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Voicescope — Conversational keyword research: from a keyword to the question behind it.

Voicescope is a free conversational keyword research tool: type one keyword and it writes the questions people might say to an AI assistant instead, grouped by the job behind them — hypotheses about phrasing, not search volume.

Why a keyword is not a question

A person typing into a search box strips their own context out — they know the box wants two words, so “I need the lease signed before the agent closes” becomes “edit pdf”. Spoken to an assistant, the context comes back. This puts it back on purpose and shows you the sentences.

Search boxes taught two generations of people to compress. You do not type what you want; you type the two words most likely to be indexed against it, and you do the rest of the work yourself by scanning ten blue links. Every keyword tool ever built measures the output of that compression — which is why a keyword list tells you what people typed and never what they needed.

An assistant removes the reason to compress. There is no box, no ten links and nothing lost by saying a full sentence, so people say the whole thing: the urgency, the device in their hand, the document on the table, and the specific way it is going wrong. The question that reaches a model is longer, stranger and far more specific than anything in a keyword report — and it usually does not contain the keyword at all.

That is the gap this tool works in, and what conversational keyword research means here. It does not find you more keywords. It takes one keyword and reconstructs the situations that get compressed into it, then writes what somebody standing in each of them would say.

Start with one job, write one page

Pick the job that matches your page, choose one question, and write a clear, helpful answer. Focus on one situation and one person.

Next step: Vectorscope

When conversational keyword research has given you a question and you have a page that answers it, use Vectorscope to see the page the way a retriever reads it, and whether the answer lands inside what it keeps.

Go to Vectorscope →

Who it is for

Conversational keyword research is for whoever writes the page an assistant might quote.

Content writers and SEO leads deciding which page to write next for a keyword they already rank for.
Product and support teams writing help articles and FAQs in the words customers actually use.
Founders and marketers checking whether their site answers the urgent situations, not only the head term.

It is not for estimating demand. If you need search volume, a keyword tool with measured data is the right instrument; this one writes hypotheses and says so.

Frequently asked questions

What is Voicescope?

A free conversational keyword research tool: it takes one search keyword and shows the questions people speak to an AI assistant instead of typing it. It crosses the keyword with four real-life contexts — urgency, device, the document in front of them, and what is going wrong — and writes the sentences that result, grouped by the job somebody is doing. No account, no payment.

How is this different from a keyword tool?

A keyword tool reports what people typed, which is already compressed: the two words most likely to be indexed, with the situation stripped out. This works the other way — it starts from the keyword and reconstructs the situations compressed into it. The output is sentences rather than phrases, most of which do not contain the keyword, and there are no volume figures because nothing here has been counted.

Are these real searches that people have made?

No, and the tool never says otherwise. They are written from a framework, not harvested from a query log, so each one is a hypothesis about how a need gets phrased out loud. That is genuinely useful for deciding what to write and genuinely useless as a demand estimate, and confusing the two is the mistake this answer exists to prevent.

Does it work for languages other than English?

Yes. The questions are generated in the language you ask for, written in that language rather than translated out of English — a phrasing translated from English is an English phrasing with foreign words in it, which is the opposite of what this measures.

What is JTBD, and why use it here?

Jobs-to-be-Done is the idea that people do not want a product, they want a job finished. It fits here because a spoken question is a job description: the urgency, the constraint and the obstacle are all in the sentence. Grouping by job rather than by wording is what makes the output a set of pages to write instead of a list of phrases to sprinkle.

Is it free, and what is the catch?

Free, with an allowance per visitor so one person cannot spend the day's budget. No account, no trial, no card. The catch, such as it is, is that the tool does one thing — conversational keyword research for one keyword at a time — and it will not measure whether an assistant names your brand, because that takes repeated checks on prompts you choose over weeks, which is the paid product.

Can I use the output on my own site?

Yes, without attribution. Write the pages, use the questions as headings, put them in an FAQ — they are yours. Two cautions: read each one out loud before publishing, because a question that sounds wrong to you will sound wrong to a reader, and do not paste all twelve into one page, which is how a page ends up serving four jobs and being retrieved for none.

