A chatbot is an automated system or program designed to simulate human conversations through text or voice interaction to provide customer support. When a customer reaches out to a business through a communication channel, the chatbot answers their questions and queries and provides all the necessary information. Different types of chatbots are developed for tailored needs and functions, such as rule-based chatbots, keyword-based chatbots, menu-based chatbots, and knowledge base chatbots, the most versatile ones providing a wide range of solutions.

A chatbot with  knowledge base is designed to excel in different areas, such as intelligent interactions, customized responses, and continuous learning. Let's explore what a knowledge base chatbot is and how it is designed to foster business communications.

What Is a Knowledge Base Chatbot?

A knowledge base chatbot is a conversational technology designed to integrate two solutions, i.e., knowledge base and AI chatbot. Knowledge base means the database or the library that contains information about a company's products, services, and procedures. The latter interprets the queries, relates them with the available information, and generates an answer. It includes various types of data, such as:

• FAQs about services and products
• How-to-guides for completing tasks
• Troubleshooting tips
• Internal knowledge
• Knowledge base articles

What makes this chatbot stand out in customer services is its ability to generate natural responses, customize interactions, and handle complex workflows, e.g., pricing info, order status, or processing refunds.

How To Build a Knowledge Base Chatbot

Here is your step-by-step guide for building an effective AI chatbot with a knowledge base.

1. Pre-Design or Pilot Phase

Define Your Goals

Before building a knowledge base chatbot, create a road map with clear goals and objectives. Figure out with your team:

• Who will be using your chatbots? What are their needs, preferences, and pain points?
• Which specific feature does your chatbot need to improve user experiences?
• How will you measure the performance of your chatbot? Defining the key metrics, such as task completion, user engagement, and satisfaction rate, will help you quantify its impact.

Create a Knowledge Management Strategy

Knowledge management is the procedure of collecting, organizing, and sharing information that customers can easily access. Chatbots are self-preserving; they can analyze and grow their intelligence (and enhance their knowledge base) from conversations. A careful assessment of what knowledge should be shared with your chatbots for customers to access and what should be kept internally for agents will provide you with a solid knowledge management base.

2. Collect The Data

The next step is to collect relevant data for the chatbots. You can streamline the process by using spreadsheets. Start with gathering the questions or queries your customers ask most often, then gradually proceed to live chat transcripts, email templates, or technical information. You can divide this information into sub-categories such as:

• Product or service-related information
• Pricing plans/ installments
• FAQs
• Feedbacks
• Order tracking inquiries

Choose A Professional Platform

Choosing a professional platform like Aidbase with an expert team is crucial to powering your knowledge base chatbot. Consider the following factors before selecting a framework:

• Technical Expertise: Choose a team with the appropriate skills, experience, and a successful record of similar projects.
• Integration: Your chosen platform should be well-integrated with your existing systems.
• NLP: Select a platform that offers natural language processing capabilities for AI-powered chatbots.

3. Development, Training, and Launching Phase

Appropriate Programming

Developers will select a language from Python, Java, or specialized chatbot frameworks to create the core of the chatbot. The code or language selection depends entirely on a chatbot's sophistication and intended functionalities. Continuous maintenance and updates are essential to maintain a smooth workflow.

Integration With AI and NLP

The next step is the Integration of the knowledge base with AI. This is training a chatbot model to use relevant data for appropriate response generation. NLP (natural language processing) enables a knowledge base chatbot to understand the meaning behind user queries even if they are not correctly composed. This is how it happens:

• Tools like tokenization, part-of-speech, and keyword identification help the chatbot to analyze and process a query.
• It helps the chatbot extract specific details like a name, date, gender, or place from a question to understand the user's intent and give personalized and particular responses.

Note: To make a chatbot work more humanely, develop its tone, personality, and persona according to your brand's image. The level of professionalism and perfection you expect from your agents should be equally reflected in your chatbots.

Trial and Testing

Once the chatbot is developed into the launching phase, it's good to run some tests and trials. Consider functional testing on a limited scale with real customers to identify any possible errors or loopholes. This phase is essential and crucial for refining the chatbot's performance and ensuring a smooth user experience.

4. Post Launching Phase

Deploy and Integrate The Chatbot

Once the chatbot has gone through intensive trial and testing, consider the following deployments:

• Website: Include the chatbot on your website so visitors can utilize it.
• Mobile Apps: Integrate the chatbot to offer in-app assistance on your mobile apps
• Messaging Apps: For a massive client reach, your chatbot should be enabled on all modern messaging apps such as Facebook, Instagram, or WhatsApp.

After deployment, keep track of analytics and metrics such as user interactions, response timing, workflow, and chatbot performance. Use this data to improve the performance of your chatbot.

Collect Customer Feedback

Knowing the viewpoints and feedback of people who interact with your chatbots regularly is essential. Use AI chatbots' automatic feedback collection feature to see how your customers interact with them. Does it successfully resolve their pain points? Has it improved their shopping experience? The ratings and comments can give you much-needed information to elevate your business.

Develop Your Next AI-powered Chatbot With Aidbase

Think about having customer support for your business that never sleeps. While it may sound too good, Aidbase Ai has made it entirely possible. Aidbase is a leading AI automation platform providing customized AI chatbots that deliver exceptional customer support without manual training. With well-trained chatbots and live AI chat support, enjoy a 24/7 seamless customer service and elevate your business success.

A Step By Step Procedure of Creating FAQs Using Aidbase

Here's a step-by-step process of how you can create FAQs using Aibase.

Step#1: Log in to Aidbase or create an account using your Gmail.

Step#2: You'll land on the Homepage. Here, you'll see a Knowledge Base tab on the left side. From there, click on the FAQ.

Step#3: Click 'Create new FAQ' to write custom-based FAQs per your organizational needs or service requirements.

Step#4: Add your Question, answers, and a source link. You can also name the categories for your convenience.

These FAQs can resolve your customers' queries instantly, which can help them have a seamless experience.

Knowledge Base Chatbot FAQs

1. What are the advantages of using a knowledge base chatbot over others?

A knowledge base chatbot is designed to enhance user experience by providing natural responses, customized interaction, and handling various queries such as product information, order status, or refunds.

2. What is the average cost of developing a knowledge base or hybrid chatbot?

This may depend upon several factors, such as the complexity of the chatbot, the development process, and integration requirements. Outsourcing the whole procedure through an agency can cost you between 1000$ to $5,000.

3. What are the ethical and privacy concerns for using chatbots in customer services?

Here are some primary ethical and privacy considerations that should be addressed before using chatbots in customer services:

• Make it transparent to users that they are talking to a chatbot, not human agents.
• Chatbots should be designed to interact with users respectfully with empathy and avoid generating unfair or discriminatory responses based on algorithms.
• Data security measures should be robust to avoid user information breaches and misuse.

Conclusion

Proactive customer service is essential for a business that wants to build strong relationships and effective communication with its customers. Using AI support, such as a knowledge base chatbot in your customer services, helps you save time, enable multitasking, and create a positive business experience.