance industry, chatbots help customers file claims, obtain policy information, and answer questions about coverage. They can guide users through claims, collect relevant information, and offer instant assistance. Table 1 shows examples of how different industries are leveraging AI-based chatbots for their businesses.
Table 1: Popular AI-based chatbots used in industries
Company name | AI-based chatbots used for their business |
Bizbike |
Bizbike is Belgium’s biggest e-bike provider. It has implemented AI chatbots to efficiently and reliably respond to consumer enquiries. |
Starbucks |
Starbucks uses AI chatbots to place orders via voice and carry out payment transactions. It also uses them for digital marketing and retail purchase. |
Belfius | Belfius is a popular, trusted bank in Belgium that uses AI chatbots to manage insurance claims and respond to customer queries efficiently. |
iFood | iFood is a Brazil-based company that uses an AI chatbot to manage an online meal delivery system. |
European Commission | The European Commission uses an AI chatbot to manage traveller’s queries. |
Kotak Life Insurance | India’s Kotak Life Insurance has developed the Kaya virtual assistant as an AI-based chatbot system to manage user queries. |
Several AI-based chatbot tools are available in the market, each with its own features and capabilities (Table 2).
Criteria | WP-Chatbot | Microsoft Bot | IBM Watson Assistant | CSML | LivePerson |
Developed by | MobileMonkey | Microsoft | IBM | Clevy.io | LivePerson, Inc. |
AI technology used | NLP | NLP | NLP, ML | NLP, ML | NLP |
Key features | Facebook page branding, compatible with WordPress | Allows use of open source SDK | Provides a visual interface for designing chatbot flows, and supports multiple channels | Provides a ready-to-use chatbot templates library | Hyperlinks and custom pre-written statements |
Target application |
WordPress ecosystem | To build a conversational AI experience | To respond to user queries for commerce and support | To improve the customer experience for e-commerce platforms | To engage customers using messaging, voice, etc |
Pricing | 14-day free trial; and US$ 99/month | No free trial US$ 499/month |
US$ 140/instance | Free version available | Free trial available |
Using IBM Watson to develop a chatbot application
The steps we need to follow when using IBM Watson to deploy an AI-based chatbot solution are briefly listed below.
Step 1. Set up an IBM Cloud account: If you don’t already have an IBM Cloud account, sign up at https://cloud.ibm.com/registration.
Step 2. Create an IBM Watson Assistant service: Once you successfully log in at IBM Watson, create an assistant service using the catalogue menu bar. Now, generate assistant and dialogue skills. Give a name to your dialogue skill, for example, ‘student advisor’, as shown in Figure 2. An assistant is a chatbot that helps connect user conversation flow and search for an answer from the knowledge database.
Step 3. Design the conversation flow: Use the Watson Assistant tooling to design the conversation flow by creating nodes and defining the dialogue structure. Each node represents a step in the conversation, including user inputs and chatbot responses.
Step 4. Define intents and entities: Identify the intents (user goals or intentions) and entities (important pieces of information) that your chatbot should understand. Train Watson Assistant to recognise these intents and entities to improve the accuracy of understanding user inputs. You can construct an intent called ‘feedback’ that acts in response to user input, as shown in Figure 3.
Step 5. Add a custom greeting node: Click the ‘Add node’ button in the workspace editor to create a new node, as depicted in Figure 4. This node will represent the custom greeting.
Step 6. Save and test: Finally, save your changes and try the custom greeting node by interacting with the chatbot to ensure it triggers the greeting when the specified input is provided. A sample deployed application is shown in Figure 5.
Chatbots are gaining popularity in industries with their ability to enhance customer experiences, improve operational efficiency, reduce costs, and provide businesses with valuable insights for better decision-making. IBM Watson is a powerful platform that offers a range of AI capabilities, including natural language processing (NLP) and machine learning, which can be leveraged to build AI chatbots. Businesses can build robust and intelligent chatbot solutions by utilising IBM Watson’s AI capabilities.