How to Make Chatbots Better through Knowledge Management

by | Knowledge Management

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According to a recent study, 40% of millennials claim to use chatbots on a daily basis. This astounding number highlights the importance of AI technology in the commercial world; chatbots are no longer a curiously or a fun new example of AI in the tech community—chatbots have become mainstream in a few short years. However, many bot can be inherently limited, hit or miss…depending on the question. How can we make chatbots better using knowledge management? 

In this post, we’ll explain why modern knowledge management is the secret sauce that separates great chatbots from mediocre ones, and how you can improve your organization’s current chat solution.

Why chatbot problems stem from how they are developed

Some chatbots aren’t too helpful because chatbots are only as smart as the rules, algorithms, and knowledge used in their creation; when humans program chatbots, answers depend on the decision-making AI engine and the knowledge source used.

During a typical chatbot development phase, software developers attempt to understand what questions the end user will routinely ask— whether that is an employee or customers. Using these questions as a guide, developers then create algorithms that sift through the typical query process to arrive at a final answer. Regardless of how thorough these developers are, it’s not possible to program chatbots for every possible scenario.

Make chatbots better by making them smarter How to Make Chatbots Better through Knowledge Management: image 2

Chatbots become smarter if the AI used in chatbot development can connect to a knowledge database; this connection provides a vital link to information—important information that allows chatbots to answer a greater variety of queries with improved accuracy and depth of response. In the next section, we’ll look at how chatbots query a database to return a response.

How chatbots source information

Chatbots function in a unique way. Their process begins with a set of rules that define reactions to specific prompts. A common chatbot reaction might be any of the following:

  • Play a greeting when a voice is detected
  • Open a menu when the keyword is given
  • Present other information based on the user’s request

When a query is entered into the system, the AI proceeds to search through its knowledge database for applicable solutions. Based on the words that were used to ask the question, the chatbot searches through its files to find related information.

The AI Survival Guide for Knowledge Managers Read this guide to future-proof knowledge management in the age of AI.

Chatbots can then narrow down the data to a handful of possible solutions which are presented to the user using algorithms as the decision-making engine.

Once potential solutions are presented, the user can either tell the chatbot to proceed with a chosen solution or go back and try again.

Quality knowledge is key to make chatbots better

Source material is an essential part of chatbot functions. Some AI’s are preloaded by engineers with the data used to discover solutions. Others are connected to a knowledge management database that allows the program to dynamically generate solutions from the source material. With AI learning capabilities, chatbots can quickly discover and catalog the best and most frequent solutions to repeat issues. Over time, these programs naturally become more efficient, enabling you to make chatbots better.

Poor source material leads to poor chatbot performance

A rich and comprehensive database is vital to a well-functioning chatbot because chatbots rely on source information to find answers to user questions. Chatbots fail when the information they receive is incomplete or of poor quality; with an incomplete or poor knowledge source, it’s unlikely chatbots will be able to find the right answers.

If the chatbots can’t surface an answer, they typically will present users with information to contact a support agent as a last step—one response no contact center manager wants to see.

Whenever users are forced to speak with a live agent, this wasted time and inconvenience only adds to their frustration. Poor chatbot performance ultimately can have a negative impact on CSRs and make it challenging for call center managers to retain employees.

On the other hand, when chatbots are fully integrated into knowledge management systems, they are able to pull from the organization’s full catalog of data. This means they can solve more problems without the need for agent interaction. Proper integration allows call center managers to use their AIs for more than just basic transactions like taking payments and providing balance inquiries.

Turn to knowledge to make your chatbots better

It’s a lot to expect a software engineer to understand all the complexities and nuances that exist within the contact center function of a business. Even the smartest subject matter experts won’t anticipate all the questions, answers, policies, and procedures a chatbot needs for every interaction; it’s simply unreasonable to expect engineers (or anyone else) to predict the future and provide all the information a chatbot will need to be effective.

Only with a knowledge base or knowledge management integration will you offer the best source of knowledge to be included in an AI’s internal database. If humans curate information they ‘think’ will suffice, organizations limit an AI’s capabilities and actually make it harder for customers to find what they need.

Rather than selecting common answers to simple questions (based on what a team of developers believes is useful), integrating the AI with a knowledge base will give the chatbot access to more comprehensive information for every scenario.

Once you connect your chatbot solution to a better knowledge source, the AI can then concentrate on learning for itself what your customers really need. With full access to a complete database, your AI can handle a greater variety of queries, identify more relevant information related to caller issues, and provide more satisfying resolutions without the need for agent involvement.

Improve your chatbot solution with Shelf

Ready to offer better chatbot answers for customers, and even help your agents during live interactions? Shelf is a knowledge management software platform that helps relieve the burden on customer support agents by surfacing great answers in any support environment.

To learn how Shelf can improve your chatbots and self service channels with AI-generated answers, request a free demonstration today.

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