The workhorse of AEO
Posts written for the question an engine was asked
A blog post is the most flexible unit of AEO content and the easiest one to waste. The version that earns a citation answers one buyer question completely and commits in its first paragraph. The version most firms publish is a topic, written for a reader who is already interested, and no engine has a reason to reach for it.
Every plan queries all 6. See how each engine picks who it names
What we measured
of the pages ChatGPT cites carry structured data, and 65% of the pages Google AI Mode cites do (SE Ranking, 2026). The cited pages are specific and organized rather than broad.
Engines queried
ChatGPT, Claude, Perplexity, Gemini, Google AI Mode, Microsoft Copilot. Every plan, including the free one.
Answers kept
Every answer is stored word for word, so any number on your report can be checked against the text it came from.
The gap this closes
- The blog already exists, is updated, and does nothing for vendor selection.
- It answers the questions you find interesting, not the ones buyers ask an engine.
- Buyers write full sentences carrying constraints: headcount, industry, compliance, the situation.
- A post can be correct and still unusable, with the answer buried in paragraph nine.
What you end up with
- Finished drafts aimed at named questions from your scan, not a content calendar.
- The answer committed in the first paragraph, which is the part an engine lifts.
- One buyer question fully answered per post, in your voice, ready to publish.
- Published straight to your CMS, then re-scanned so you can see if it moved.
How it works
Three steps, and you only do the first one.
The question comes from the record, not a brainstorm
Each draft is aimed at a buying question your scan already recorded as lost, in buying-intent order. The brief carries the exact phrasing the engines were asked, the competitors they named instead, and the verbatim answers, so the draft is written against a real target and not a guess about one.
The draft commits early and stays checkable
The question becomes a heading, the answer lands in the first two sentences, and the rest of the page earns it with specifics a reader can verify. The FAQ block goes in with its markup, the internal links go in, and the whole thing arrives ready to paste rather than ready to brief.
You publish, and the next scan referees it
Publishing runs through your CMS connection, so the post lands on your domain under your byline. The next scan re-asks the question the post targeted on all six engines. That is the only honest test, and it is why every draft targets named questions from the start.
What you get on each plan
You get finished drafts aimed at named questions, not a content calendar. This is what lands, per plan, with the monthly volume read live from the plan configuration.
Track
Free- No drafting on this tier, and we will not pretend otherwise
- Every question where a competitor was named instead
- Ranked by buying intent, competitor names attached
- The topic list a paid plan would draft, shown undrafted
- Next free scan re-asks the same questions
Fix
$99/mo- Every losing question becomes a finished draft
- Answer-first, with the FAQ block already marked up
- Internal link plan pointing at your money pages
- The engine answer that lost it sits alongside
- Publishes to your domain, next scan referees it
- Tracked from idea to published to cited
Dominate
$499/mo- Wider budget reaches further down your buying questions
- Higher draft volume against the questions you are losing
- Every brief reused by the video and newsletter generators
- One buyer question answered in three formats
Rule
$1999/mo- The same production run across a portfolio
- A person picks which brand gets the volume
- One scan per client, one queue
- Built for an agency book of work
Which engine actually leans on this
Your row is Your own site. The rest of the grid is on the engines page.
| Channel | ChatGPT | Claude | Perplexity | Gemini | Google AI Mode | Microsoft Copilot |
|---|---|---|---|---|---|---|
| Your own site Schema, answer pages, llms.txt, crawlability | Heavy Vendor | Heavy Vendor | Heavy Measured | Heavy Our read | Heavy Vendor | Heavy Our read |
| Reviews and directories G2, Clutch, Capterra, Trustpilot, Google Business | Moderate Our read | Light Measured | Heavy Our read | Moderate Our read | Moderate Measured | Moderate Measured |
| Reddit and forums Unpaid opinion, where buyers go for the unvarnished view | Light Our read | Light Measured | Heavy Our read | Moderate Our read | Heavy Measured | Moderate Measured |
| Video YouTube. Only counts once there is a transcript | Moderate Our read | Light Our read | Moderate Our read | Heavy Our read | Heavy Measured | Light Measured |
| Newsletters LinkedIn, Substack, Beehiiv. Published under a named person | Moderate Our read | Light Our read | Moderate Our read | Heavy Our read | Heavy Measured | Light Our read |
| News and PR Earned coverage, wire pickup, journalist mentions | Heavy Vendor | Heavy Vendor | Heavy Our read | Moderate Our read | Moderate Our read | Moderate Our read |
Your own site. Your own site counts most for ChatGPT, Claude, Perplexity, Gemini, Google AI Mode, Microsoft Copilot.