The four axes

Each question is one crossing of the four, and it carries the labels it came from — which is what keeps conversational keyword research tied to a situation rather than to a list of modifiers.

01 · Urgency

How much time there is. The same need phrased at leisure and phrased in a panic retrieves different pages, and the panicked phrasing is the one nobody writes for.

right nowon the moveagainst the clock

02 · Who is asking, and on what

A phone with nothing installed asks a different question from a desk with everything installed. So does somebody with a colleague standing over them.

a phonenothing installedhands busy

03 · The thing in front of them

Not the category — the actual document, account, report or person. “A document” is a keyword. “The lease the agent is waiting for” is a question.

a leasea tax forma résumé

04 · What is going wrong

The mistake already made, the thing that cannot be found, the thing they are afraid of getting wrong. This is the axis that produces the questions worth a page.

fix one wordhide a numberdid it actually delete

How to read the result

The questions are grouped by the job somebody is doing, not by how similar the wording is. In conversational keyword research that grouping is the useful part: a job is something you can write one page for, and a wording cluster is something you can only write one paragraph for.

A job, not a cluster: Each group is a situation with a beginning and an end — somebody with a lease to sign before an office closes. If two groups could share one answer, they are one job and one page.
The labels under a question: They name the crossing it came from, so you can throw away a whole branch at once: if nobody in your market is ever on a phone, drop every question carrying that label instead of reading them one at a time.
The questions without your keyword: Those are the valuable ones, and they are why this is not a keyword tool. A question still containing the head term is one your existing page probably answers. A question that describes the problem instead is the one your competitor has not written yet.
The count, stated: The strip says how many questions came back and how many were asked for. A run that returns nine of twelve says nine — a tool that prints its target and shows its result reads as complete when it is not.

What this tool can and cannot tell you

Conversational keyword research done honestly names what it cannot see as clearly as what it can, and this page answers one question for one keyword.

What it can tell you

The shapes a keyword takes when it is spoken instead of typed, as full sentences you can read out loud and judge.
Which life context produced each phrasing, named, so you can tell a real job from a reworded keyword.
Which situations around your keyword you have never written a page for — usually the urgent ones and the frightened ones.
A starting set of headings in the words a reader would use rather than the words a keyword tool would.

What it cannot tell you

How many people ask any of these. There is no volume here and none is implied: every question is a hypothesis about phrasing, not a measurement of demand.
That anybody has ever asked one of them. They are written from a framework, not harvested from a query log, and this version cross-checks them against nothing.
Whether an assistant answers with your page today. That is a measurement over time on prompts you choose, not a property of one keyword.
Which question is worth your week. It names the job; the judgement needs a market you know and we do not.

Using the questions

The output of conversational keyword research is not a keyword list to sprinkle. Each group is a candidate page, and each question is a candidate heading in the words a reader would actually use.

1
Take one group, not the whole run
One job, one page. A page trying to serve four jobs answers the first sentence of each and is retrieved for none, because a passage has to stand alone to be quoted.
2
Use the question as the heading
Verbatim, including the awkwardness. A heading matching the question somebody asked is the largest retrieval improvement available on most pages, and smoothing it into marketing language undoes exactly that.
3
Answer in the first sentence
Yes, no, usually, it depends and on what. A paragraph that clears its throat before answering gives a retrieval system nothing to lift, however good the third sentence is.
4
Check the page can be read
Then run it through Vectorscope. A question answered in a passage that falls outside the retrieval cap is a question you have answered for nobody.

Words used on this page

Four terms that conversational keyword research leans on, defined once, because a page that uses them without defining them is a page an assistant cannot explain to anybody.

JTBD: The job somebody is trying to finish, which is never “edit a pdf”.
Conversational query: A question phrased as speech, carrying the context a keyword drops.
AEO: Writing to be the answer rather than a result in a list of links.
Long tail: The specific, low-volume phrasings that together outnumber the head term.

On this topic

Do AI assistants mention us?

Term: AI Visibility GEO AEO AI Overviews AI Mode
Read: AI assistants in October 2026: the questions spread out, the clicks did not The week Google closed the exit
Check: AI model usage

Every day The same questions asked of real assistants on a schedule, every answer kept in the evidence store. How the product works