Conversational Query Coverage Analyzer
People ask full questions out loud — and get back one spoken answer. This tool builds the who, what, where, when, why, and how question set for your topic, then scores whether your content answers each one in a way an assistant could actually read aloud.
Voice and AI assistants return a single answer, not ten links. So the winning move is boring and powerful: answer the whole question set, each in a concise, spoken-ready block. Paste a topic and your content below. The analyzer generates the natural-language questions your buyers ask, flags which you answer well, which are too terse or too long to be spoken, and which are gaps — then rolls it into one coverage score.
Query coverage inputs and result
| Question | Type | Status | Note |
|---|
Illustrative · RGM analysis. This is a transparent content audit, not a ranking prediction. It checks whether a clear, correctly-sized answer exists per question type — real answer wins also depend on authority, competition, and structured data.
How to use this analyzer
- Name the topic the way people say it.Use the spoken phrase, not a keyword string — “roof repair,” not “roofing services contractor near.” The generated questions inherit your phrasing.
- Paste your real content.Drop in the page copy, or just the sentences that answer questions. You can paste a draft to check it before you publish.
- Read the question set.The tool builds the who/what/where/when/why/how questions, plus cost and a yes/no qualifier — the shapes buyers actually ask out loud.
- Fix the reds and ambers.A gap means no answer was found; amber means the answer is too terse or too long to be spoken well. Add a concise 40–55 word lead answer under that question.
- Re-score and export.Watch the coverage climb, then copy a share link, download the CSV, or print a one-page brief for your writer or SEO.
RGM Expert Says
We run this in the content-planning meeting, before a word is written. Teams think in keywords; buyers ask in sentences. When you lay out the who/what/where/when/why/how set for a topic, the gaps are obvious — usually a site answers “what” five times and never answers “how much,” “when,” or “is it worth it,” which are exactly the questions people speak to an assistant.
The most valuable output is not the score — it’s the amber rows. A gap is easy: write the missing answer. Amber is the sneaky one: the page technically mentions the answer, but it’s buried in a 90-word sentence no assistant can read, or it’s a three-word fragment with nothing to say. That’s where the cheap wins live — add one concise 40–55 word lead answer, directly under the question, and a mediocre page becomes a spoken-answer candidate.
Two habits get the most from it. First, paste a draft, not just the live page — fixing coverage before publish is free; fixing it after is a re-write. Second, treat the generated questions as a starting skeleton, then replace them with the exact phrasings from People Also Ask, autocomplete, and your own sales and support logs. The tool gives you the shape; your buyers give you the words. Pair it with the FAQ schema generator to ship the markup, and the featured-snippet probability tool to see which answered questions are worth a real push.
How it works
The analyzer is deliberately transparent — no black box, no fake precision. It does three things: build the question set, find a candidate answer for each, and judge whether that answer is the right size to be spoken.
1. Build the question set. For your topic T, it generates the eight shapes people ask out loud: What is T? How do you do T? Why does T matter? Who is T for? Where does T apply? When should you use T? How much does T cost? Does T work? These map to the six question words plus cost and a yes/no qualifier.
2. Find the answer. For each question type it holds a small lexicon of trigger phrases (for “why,” words like because, benefit, matters, reason). It splits your content into sentences and finds the sentence nearest the ideal answer length that contains a trigger.
3. Judge the size. The candidate answer is scored on word count against the spoken-answer window:
Below 8 words it’s too terse to speak; above 70 it can’t be read aloud cleanly — both score amber. No trigger match at all is a gap. Coverage is then:
- ready — questions with a concise, correctly-sized answer present.
- partial — answered, but too terse or too long to be spoken well (half credit).
- gap — no answer found for that question shape (no credit).
The 40–55 word spoken-answer window reflects widely reported featured-snippet answer lengths (commonly ~40–50 words); the wider 8–70 tolerance avoids false negatives. This lexical heuristic is RGM’s own framing and is meant as a fast audit, not a ranking model.
One answer, not ten links
Typed search returns a page of options; a spoken question returns a single reply. That collapses the value of ranking “somewhere on page one” and raises the value of being the answer to a specific question. Assistants and AI overviews overwhelmingly lift concise, structured answers — often the featured snippet — which is why coverage of the question set, not raw keyword rank, is the better scoreboard.
Be honest about the numbers, though: clean, current “voice search share” figures are scarce and mostly dated, because platforms don’t report spoken queries separately. So don’t chase a vanity voice-traffic metric. Chase the durable behavior instead — people ask full questions and expect one good answer — and the same work wins voice assistants, AI answers, and featured snippets together. Coverage is how you measure your progress against that behavior. See the full model on the voice search marketing page.
Spoken-answer readiness, at a glance
Use these as a sanity check on your own answers — not as hard rules. Answer length and question shape matter more for voice than almost anything else on the page.
| Signal | Spoken-ready target | Why |
|---|---|---|
| Lead answer length | ~40–55 words | Long enough to be useful, short enough to read aloud |
| Answer placement | Directly under the question | Engines lift the block nearest the matched question |
| Question words covered | 6 of 6 (W/H) | Who, what, where, when, why, how — plus cost and yes/no |
| Markup | FAQPage / speakable | Tells the engine what to read |
| Reading level | Plain, grade 5–7 | Assistants and buyers both prefer plain language |
What the search field says
“The best interface is no interface.” The logical end of that idea is a spoken question answered in one sentence — no page, no scroll.
Answer the question the searcher actually asked, in the fewest words that fully answer it — that is the whole craft of winning the snippet.
Voice and AI answers reward the same thing: clear, structured, trustworthy content an engine can lift with confidence.