Find Questions Your Content Does Not Answer
Use LLMIC prompt coverage analysis to compare audience questions with crawled pages, inspect answer evidence and prioritize useful content improvements.
Your website can mention a topic without answering the question a customer actually has. Prompt Coverage helps you compare questions with your pages and inspect the supporting text. The goal is a clearer answer for readers, not a larger pile of repetitive paragraphs.
What this guide helps you do
Content gap analysis reveals useful questions that your existing pages do not answer clearly. LLMIC’s prompt coverage workflow maps each question to available page evidence, then separates covered, partial and unsupported topics.
Build availability: This guide describes the updated workflow checked against the September 2026 development build. Some controls may not yet be included in the public installer. Check the release notes and your app version before following those steps.
The workflow at a glance
- Define the question
Be specific about audience and intent. - Match relevant pages
Use the current crawl as evidence. - Read the answer passage
Distinguish a real answer from a topic mention. - Plan a focused update
Add only what helps the reader.
Workflow illustration. These steps explain the process; they are not measured performance results.
Begin with real customer questions
Open Prompt Coverage in AI Intelligence with an appropriate plan and a completed crawl. Build questions from customer conversations, support requests and your existing search research. Keep audience and language explicit. “What does this cost for a small team?” is more useful than a vague phrase such as “pricing content.”
Inspect the matched page
Review the page suggested for each question and read the available passage. A shared word can help identify a candidate, but it does not prove the page answers the question. Check whether the answer is direct, complete enough for its purpose and supported by the page’s actual facts.
Separate absence from unavailable evidence
A missing or partial capture cannot establish an unanswered question. Check crawl success, document layer and retained content before calling something a gap. Equivalent wording may already answer the question without using the same phrase. Some omissions are intentional, especially when the topic is outside the page’s audience or purpose.
Choose between an update and a new page
If the question belongs naturally on an existing page, propose a short section where the reader needs it. If it serves a different intent, consider a separate guide linked from the relevant context. Avoid creating a new URL for every minor wording variation. Maintain one clear purpose for each page.
Review and measure the result
For an illustrative delivery question, a useful update states the actual delivery conditions rather than a generic promise of speed. Confirm those facts with the business before publishing. Recrawl the changed page to check the answer, and use a separate controlled benchmark if you want to observe AI mentions or citations afterward. Coverage alone does not prove visibility.
Quick reference
| What you see | What to do next |
|---|---|
| Topic mentioned | Read the passage to see whether it answers the question. |
| Equivalent wording | Keep a useful answer even without an exact phrase. |
| Incomplete capture | Obtain the missing evidence before reporting a gap. |
| Useful unanswered question | Plan a factual section or a distinct linked guide. |
Your next step
Continue with understand AI evidence, prepare a complete crawl, prepare a reviewed content change. Return to the documentation home for the full workflow. Before sharing an export, check its website, dates and filters, and remove private information. If a control is missing or a result looks wrong, contact support with your app version and a sanitized example.
Frequently asked questions
Use LLMIC prompt coverage analysis to compare audience questions with crawled pages, inspect answer evidence and prioritize useful content improvements.
Load the relevant crawl, define the prompt or question set, and connect only the supported provider needed for the measurement. Record the provider, model, location, language, and run time so the observation can be interpreted later.
Review the exact prompt, returned answer, mention or citation, cited URL, provider metadata, and any unsuccessful check. Keep measured provider output separate from local readiness checks and editorial recommendations.
Turn the observation into a review task with the affected page, captured answer evidence, intended audience need, proposed change, and owner. A missing mention is an observation from that test, not proof that the brand is invisible everywhere.
Repeat the same saved question set with comparable provider settings and record the new dated observation. Do not compare different prompts, models, markets, or time periods as if they were the same measurement.
A provider run is a dated observation, not a probability or ranking guarantee. Results can change by model, prompt, location, personalization, availability, and time, and a local checklist cannot prove inclusion in an AI answer.
Save or export the evidence, assign the approved action, and use the related guides linked on the page for the next check. After implementation, repeat the same workflow against a fresh crawl so the result is comparable.