FAQ Knowledge-Base Chatbot

We begin with a content audit. We collect your existing FAQs, help pages, product guides, policy documents, past support emails and chat logs, then identify the questions customers ask most often and the answers your team gives. Duplicates and contradictions are resolved with you; if two documents say different things about refunds, the chatbot would repeat the confusion, so decisions are made before anything is built. We then organise the content into a knowledge base. Each entry has a clear question or topic, a short and accurate answer, a longer explanation if needed, a last-reviewed date and an owner who is responsible for keeping it correct. Where articles are too long, we break them into focused pieces so the chatbot can retrieve exactly what matches the question. We choose a platform suited to your size and tools: a website chat widget, a WhatsApp chatbot, a help-centre search assistant, or a combination. For WhatsApp, see WhatsApp chatbots and automation. We configure the retrieval method so answers come from your content and nothing else, and write rules for tone, length, language and what the chatbot must never answer, for example legal advice, medical advice or anything involving personal account data it cannot verify. We design fallback behaviour carefully. When confidence is low, the chatbot asks a clarifying question, offers a few likely topics or hands over to staff with the conversation attached. Testing uses a long list of real questions, typos, mixed languages, vague phrases and questions designed to trip the chatbot up. We measure whether answers are correct, complete and consistent, and fix content problems rather than only adjusting the bot. After launch, we review conversations weekly at first. The most useful output is the list of unanswered or poorly answered questions, which becomes your content to-do list. Over time the knowledge base grows, and the chatbot handles more. We cannot promise a particular percentage of queries deflected, as that depends on your customers and content quality, but the setup makes improvement measurable.