Reviews and directories. Reviews and directories counts most for Perplexity. It is a light signal for Claude.
Reddit and forums. Reddit and forums counts most for Perplexity, Google AI Mode. It is a light signal for ChatGPT, Claude.
Video. Video counts most for Gemini, Google AI Mode. It is a light signal for Claude, Microsoft Copilot.
Newsletters. Newsletters counts most for Gemini, Google AI Mode. It is a light signal for Claude, Microsoft Copilot.
News and PR. News and PR counts most for ChatGPT, Claude, Perplexity.
Where this comes from
- OpenAI: publishers and developers FAQ States that a site must allow OAI-SearchBot to be eligible for ChatGPT search at all.
- OpenAI: introducing ChatGPT search The named publisher partnerships behind the news and PR row.
- Anthropic: web search tool documentation Citations are always enabled, and Claude only searches when a question needs current information.
- Google Search Central: AI features and your website AI Overviews and AI Mode report inside the ordinary Search Console Performance report.
- Search Console Help: impressions, position and clicks How AI Mode counts a click, and why a follow-up question is treated as a new query.
- Dan Petrovic: citation mining of OpenAI grounding metadata Reddit retrieved in 76 percent of OpenAI searches and selected 0.61 percent of the time.
- Our production scan database, read 12 August 2026 46 completed reports, 34 brands, 419 buying questions, 2,421 answered buying cells. Where the per-engine mention rates come from.
- Our 15-region managed services study 743 records, 566 named by an engine, and the per-engine corroboration rates.
- What our crawler finds on real sites 39 readable crawls: 38 with no llms.txt, 26 with no FAQ schema, 16 with no Organization schema.
- How we check an AI visibility report The method behind every first-party number on this page, including what it cannot show.
Engine behaviour moves month to month. This table is maintained, not published once.
The proof, including the parts that flatter nobody
The reason we push structure this hard is that we can see how thin the average result is. Across the 46 completed reports behind this page, the best any engine managed was naming the brand in 7.4% of the buying questions we put to it, and the others sat between 0.4% and 4.0%, measured on firms that arrived already suspecting they were missing.
Our managed IT study says something sharper about where a post can help. Asked to recommend managed IT providers, Perplexity retrieves before it answers and produced 101 of 257 names we could resolve to a real firm, while Claude, answering from memory, produced 2 of 129 in the same study. A published page is how you reach the first kind of engine. The second kind changes slowly and by corroboration, and no single post moves it.
What we do not claim: we cannot prove a specific post caused a specific citation. What we can show is the question it targeted, the engines asked before and after, and whether the answer changed. That is correlation with a date stamp, which is more than a content report usually offers and less than proof.
Read the MSP AI Visibility Report 2026 →A worked example: the brief a draft is written from
Nothing here is a template with blanks. A brief is a record pulled out of your scan, and this is one, with an illustrative brand and an illustrative engine answer standing in for a real customer's.
Brief: content brief 3 of the month
| Field | Value |
|---|---|
| Target question | which IT provider should a 40-person accounting firm use for SOC 2 readiness |
| Engines asked | All six. Four answered, one returned nothing, one named you in passing |
| Verdict | Absent on ChatGPT, Claude and Google AI Mode; brief mention on Perplexity |
| Named instead | Vendor A on three engines, Vendor B on two, Vendor C on one |
| Quote from the losing answer | "Look for a provider with prior SOC 2 Type II experience in professional services and a named compliance lead." |
| Angle the quote hands you | Answer the criteria the engine itself stated, with evidence, before anyone else does |
| Funnel position | Buying intent, weighted highest in the Index |
What the draft is required to contain
- H1 phrased as the question, so the match is not left to inference.
- A committed answer inside the first two sentences, before any context.
- The five artefacts an auditor asks for, named, because the engine's own answer asked for evidence.
- A short table of what a 40-person firm needs versus a 400-person firm, since headcount is the qualifier in the question.
- An FAQ block of four pairs, marked up, matching the visible text word for word.
- Internal links to the SOC 2 service page and the comparison page naming Vendor A.
The brief is visible to you before anything is written, and you can reject it. That matters more than it sounds: the brief is where a wrong assumption about your business is cheap to fix, and a draft is where it is expensive.
How it actually works
The mechanism, for anyone who wants it. Open a card to read the detail.
