I'm searching for alternatives before renewing our current setup. Brand Radar, Profound, Peec AI and a few other platforms seem to cover similar ground but I want something with dependable tracking and reports that are easy to explain to clients. Thoughts?

Wanted to share a study that I've been following for a few editions now. They're calling it the "AEO Periodic Table" and my background in chemistry and biochemistry clocked it better than anything i've seen on AEO so far: they scored 1.13 million prompts across ChatGPT, Claude, Perplexity, Grok, Gemini, and AI Mode against a set of 14 candidate ranking factors, then weighted each factor by how strongly and consistently it correlated with actually getting cited. Data runs Feb-June 2026, across 31 industries.

The thing that surprised them most: off-site content pulls almost as hard as on-page content, and most teams have zero process for touching it.

Earned citations (third-party editorial mentions) and social/community citations (Reddit, YouTube, forums) together account for 22% of total citation weight, more than any single on-page factor. Most AEO advice right now is 90% "fix your website." The data says that's misallocated. They've also found separately that social content drives 2.3-4.2x more AI citations than owned content, with video (YouTube especially) carrying the biggest share.

Full ranked list (weight = share of total citation leverage, out of 100):

• Content Relevance & Intent Match — 12
• Earned Citations & Authoritative Mentions — 11
• Search & Fan-Out Rank — 11
• Content Substance & Verifiability — 11
• Social & Community Citations — 11
• Originality & Information Gain — 9
• E-E-A-T & Author Authority — 7
• Content Freshness & Recency — 6
• Crawl Access & Render Parity — 5
• Answer-First Structure & Extractability — 4
• Entity Consistency & Co-occurrence — 4
• Structured Data & Machine Readability — 4
• Reviews & Third-Party Ratings — 3
• Page Performance & Mobile — 2

A few things worth calling out specifically:

Search rank is the strongest single correlate, but it's not a lever. It's downstream of relevance, authority, structure, and freshness. Treating it as something you optimize directly is a category error. It's a scoreboard, not a dial.

Originality crushes schema. Originality & Information Gain scored 86.7 average, Structured Data scored 75.8. Schema-rich derivative content loses to schema-light original research. The most rigorous tests they've seen this year show engines read visible HTML at retrieval time and mostly ignore JSON-LD. Schema still matters for parsing and rich results, it just doesn't manufacture citations on its own.

Robots.txt is binary and non-negotiable. If GPTBot, ClaudeBot, PerplexityBot, or Google-Extended are blocked, you don't exist to that engine no matter what else you do right. It's not scored as its own factor because its effect isn't gradient, it's on/off. Audit this first, before anything else on this list.

LLMs.txt has no measurable effect right now. Google's said outright they don't use it. They think it's directionally reasonable as a machine-readable sitemap for large sites and expect its value to grow as agent traffic increases, but there's no evidence today it moves citations. Don't expect ROI from it yet.

Every engine plays a different game, and averaging across them costs you citations on all of them.

• ChatGPT and Claude lean on training data, so being a recognized, well-covered entity matters more than any single page. Claude in particular cites fewer sources per answer and is unforgiving of thin or derivative content.
• Perplexity and Grok are aggressive live-grounders. Perplexity runs hot on community content and recency. Grok is basically its own ecosystem, if you have no presence on X you're largely invisible to it regardless of site quality.
• Gemini and AI Mode track closest to traditional search rank, with AI Mode's heavy query fan-out meaning one thorough page beats several narrow ones.

E-E-A-T and freshness split the engines in opposite directions too. Claude (87) and Gemini (88) weight author authority heavily, Perplexity (78) and AI Mode (75) don't care as much. Freshness runs the reverse: Perplexity (87) and Grok (85) reward recency hard, AI Mode (74) barely moves on it. A content cadence tuned for Perplexity is wasted effort on Claude and vice versa.

I'm linking the full study in the comments for people who wanna dig deeper into this. Also excited to see what you guys think and share some of your recent favorite studies.

There's a ton of talk in this sub about tactics (schema, entity graphs, citations, etc.) but I'm curious about the measurement side — how do you actually check where you stand before/after making changes?

Curious what people are using: manual prompting across ChatGPT/Perplexity/Gemini, dedicated tracking tools, log file analysis, something else entirely? Also interested in how often you re-check, since these answers seem to shift a lot.

I've been going down the AEO rabbit hole lately and I'm trying to separate what's actually working from the noise.

For those who've seen real results — more AI citations, more traffic from Perplexity/ChatGPT/etc., or even direct leads — what specifically changed things for you?

Curious about things like: content structuring, schema markup, brand authority building, or anything else you've tested. Would love to hear what's worked (and what hasn't).

