AEO Strategy: A 90-Day Answer Engine Optimization Plan for 2026
An AEO strategy is a plan for getting your brand named and cited in AI-generated answers. It decides four things: which prompts you need to show up for, which pages should answer them, where else on the web you need to be mentioned, and how you will measure whether any of it worked. Everything else is execution.
Answer engine optimization (AEO) and generative engine optimization (GEO) are the same practice under two names; we explain why in GEO vs SEO vs AEO. So this is also a GEO strategy. If you want the definitions first, start with what AEO is. If you want a step-by-step build of the measurement side, how to build a GEO strategy from scratch goes deeper on prompt libraries and gap matrices.
This page is the strategy layer: the best practices that decide where effort goes, a 90-day plan, and two things that went wrong when we ran this on our own site.
Last updated October 4, 2026. This page replaced an older GEO playbook that carried statistics we could not source; more on that below.
The Short Version
If you only read one section, read this one. Six decisions make up most of an AEO strategy:
- Measure inside the engines. Search Console positions and impressions are a poor proxy for AI visibility.
- Choose unbranded buyer prompts. "Best tools for X", "X vs Y", "how do I solve Z". Your own brand name tells you nothing.
- Make every answer quotable. The answer goes in the first sentence under the heading, and each section stands on its own.
- Keep facts current, on a schedule. Stale pages lose citations to pages that are merely newer.
- Say the same thing everywhere. Engines corroborate. A price that differs across your own pages is a reason not to quote any of them.
- Get mentioned where engines already look. Reviews, lists, forums and other people's articles. For a small site this is usually the binding constraint.
The rest of this page is why, and how.
AEO Best Practices
These are ordered by how much they changed our own plan, not by how often they appear in other guides.
1. Measure in the engines, not in Search Console
This is the practice we got wrong for longest.
Google Search Console reports positions and impressions, and for AI-heavy queries both mislead. Search Console counts a citation inside an AI Overview as a position. On October 4, 2026 we checked three of our queries against a live US Google result: Search Console placed us at position 3.6 for chatgpt knowledge cutoff, 4.2 for peec ai alternatives and 7.0 for llm seo tools. On the live result page, we were outside the top 10 for all three.
Impressions are worse. Over the four weeks to early October, our impressions in positions 1 to 10 rose from about 507 a day to about 932 a day. Clicks did not move: roughly 6 a day before and after. About a third of the rise came from one family of queries that appeared on September 23 ("best llm seo rankstar io" and close variants), at a couple of hundred impressions a day and zero clicks. Those were not people.
What to do instead: run your buyer prompts through ChatGPT, Google AI Overviews, Perplexity and Google AI Mode, and record whether you are named, how you are described, and who is named instead. Do it on a schedule, more than once per prompt. Use Search Console for indexing and for clicks, where it is reliable.
2. Pick prompts your buyers ask, and leave your brand name out
A prompt library built on "what is [your brand]?" will show you a high citation rate and tell you nothing. Engines often know who you are when asked directly. The question that matters is whether they name you when a buyer asks about the problem you solve.
Three kinds of prompt cover most of it:
- Discovery: "best AI visibility tools for a B2B SaaS team"
- Comparison: "Profound vs Peec AI", "alternatives to Semrush for AI tracking"
- Problem: "how do I find out whether ChatGPT recommends my product"
Start with 20 to 40. A short list you actually re-run beats a long one you check once.
3. Put the answer first and make each section stand alone
Engines extract passages, not pages. The passage they lift is usually the first sentence or two under a heading that matches the question. So the heading should be the question, in the words a person would use, and the first sentence should answer it plainly. Context comes after.
Each section should also make sense if it is the only thing an engine reads. "As mentioned above" breaks that. So does a table whose meaning depends on a paragraph three screens earlier.
You can see this on this page. The first paragraph defines an AEO strategy in one sentence before anything else happens.
4. Keep facts current, on a schedule
This is where our own strategy failed in September, and it is the worked example below. The short version: a page that answered a fast-moving question went a month without an update, and by the time we looked, the AI Overview for its main query cited two competitors whose pages were newer.
Freshness needs an owner and a calendar, not good intentions. For each page that answers a question with a changing answer (prices, model versions, rankings, statistics), write down what event makes it stale and who checks it when that event happens.
5. Say the same thing about yourself everywhere
AI answers lean on corroboration. If your pricing page says one thing and your blog says another, an engine has two versions and a reason to trust neither.
