Effective chatbots manages context, correctly responds to expected questions within the knowledge base, and knows when to engage the user at the right point in the conversation.
However, there may be instances where the bot does not correctly understand a request. Why does this happen? Let’s explore some possible reasons.
Missing Knowledge Base Entries
A chatbot fails to understand a request if it is not included in the knowledge base or if the question is phrased in an alternative way. When this happens, the bot returns an “unrecognized request” message, which is logged as a “miss” (unrecognized message) within the Improve step.
Alternatively, if the bot is uncertain about the correct response, it provides disambiguation options. This means it presents buttons with possible interpretations, allowing the user to select the most relevant one. If one of the options aligns with the request’s domain, the conversation continues smoothly.
Bot Conflict
Sometimes, a chatbot may fail to correctly respond to a question that is included in the knowledge base. This can happen if the same response is assigned to multiple different requests, causing the bot to lose confidence in selecting the correct answer, leading to a conflict.
To prevent this issue, the Crafter.ai platform manages conflicts by flagging potentially overlapping variations of a given question. However, to avoid conflicts altogether, it is always best to ensure that each Q&A pair has a distinct and specific response.
Questions Requiring an Additional Flow
A chatbot’s behavior depends on the conversational flow it is designed to handle. A simple Q&A automation bot can answer predefined questions but will not be able to perform actions requiring additional capabilities, such as collecting user data for lead generation or transferring the conversation to a human agent via handover.
To enable the bot to make proactive suggestions and ask follow-up questions, it is necessary to define the appropriate conversational flow.
Why Is the Chatbot Offline?
After launching a training session to teach the bot new information or making changes to its settings or chatroom design, the Crafter.ai platform requires an update.
This update process takes a few minutes, during which the bot will be temporarily unavailable to users attempting to interact with it. For this reason, it is advisable to schedule updates during low-traffic periods on the channel where the bot is hosted.
AI Hallucinations
AI hallucinations occur when a chatbot generates responses that seem plausible but have no real basis in the data it was trained on. These errors can compromise the system’s reliability and spread misinformation.
Strategies to Prevent AI Hallucinations and make Effective chatbots
The Crafter.ai platform reduces the risk of hallucinations through the integration of Retrieval-Augmented Generation (RAG) technology. This approach combines the ability to retrieve up-to-date information from reliable sources with natural language generation. By leveraging this method, along with well-designed conversational flows, the chatbot can provide relevant and contextually accurate responses, improving its overall reliability.
Additionally, developing effective system prompts is crucial to ensuring high-quality chatbot interactions. A well-structured and clear prompt guides the AI toward more precise and relevant responses, enhancing the user experience.