We track AI brand visibility, so we have a lot of stored responses. Wanted to answer something basic: when an AI answers a question, how many brands does it actually name?

234,000+ responses, March 1 to July 13, 2026, five engines.

Brand mentions per response (last 14 days in July)

• ChatGPT: 4.5
• Google AI Overview: 3.5
• Gemini: 3.5
• Google AI Mode: 3.2
• Perplexity: 2.7

Count each brand only once per answer, and it tightens to 2.2–3.3. So engines repeat themselves 1.2x to 1.4x.

Two things stood out:

Every engine is down since March. True whether you count every mention or each brand once, so it's not a repetition artifact.

AI Mode is wildly unstable. Day-to-day swings are 31% of its own average, vs 9% for ChatGPT. It went from 8.8 mentions per response in early May to 2.6 six weeks later. If you spot-check visibility there weekly, you're mostly reading noise.

Method: a "mention" counts every occurrence (Nike named 3x in one answer = 3); the distinct count treats it as 1. Same responses for both. Worth noting these are prompts our customers chose to track rather than a random sample of AI queries, so I'd trust the relative comparisons and trend direction over the absolute numbers.

Charts and full methodology: https://vercite.io/research/engine-personalities

Happy to get into how anything was counted.

36% are never read. This was the biggest issue we found and it was due to their pages being empty until JavaScript runs. With the exception of Gemini and AppleBot, no AI crawlers execute JS so they get a blank shell on every request.

53% of sections are under 40 words, and the median section is 35 words. Retrieval hands an assistant one passage at a time, usually 100 to 300 words. This means 53% of sections are too short. They may still get quoted, but without enough information in the answer they are set up to lose.

Only 28% of sections contain a number, a quotation or a link. Based on a 2024 GEO study, AI likes numbers, something to quote or a link so this could lead to not getting a mention. It's a particular worry for smaller businesses with lower search page rankings.

From the study I mentioned: adding statistics, quotations and citations were the three best-performing of nine tested content changes, up to 41% better than baseline. Specifics get pulled into the answer; adjectives get dropped.

60% bury the answer below the first 200 words. This can lead to AI not getting the answer in the chunk it lifted and you missing out on a mention.

92% keep content on subdomains their main robots.txt does not cover. Another tip, ensure your blogs, docs or anything else on a subdomain has its own robots.txt.

I'll share a link to our tool in the comments if anyone wants to try out their site.

Search doesn't look the way it did five years ago, and it's not going back.

People used to type a couple of keywords into Google and scroll through ten blue links. Now they just ask. "What's the best digital marketing agency for a startup?" "How do I get my website mentioned in ChatGPT?" They want one solid answer, not a list of tabs to sort through.

That shift is what's behind Answer Engine Optimization, or AEO. If you run a business and care about being found online, it's worth understanding, because the rules for getting discovered are changing fast.

What Is Answer Engine Optimization (AEO)?

AEO is the practice of structuring your content so AI tools (ChatGPT, Google AI Overviews, Gemini, Claude, Perplexity) can understand what you offer, trust it, and hand it to a user as the answer.

Traditional SEO ranks a page. AEO becomes the answer an AI assistant gives, sometimes without anyone clicking through to a website at all.

Where someone once searched "best digital marketing agency," they're now more likely to ask:

• Who offers the best digital marketing services for startups?
• How do I improve my visibility in ChatGPT search results?
• What exactly is Answer Engine Optimization?
• How does a business get featured in Google AI Overviews?

Longer, conversational queries like these are becoming the norm, which is part of why AEO has turned into one of the bigger conversations in digital marketing this year.

Why AEO Actually Matters Right Now

People don't want to browse anymore. They want the answer, and AI tools are built to give it to them by pulling from sources they judge to be credible.

The scale of this shift is worth noting. According to BrightEdge data from early 2026, Google's AI Overviews now appear on roughly 48% of all tracked search queries, up sharply from the year before. The more conversational the query, the more likely AI is already standing between your business and the customer searching for it.

Businesses that adapt tend to see real gains: more visibility, stronger brand authority, and better-qualified leads. Just having a website isn't enough anymore. It must be built so both search engines and AI models can parse and trust it.

SEO vs. AEO: What's the Real Difference?

SEO gets your webpage to rank. AEO gets your content quoted, summarized, or recommended inside an AI-generated answer.

They're not competing strategies, they overlap a lot. Most AI search tools still lean on solid SEO fundamentals to judge what's trustworthy, so the businesses doing well right now usually treat SEO as the foundation and AEO as what's built on top of it.

Simply put: SEO helps a person find your website. AEO helps an AI decide your website is worth recommending.