We found this the hard way. In September 2026 an audit of our own site found our entry price stated wrongly in 239 places, including prices baked into 22 blog header images where no text search would find them. A later sweep missed three claims about a free trial we no longer offer, because they used a word order the search pattern did not expect. Every one of them was a sentence an engine could have quoted.
Keep one source of truth for product facts, and sweep everything that repeats them, images included, whenever a fact changes.
6. Source every number, or delete it
A statistic without a source does damage twice. It is unverifiable, so it is a weak thing to be cited for. And other pages copy it, so when it turns out to be wrong it is wrong in a dozen places.
The older version of this page is an example. It told readers that measuring a week after publishing "underestimated results by 40 to 60%", attributed to our own platform data. No such report has been published, so the claim is gone. So is a before-and-after chart in the old header image that presented illustrative numbers as if they were results.
Our rule now: if we cannot link the primary source and date, the number does not ship. We do not swap it for a different plausible number either.
7. Get mentioned on the sites engines already trust
This is the opinion in this guide most likely to be wrong, so here it is plainly: for a small site, off-site mentions matter more than anything you do on your own pages.
The best public evidence we know of is Ahrefs' study of 75,000 brands. Brand web mentions correlated with AI Overview visibility at 0.664, branded anchors at 0.527, and backlinks at only 0.218 (Ahrefs, updated April 2026). Correlation is not cause, and the study covers Google's AI Overviews, not every engine. But it matches what we see: the sources AI answers cite in our category are mostly comparison articles on other sites, plus Reddit and YouTube, and our own pages rarely beat them on writing alone.
In practice that means product listings and review profiles kept current, inclusion in the comparison articles that already rank for your category, and genuine participation in the forums where your buyers ask questions.
8. Let the crawlers in, and treat schema as context
Two hygiene checks that take an afternoon:
- Crawler access. Check robots.txt for GPTBot, OAI-SearchBot, PerplexityBot and ClaudeBot; our AI crawler checker does all of them in one step. A page a crawler cannot fetch cannot be retrieved for an answer.
- Schema. Use it to describe the page accurately, and keep it matched to what is visible. Do not expect rich results from FAQ markup: Google has limited FAQ rich results to "well-known, authoritative government and health websites" since August 2023 (Google Search Central). We found 37 of 408 FAQ questions on our own site marked up with no visible answer behind them, and fixed that by rendering the page and the schema from one list.
An llms.txt file is cheap and we publish one (our llms.txt generator drafts one from your sitemap), but we have seen no evidence that any engine's citations depend on it. Do it last.
The 90-Day AEO Plan
A plan has to survive contact with how fast AI answers change. One study tracked 530,875 citations across 2,398 queries for seven days and found that, day to day, a median 82% of a ChatGPT answer's sources changed, 92% on Gemini, 78% on Google AI Mode and 43% on Perplexity (GetMentions, July 2026). So no single reading means much, and the plan is built around repeated ones.
| Weeks | Focus | Output |
|---|---|---|
| 1 to 2 | Baseline. Choose 20 to 40 unbranded prompts. Run each several times across ChatGPT, Google AI Overviews, Perplexity and Google AI Mode. Record who is named. | A table of prompts by engine: named, not named, who instead |
| 3 to 4 | Fix what blocks citation. Crawler access, indexing of your key pages, and the answer-first structure of the pages that should answer your top prompts. Correct inconsistent product facts. | Key pages indexed, structured, consistent |
| 5 to 8 | Publish and get mentioned. Fill the gaps where a competitor is named and you have no page. In parallel, work the off-site list: review profiles, comparison articles, forum answers. | New or rewritten pages, a log of off-site placements with dates |
| 9 to 12 | Measure and decide. Re-run the baseline prompts the same way. Compare by engine. Keep what moved, revisit what did not, and set the freshness calendar. | Before and after by engine, next quarter's list |
Log every change with a date. When a citation appears, you want to know what you changed before it, and when a citation disappears, you want to know whether you changed anything at all. With day-to-day churn this high, many changes in a single reading are noise, which is why the comparison in weeks 9 to 12 should use several runs per prompt, not one.
Engines do not move together
The same study is useful for planning by engine. Perplexity's citations changed far less: 43% of sources day to day, against 82% on ChatGPT and 92% on Gemini. A gain on Perplexity is more likely to still be there next week; a gain on ChatGPT needs more readings before you believe it.