Why a keyword tool cannot see these questions
Search volume describes what people type into a search box. A buying question put to a chat window is a different register: longer, phrased as a full sentence, and carrying the qualifiers a keyword would strip. Nobody types their headcount and their compliance regime into a search bar, and everybody mentions both when they ask an assistant who to hire.
Read the detail
The practical consequence is that the questions worth winning report no volume at all. We hit this on our own site, where the planner returned zero for the exact phrasings buyers were using, and we published the measurement behind it rather than asserting it. A tool that reports zero is not telling you the demand is absent. It is telling you the demand moved to a surface it cannot see.
So the question set comes from the answers themselves. We ask the engines, read what comes back, and treat the questions where a competitor gets named as the demand signal. On a first scan we also seed some phrasings from what people are observably searching, so the set is anchored in both places rather than one.
What retrieval does with a page
A generative answer is assembled, not recalled. The system runs a search, pulls candidate documents, and writes its response grounded in their text. Every property that makes a document cheap to use at that step is a property worth engineering into a draft, and the research literature on this is direct about which ones matter.
Read the detail
The academic work on generative engine optimization measures source-side changes and finds real movement, with the authors reporting gains of up to 40% and stating plainly that the effect varies by domain. Read the caveat as the finding: what works is a function of the question and the category, which is why a draft aimed at a named question beats a draft aimed at a topic.
The engineering falls out of that. State the question in a heading so the match is obvious. Answer it in the next sentence so an extractor gets your position rather than your preamble. Carry specifics, because a passage with five verifiable facts survives a quotation and a passage of adjectives does not. Define terms instead of assuming them, since the retrieved chunk arrives without your other pages around it.
Being read and being cited are different outcomes
A post that ranks well and gets traffic can still lose every AI answer. The systems deciding who to name are checking whether the wider web agrees with you, and a claim that exists on your domain alone is a claim with one source. The fix is not a better paragraph on your own site. It is being described the same way somewhere you do not control.
Read the detail
That is why a post is drafted with its supporting cast. The FAQ pairs give an extractor something to lift, the internal links tell a crawler what else you cover, and the same brief feeds the LinkedIn edition and the video script, so the argument shows up somewhere other than your own site. One post on your domain is a claim. The same claim in four places is corroboration.
What it costs
Prices and monthly draft volumes below read from the live plan configuration, so this page cannot drift from what your account gets.
| Plan | Price | Questions | Scans |
|---|---|---|---|
| Track | Free | 5 | 1/mo |
| Fix | $99/mo | 10 | 4/mo |
| Dominate | $499/mo | 25 | 4/mo |
Rule is portfolio level and sales-assisted, which is the right conversation if you are running this across a book of clients.
See where you stand first
Run a free scan and find out which of these gaps you actually have.
Get your free auditFrequently asked questions
How are topics chosen?
From your scan, never from a brainstorm. Each draft targets a buying question where an engine named a competitor and skipped you, and the highest-intent gaps go first, so the earliest posts sit closest to a purchase decision.
Will the drafts sound like my company?
They arrive in a clear, specific B2B voice with your positioning and your real service detail in them, and they are yours to edit. Because they lead with substance instead of adjectives, most need a light pass to add your point of view rather than a rewrite.
Will AI-drafted content get my site penalized by Google?
Google's spam policies target scaled content abuse, meaning thin mass-produced pages, and the definition turns on the page rather than on who wrote it. Every draft here is grounded in your positioning and a real buyer question, and you review before publishing, which is the quality floor that keeps a page safe on both Google and the engines.
How long are the posts?
Long enough to answer the question and no longer. Most land between 1,200 and 2,000 words because that is what a thorough answer with checkable specifics takes, but the length follows the question rather than a quota.
I already publish a blog. Do I still need this?
The scan answers that better than we can. If your existing posts already cover the buying questions where engines skip you, your gap is small. Most firms find the opposite, and this closes that specific gap alongside whatever you already publish.
How do I know a post worked?
You watch the question, not the post. The Content Engine tracks each piece against the buying questions it targeted, and the next scan re-asks those questions on all six engines. If the answer starts naming you, the piece is marked cited.
Sources and further reading
- SE Ranking, structured data in AI answers (via Search Engine Land): 71% of pages ChatGPT cites include structured data; 65% for Google AI Mode.
- Aggarwal et al. 2024, Generative Engine Optimization (arXiv:2311.09735): A KDD 2024 paper measuring how source-side changes move visibility in generative engine answers; the authors report gains of up to 40% and caveat that they vary by domain.
- Google Search Essentials, spam policies: Scaled content abuse is the violation, defined by thin mass production rather than by who or what wrote the page.
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