Conversational Search
Conversational Search enables information retrieval through natural dialogs instead of rigid keywords – the future of search engines and enterprise search.
Conversational Search replaces keyword search with natural dialogs – with direct answers, follow-up questions, and contextual understanding.
Explanation
Instead of a list of links, Conversational Search delivers direct answers in dialog. Follow-up questions refine the search. Perplexity, Google SGE, and ChatGPT Search are prominent examples.
Marketing Relevance
Fundamentally changes SEO: Content must be optimized for Answer Engines (AEO). Internally it replaces dashboard search with natural questions.
Example
User asks "Which CRM fits a 10-person team?" → System answers with recommendation → User asks "And what does it cost?" → Contextual follow-up.
Common Pitfalls
Hallucinated answers without citations. Zero-click problem for publishers. Context drift in long dialogs.
Origin & History
TREC Conversational Assistance Track (2019) started academic research. Bing Chat (2023) and Perplexity (2023) brought conversational search mainstream. Google SGE (2024) and ChatGPT Search (2024) followed. 2025 conversational search is the dominant search trend.
Comparisons & Differences
Conversational Search vs. Traditional Search (Google)
Traditional search delivers link lists; Conversational Search delivers direct answers in dialog with follow-up capability.
Conversational Search vs. RAG
RAG is a technique (retrieval + generation); Conversational Search is a product experience that can use RAG as foundation.