Google is also two surfaces, not one. AI Overviews and AI Mode can cite different sources for the same question, so check both rather than assuming one stands in for the other.
Worked Example: Our Most-Clicked Page Went Stale
Here is the failure that most changed how we plan freshness, with the dates.
The page. Our post on ChatGPT's knowledge cutoff is the one non-brand page on our site that people reliably click: 87 of our 176 clicks in the four weeks to October 4, 2026.
What changed in the world. OpenAI announced GPT-6 on September 3, 2026. Its knowledge cutoff, April 30, 2026, is later than anything our page mentioned.
What our page said. A month later, our title and summary still led with GPT-5.6's February 16, 2026 cutoff, and GPT-6 did not appear anywhere on the page. When we checked it line by line against OpenAI's documentation, it was worse: it still called GPT-4o the default for free ChatGPT users, eight months after OpenAI retired GPT-4o from ChatGPT, and four older OpenAI dates were simply wrong.
What happened to the page. A keyword database had our page at position 6 for chatgpt knowledge cutoff on September 13. On October 4 it was outside the live top 10, and the AI Overview at the top of the result cited two other sites, both of which covered GPT-6.
What we can and cannot say. We cannot prove the stale content caused the drop. Rankings move for many reasons, and we have one reading on each side. What we can say is that the page was factually behind, on the one topic where being current is the whole point, for a month, and nobody owned noticing.
What we changed. We rewrote the page against each vendor's own documentation, linked every row to its source, and wrote down the trigger that makes it stale: any major model release. The fix took an afternoon. The month it sat out of date is the cost.
Common AEO Strategy Mistakes
Starting with content. Publishing before you have a baseline means you cannot tell what any of it did.
Treating the strategy as a one-time project. Citations churn daily. A quarter is a reasonable cycle; a single campaign is not a strategy.
Running two pages for one intent. Until this rewrite, our site had two near-identical GEO strategy guides. This one collected 20 impressions in 90 days. Two pages competing for the same answer split whatever signals you have.
Optimizing only your own pages. The sources AI answers cite are often not brand sites at all. If you are absent from the lists and forums an engine draws on, a better page of your own may not change the answer.
Reporting a single number. A sitewide average blends engines, prompt types, branded and unbranded queries. Report by engine and by prompt type, with the raw counts.
Where RankScope Fits
The measurement in this plan is the part that does not scale by hand. Forty prompts, several runs each, across four engines, every week, is thousands of readings a quarter.
RankScope runs your prompts on a daily schedule and records which brands each engine names, how it describes them, and how that changes over time. Starter is $49/mo, or $39/mo billed annually, and covers ChatGPT and Google AI Overviews with 40 monitored prompts. Professional ($149/mo, or $124/mo billed annually) covers all four engines (ChatGPT, Google AI Overviews, Perplexity and Google AI Mode) with 150 prompts. See pricing for the full comparison.
The strategy decisions in this guide, which prompts matter and what to publish, stay with you.
Frequently Asked Questions
What is an AEO strategy?
An AEO strategy is a plan for getting your brand named and cited in AI-generated answers from engines like ChatGPT, Google AI Overviews, Perplexity and Google AI Mode. It decides which prompts you need to appear for, which pages answer them, where else you need to be mentioned, and how you measure the result inside the engines.
Is an AEO strategy different from a GEO strategy?
No. Answer engine optimization and generative engine optimization describe the same practice: earning citations in AI answers. The names come from different communities. A plan for one is a plan for the other.
What are the most important AEO best practices?
Measure inside the AI engines rather than in Search Console, track unbranded buyer prompts, put a direct answer at the top of each section, keep facts current on a schedule, state your product facts the same way everywhere, source every statistic, and get mentioned on the sites engines already cite.
How long does an AEO strategy take to show results?
Nobody can promise a timeline, including us. AI citations change daily, so plan on quarterly cycles: a baseline, a round of fixes and publishing, and a re-measurement around 12 weeks later using several readings per prompt.
How many prompts should an AEO strategy track?
Start with 20 to 40 unbranded prompts across discovery, comparison and problem questions. Re-running a short list consistently is worth more than checking a long list once.
How do you measure AEO?
Run your prompts through each AI engine on a schedule and record whether your brand is named, how it is described, and which competitors are named instead. Compare by engine and by prompt type over time. Search Console positions and impressions are not reliable measures of AI visibility.
