What is a conversational query?
A conversational query is a search written the way people talk. "Plumber Denver" is a keyword query. "Who can fix a burst pipe in Denver on a Sunday without charging a fortune?" is a conversational query. The second carries the same core need, plus context: urgency, timing and budget.
Conversational queries usually:
- are full sentences or questions, starting with words like "what", "how", "should" or "can";
- include small words such as "for", "to" and "without" that change the meaning;
- add conditions, such as a budget, a location or a constraint;
- sometimes follow on from an earlier question, as in a chat.
Google's Pandu Nayak described the older habit of typing keywords as "keyword-ese", meaning "strings of words that they think we'll understand, but aren't actually how they'd naturally ask a question" [1]. Conversational queries are what people type, or say, once they trust the system to understand them.
How does Google handle conversational queries?
Google handles conversational queries by interpreting the meaning of the whole question, including the small words, and in its AI features by splitting complex questions into several searches. That ability has been built up over a decade of updates.
When Google introduced BERT in October 2019, it said BERT would especially help with "longer, more conversational queries, or searches where prepositions like 'for' and 'to' matter a lot to the meaning" [1]. Its example was "2019 brazil traveler to usa need a visa": before BERT, Google returned results about US citizens traveling to Brazil, missing that "to" set the direction of travel [1].
In AI Mode, Google breaks a complex conversational query into subtopics and runs many searches at once, a technique it calls query fan-out [3] [7]. The extra searches are synthetic queries the user never sees.
When did Google start supporting conversational queries?
Google began building for conversational queries with the Hummingbird update, announced on September 26, 2013, which focused on natural language queries and the meaning behind them rather than individual keywords [2]. BERT in 2019, AI Overviews in 2024 and AI Mode in 2025 each made long, natural questions work better.
2013: Hummingbird
Google announced Hummingbird on September 26, 2013, about a month after it went live. It shifted Google toward understanding natural language queries by considering context and meaning over individual keywords [2].
2019: BERT
BERT, announced October 25, 2019, applied to about one in 10 English searches in the US and targeted exactly the longer, conversational phrasing that keyword matching handled badly [1].
2024: AI Overviews invite complex questions
Launching AI Overviews to everyone in the US on May 14, 2024, Google encouraged people to "ask your most complex questions, with all the nuances and caveats you have in mind, all in one go" [6].
2025: AI Mode
Google introduced AI Mode on March 5, 2025, for "complex, multi-part questions" that "might have previously taken multiple searches", with follow-up questions in the same thread [3]. It rolled out to everyone in the US on May 20, 2025 [7].
What is the difference between a conversational query and a keyword query?
A conversational query states a full need in natural language, while a keyword query compresses that need into a few terms. The table shows the same needs written both ways.
| Keyword query | Conversational query |
|---|---|
| dishwasher repair vs replace | Is it worth fixing a 10-year-old dishwasher that won't drain? |
| crm small agency | What's the best CRM for a five-person marketing agency that already uses Google Workspace? |
| visa usa brazil | Do I need a visa to visit the US from Brazil for two weeks? |
The difference matters for which results appear. In a Pew Research Center study of searches made in March 2025, Google showed an AI summary on 53% of searches of 10 words or more, against 8% of searches of one or two words [5]. Long, natural questions are where AI answers now sit, and where clicks to websites are least likely.
What is the difference between a conversational query and a long-tail keyword?
A conversational query is defined by how it is phrased, while a long-tail keyword is defined by how rarely it is searched. Many conversational queries are long-tail, because full sentences are rarely repeated word for word. But "how to tie a tie" is conversational and searched constantly, and "red nike air max 90 size 11" is long-tail without being conversational.
Can you find conversational queries in keyword research tools?
Mostly not. Keyword tools are built on repeated searches, and conversational queries are so varied that most show little or no recorded volume. A question that thousands of people ask in slightly different words can appear as dozens of near-zero entries, or not at all.
Better sources for the questions people really ask:
- your site search logs and Google Search Console queries, filtered for question words;
- sales calls, support tickets and chat transcripts;
- forums, Reddit threads and review sites in your niche;
- the "People also ask" questions on your main topics.
Data on what people type into AI assistants is scarcer still. No AI company publishes query volumes, so any figure for prompt volume is an estimate.
How do you optimize content for conversational queries?
You optimize for conversational queries by answering real questions directly and completely, not by writing a page for every way a question can be phrased. Google says site owners do not need to worry about missing "long-tail" keywords or every variation of how someone might search, because its systems understand synonyms and general meaning [4].
What helps:
- Use questions as headings where people genuinely ask them, and answer in the first sentence below.
- Handle the conditions. If people ask about budgets, timeframes or situations, cover them explicitly: "for a small agency", "if it won't drain".
- Keep the small words. Words like "for", "without" and "to" carry meaning in conversational queries [1]. Search Insider's study Is deleting a stop word safe? tested how often dropping one changes Google's results.
- Cover the follow-ups. Conversational search runs in threads, so answer the next obvious question on the same page.
Do not stuff pages with every phrasing of a question. That reads badly, and Google says it is unnecessary [4].