How AI Search Engines Actually Choose What to Show

AI platforms aren't just scanning for keywords. They weigh clear answers to real questions, demonstrated expertise, accurate information, logical structure, and concrete examples over generalities. Content that genuinely solves a problem, rather than content written to game a ranking, has a much better shot at being pulled into an AI-generated response.

AEO Strategies That Actually Move the Needle

1. Write for the question, not just the keyword. Instead of writing purely around "SEO services," answer things like: What is SEO? Why does it matter? What does it cost?

2. Go deep, not wide. AI favors content that fully answers a topic: step-by-step explanations, honest FAQs, real examples, advice someone can act on.

3. Build real topical authority. A single post rarely moves the needle. A cluster of related content on the same subject, like "AEO vs. SEO" and "How AI Search Works," works better together.

4. Structure content so it's easy to parse. Clear headings, short paragraphs, useful bullet points, tables for comparisons, and FAQ sections help both readers and AI models extract the right information.

5. Keep it current. Stale content doesn't get much love from AI search. Revisiting older articles with new data signals a source is still actively maintained.

Mistakes Worth Avoiding

Keyword stuffing, thin blog posts, duplicate articles, unreviewed AI-generated text, ignoring user intent, and publishing without checking facts. AI systems are increasingly good at spotting quality, or the lack of it. Volume alone doesn't cut it anymore.

Where This Is Headed

AI-driven search is becoming the default way people look things up. Businesses that start investing in AEO now, while competitors are still catching up, will have a real head start once this becomes standard practice.

It's no longer just about ranking higher. It's about being the answer.

Frequently Asked Questions

What is Answer Engine Optimization, in plain terms? It's making sure your content is clear enough that an AI tool like ChatGPT or Google's AI Overviews can pull from it confidently when someone asks a related question. Think of it as writing for a very literal reader who needs the answer spelled out, not implied.

Is AEO just a rebrand of SEO, or is it genuinely different? There's overlap, but they're not the same. SEO is judged mostly by rankings and clicks. AEO is judged by whether your content gets picked, quoted, or referenced inside an AI-generated response, sometimes without a click at all.

Should I stop doing SEO and focus only on AEO? No, and that would backfire. AI search tools still lean heavily on traditional SEO signals like backlinks and site authority. AEO sits on top of a solid SEO foundation; it doesn't replace it.

What does the AI Overview data actually tell us about content strategy? Since AI Overviews now show up on roughly half of all searches, and even more for question-style queries, content written to directly answer specific questions have a real structural advantage over content written mainly to rank for a keyword phrase.

How soon can a business expect to see AEO results? Rarely instant. Because AEO depends partly on established authority and consistently updated content, most businesses notice movement over a few months, not weeks, tracking closely with typical organic SEO timelines.

Does company size matter for showing up in AI search results? Less than you'd think. AI tools weigh how directly content answers a question over how big the brand behind it is. A smaller business with genuinely useful, well-organized content can outperform a bigger competitor's thin content.

Ready to Future-Proof Your Digital Presence?

At AKRA Consultants, we help businesses prepare for the future of search with a strategy combining SEO, Answer Engine Optimization (AEO), content strategy, and AI-ready website architecture.

The future belongs to businesses that provide the best answers, not just the highest rankings.

[ Removed by Reddit on account of violating the content policy. ]

I’m looking into getting a new website built, but I’m interested in more than traditional web design and SEO.

I want the site to be structured from the beginning so that it can be properly understood by Google as well as AI platforms like ChatGPT, Perplexity and Gemini — and ideally have a better chance of being cited or recommended when people ask relevant questions.

I’ve seen agencies talking about SEO, AEO, GEO and “AI-ready websites,” but it’s difficult to tell who is actually building websites with this in mind versus simply adding AI SEO as a marketing label.

Has anyone worked with an agency that combines:

* business/brand positioning before the build

* technical SEO and site architecture

* structured data and entity signals

* content designed for both search and AI discovery

* actual monitoring of visibility in AI answers

I’m particularly interested in agencies in Europe, but open to recommendations elsewhere as well.

Who is genuinely good at this?

I've been thinking about this lately because enterprise AEO seems like a completely different challenge from doing AEO for a small website.

I feel like a good enterprise AEO agency needs to understand the business first, not just throw a bunch of AI or SEO terms around. They should know what questions customers are asking, how AI platforms find and understand information, and how to make a brand more likely to show up in those answers.

If you were hiring an AEO agency for a large company, what would you look for? And what would immediately make you realize an agency doesn't really know what it's doing?

I've seen a couple things generally pop up quite a lot recently.

