How to Create a Great Chatbot Conversation Database

Chatbots are all the rage in marketing, sales, and customer support, and it’s easy to see why. You kill multiple birds with one stone, reaching your audience, increasing conversions, and improving customer experience with a single chatbot.

But every chatbot needs a conversation database to pull answers (and questions) from. While creating a chatbot conversation flow isn’t hard, we have a few tips for setting yourself up for success with your chatbot DB!

1. How Do Chatbots Work?

Generally, chatbots have some type of front end or user interface where users can type their questions or select options. They also have a back end with the logic determining which answers will be displayed to the users.

Here, it’s important to distinguish between rule-based and AI-based chatbots

What Are Rule-Based Chatbots?

Rule-based chatbots contain simple logic that allows them to only deal with a limited number of pre-defined questions and answers. This logic has rules that determine what answers will be displayed to a user based on the question.

Source: Thunderfoot

What Are AI-Based Chatbots?

In contrast, AI-based chatbots use artificial intelligence and technologies like machine learning and natural language processing to understand open-ended questions. 

And, because of the AI technology, AI-based chatbots continue to improve as they interact with more users. So, over time, your chatbot will be able to answer more questions more accurately without you pre-programming those answers in the database.

No matter what chatbot you use, you’ll need to store the data it will use to provide the answers. 

How to Train Your Chatbot

You can train the chatbot manually, which means you’ll compile a database of questions and their answers. 

So, for example, a rule-based chatbot can use the visitor’s query to retrieve the response from the database.

You can also train the chatbot automatically. In this case, you’ll use machine learning algorithms to train the chatbot on your documents.

For example, an AI-based chatbot can train itself on the questions and answers in historical user conversations and provide accurate, contextual answers based on the user’s query. 

2. How to Create a Great Chatbot Conversation Database

You can skip this section if you’ll be feeding your AI-based chatbot a steady stream of conversations and proprietary docs. But if you’re not into AI and use rule-based chatbots, this section is for you.

After all, your chatbot will only be as good as your chatbot conversation database.

Make Sure Your Chatbot Has a Unique Name and Personality

Remember, the goal of a chatbot is to answer questions and provide information while maintaining the impression that the user is speaking to a human, not a machine. 

The first step in getting your chatbot to sound human is to give it a unique name and personality. 

When choosing a name, you should use wording and phrases that reflect your brand’s identity. The personality you choose depends on your brand and your target audience. This seems simple, but it’ll determine how your chatbot communicates with your customers. 

So, you should decide if you want the chatbot to be, for example, more professional, formal, or more informal and friendly. When you’ve outlined your voice, you should pre-program the answers to suit it.

Typically, we find that friendly chatbots work best, but your mileage may vary.

Make Your Chatbot Simple to Talk To

When customers interact with your chatbot, they want help or have questions. If you use chatbots for customer service, they might also be distressed. The last thing you want to do is send them on a spiral that ends with frustrated tweets. 

That’s why you should ensure that your chatbot is simple to talk to, straightforward, and easy to understand. 

You should also ensure that you create a natural conversation flow. This will make your chatbot sound more human and help in cases where it has to triage distressed customers.  

Create a natural conversation flow by using simple language and a clear tone. Allow your visitors to ask and get answers to common questions. Once you can provide assistance quickly with useful answers, you’ll significantly improve your chatbot experience.

(In contrast, you don’t want your chatbot to be a word-for-word replica of your knowledge base.)

Develop Specific Expertise For Your Chatbot

You shouldn’t create a chatbot to answer all the questions your customers might have. That’s what your knowledge base is here for! 

So, to make your chatbot as effective as possible, you should give it specific expertise. As such, you should focus every chatbot on a particular area of your business and give it only one or two goals. 

For example, you might use one chatbot that answers product-related questions, one that provides support, and another that can provide sales or account-related information. 

One of the main benefits of this approach is that it helps you solve your customers’ issues faster. When it comes to sales, this helps you connect with the prospect quicker and increase the number of chatbot conversions or demo bookings. 

Source: Business Insider

Use Your Chatbot to Triage for Humans

You can’t always anticipate the questions your customers might have. Sometimes, they’ll be too complex for a chatbot to help. That’s why you want clear triage rules; what goes to the human agents’ priority queue, and what’s marked as resolved?

When you outline your triage rules, include them in your chatbot conversation database responses. 

For example, the chatbot can tell the customer that a support agent will be in contact by phone or email. This is a practical approach to reducing customer frustration while maintaining customer satisfaction. 

(Bonus points if you give them a rough response time!)

Making it Easier to Create a Great Chatbot Database

In most cases, when you create a chatbot conversation database according to the best practices, you’ll need to use a relational or non-relational database. 

The problem is that this injects some complexity into the process. It can get pretty tricky if you don’t have the time or expertise to work with these databases. 

Fortunately, there is a simpler solution. You can use, which turns your (chatbot conversation) spreadsheets into REST APIs. Simply add the answers to your chatbot’s conversation database and plug your API into your chatbot software.

And as another benefit, once you’ve populated your spreadsheet with questions and answers, you can have your API ready in as little as 30 seconds! 

Learn more about how B4BCompany provides excellent chatbot experiences to their clients with a bit of help from 

Then, sign up for your free account and chat away!

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