See what people are asking. Build the answer.
People now use search and AI to decide what to buy, who to read, which channel to watch and what to trust. This workspace works on one subject at a time — your brand, product, book, channel, service or single item — so its public information is clearer, easier to find, and easier to evaluate. Question sources stay labeled so you can tell observed search data from AI-generated ideas.
Pick one subject and work through it.
A subject is the specific thing you want people to find — a business, person, product, book, channel or service. You can have several. For each one you'll establish a baseline, find real questions people are searching for, create clear pages and structured information, and track whether visibility changes.
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Checking…
This workspace separates observed data from AI-generated ideas. Search Console queries, public search questions and answers you personally check are recorded as their real source. AI can suggest opportunities, but those suggestions are labeled as ideas — never presented as search demand. We never claim publishing means indexing, ranking or citation, and page drafts use only the facts you supplied.
Indexed means a search system has made a page available for retrieval. Cited means an answer names or links to it as a source. Training means content may have been used during model development. Recommended means a system includes the subject as an option or shortlist choice. One does not guarantee another.
What do you want to work on?
Set up the subject once. The question scan, descriptions, answer pages, identity code and tracking all use this information.
Clear, consistent public information reduces ambiguity. Use the same official name, core description, links and verified facts across the places that matter. This file is your approved source of truth; the other tools reuse it so you do not accidentally describe the same subject three different ways.
What are people asking about this type of thing?
The scan uses the subject you just entered. You can adjust the scan topic if the exact product or book name is too specific. Results are saved with their source.
Next: check what AI says now
Save a baseline before you change the description or pages.
What does AI say now?
Get a clean baseline before changing anything. Search your exact subject in Google and check one AI. Save what you actually see so you can compare it later.
Start with the exact name.
Open Google and search the subject exactly. If an AI Overview appears, read it. Also notice the ordinary results: are they about the right subject, and do the descriptions match what is true?
Ask one AI a simple neutral question. Do not feed it your desired description first — the point is to see what it already knows.
Nothing saved yet.
Turn observed names into a gap review.
This uses only names you recorded from real results. It does not claim to know why a search or AI system chose them. The review compares what the observed answer emphasized with the approved facts you saved for your subject.
Next: find real demand
Now find the actual queries and questions people use around this subject.
What are people actually searching for?
Start with observed demand. Use your own Search Console data when you have it, plus live public searches. Save the useful questions with their source. AI-generated question ideas live in a separate box and are never labeled as real search demand.
Scan this subject for related questions.
This uses a private search connection through Supabase. It looks for question-style search results, FAQ results and discussion questions related to the subject, and saves each result with its source and scan date.
Open real search sources.
Look for People Also Ask, related searches, autocomplete wording, repeated questions and buying/comparison language. Copy only questions or queries you actually observed.
Search Console CSV
If your site has Google Search Console, export the Queries table as CSV and import it here. Those are queries for which your site actually received impressions — the strongest first-party demand signal in this workspace.
Useful for brainstorming, not proof of demand.
If you want additional possibilities, ask your AI for questions a buyer might ask. These are saved with an AI opportunity label so nobody confuses them with observed search data.
No questions yet.
Next: lock one clear description
Before building the answer pages, make sure the subject itself is described consistently.
One description, everywhere.
Consistency reduces confusion. When your site, profiles and listings use the same official name, core description and verified facts, search systems and people have a clearer picture of what the subject is.
Paste the right length in each place, then check it off.
Next: build the answer page
Now turn your strongest questions into useful public pages that answer them clearly.
Build the page that answers the question.
Turn a real customer question into a useful page: answer it plainly, show who the subject is for, add relevant proof, and make the next step clear. Drafts use your saved facts only — anything unknown stays in [brackets] for you to fill truthfully.
Next: turn it into everything
One good answer becomes a post, a reel hook, an email and an FAQ — without starting over.
Turn one answer into everything.
You already did the hard part — a clear answer or page. Now reuse it. Paste it in, pick what you need, and get a prompt to run in your own ChatGPT or Claude that turns it into a post, a reel hook, an email, an FAQ entry and a short description — in your voice, using only what is already there.
Next: test the page
Check whether the page leaves important questions, doubts or missing information.
What would stop someone here?
Use this after you have a page draft. The test is a simulated review, not real customer research. It can help you notice unanswered questions, unclear wording and likely objections before you publish.
Nothing saved yet.
Next: add real proof
Now add reviews, examples, credentials or other evidence you can verify.
Add the evidence.
Independent reviews, mentions and results give people — and search systems — more evidence about your subject. Collect only real, attributable proof here; it can support your pages and, where appropriate, your structured data.
Nothing saved yet.
Put useful proof where a buyer can see it: on the relevant page near the decision point, on the platform where people buy, and in legitimate third-party coverage or listings when you have them. Independent corroboration can make the public record easier to verify.
Next: your identity code
Now make your approved facts easier for machines to interpret.
Make the facts machine-readable.
This structured-data block helps search systems interpret the factual information already visible on the page — name, type, URL, offer details and eligible proof. It is support, not a ranking switch. Paste it into the relevant page, or hand it to whoever manages your site.
Next: the publish checklist
Check that the public pages you want discovered are accessible and clear.
Open the doors.
Use these practical checks to confirm that the public pages you want discovered are accessible, clear and supported by accurate information. Check each item off as you verify it.
There is no fixed timetable for search or AI systems to reflect a change. After important pages are published and available to search systems, re-run the same checks over time and record what actually changes.
Next: track your results
Record the same checks over time so you can see what actually changes.
Did it work? Prove it.
Pick a saved question, run the same check, and record what happened. Repeat after meaningful changes or on a schedule that makes sense for you. This dated log records what the systems actually returned.
No results logged yet.