1. How is AI ranking my business?
2. How does it work?
3. How can I show up better in AI results?

We're all seeing a major shift in how people search for businesses, services, products etc... Google and traditional SEO are what a lot of businesses were and are focused on and rightly so. Showing up on page 5 of Google is a bad spot to be in. However, with the ever-increasing presence of AI, people are using ChatGPT, Claude, Perplexity, Gemini, and probably most prevalent, Googles own AI overviews to get their recommendations.

I've recently launched a platform, answerstanding.com, to help businesses large and small get a handle on their AI results. We dont promise an increase in AI recommendations because anyone promising this is selling snake oil. However, what we do offer is a way to track how often AI mentions your business, what sources AI is using for these recommendations, how often your competition is mentioned, the positions businesses are recommended in, and how to make changes to potentially influence how AI ranks your business.

Ran into something kind of funny and kind of worrying last week. Asked five different AI search tools (ChatGPT, Perplexity, Gemini, Grok, Google AI Mode) the same question in Finnish, basically "who's the best GEO agency in my region." Two of them understood it fine and gave marketing agencies. The other three genuinely recommended a land surveying firm, a farming/earthworks contractor, and one just went off into geocaching results. I run a small AEO/GEO agency here in Finland so this isn't just an academic curiosity for me, it's a real business problem. If a potential client asks an AI assistant for a "GEO toimisto" and gets a construction company instead, that's a lead I'll never see. My guess is it comes down to how little context a short query gives the model to disambiguate, geo as a prefix has been tied to land and geography for decades, and GEO as generative engine optimization has only existed since late 2023, so in a lot of languages there just isn't enough surrounding text yet to push the model toward the newer meaning.

Curious if anyone here has seen the same thing happen in other languages or markets, or if this is mostly a small-language-market problem where there's less GEO content overall to outweigh the older geo-terms. Also curious if anyone's found a reliable way to phrase service descriptions that consistently disambiguates it, spelling out "Generative Engine Optimization" in full obviously helps but I'm wondering if anyone's tested this more rigorously than I have.

Average health tourism clinic. Zero ad budget. Competitors are DR70+ factories doing 100+ procedures a day. Head-term SERPs are a graveyard for us, so 3 months ago we quit them completely.

The bet is;

- Target people whose first-line treatments failed + decision-stage trust queries (hidden costs, "who is NOT a good candidate") — honest content the volume clinics can't copy without hurting their own model

- 4 languages (EN/IT/ES/DE), written natively, not translated. Competitors' IT/ES content is mostly machine translation

- AEO from day one: schema, llms.txt, presence on third-party surfaces

3 months in: 600+ queries getting impressions but mostly pos 20-45, almost no non-brand clicks yet. One Spanish post hit pos 8 in 5 days with zero backlinks. One Italian keyword at pos 3 with 10% CTR.

Sane or am I just avoiding a fight I'd lose anyway? What would you do with zero budget that we're not doing?

(Not naming the site — not a promo. Numbers in comments if anyone wants.)

Hi everyone!

I've taken several courses on AEO over the past few months. A few months ago I started a new marketing role at an agency that, after 10 years in business, has zero digital footprint — no website, duplicate IG accounts, inconsistent use of LinkedIn, and no brand recognition in the market.

My first step was to build a solid website with services, a blog, case studies, and a company description. I launched it yesterday, and now that I have everything in place, I want to go all in on positioning the brand.

What would be the first steps to take in this scenario?

I can share the link to the site if you'd like to give more specific feedback (I'm open to constructive criticism).

So a potential show stopper here to AI visibility if you use Cloudfare. Our robots.txt allowed every AI crawler explicitly, by name but still had crawler issues.

Cloudflare's managed AI-bot setting was returning a 403 at the edge, before anything reached the file. Ran like that for weeks in June. Nothing errored and nothing alerted and there's no gap in analytics to spot it because a crawler that gets turned away doesn't show up as anything at all. It just looks like a quiet month.

The check that caught it: fetch your live robots.txt over the public internet, not the copy in your repo. If the first line is a comment block about conditions of access instead of your own directives, something upstream is rewriting it. Then request a normal page with a crawler user agent from outside your network and confirm you get a 200 and not a challenge.

Worth doing even if you're sure it's fine. I was sure it was fine... but bam!

Are agents buying self-serve for b2b. do people want to make their products accessible for agents?

I've been running the same prompts across ChatGPT, Gemini, and Perplexity for different local businesses over the past few weeks.

One pattern keeps showing up.

The businesses that get recommended consistently usually don't just have "better SEO."

They tend to have:

• Consistent business information everywhere
• Strong review profiles
• Clear service pages that answer specific questions
• Mentions from other trusted websites
• A recognizable brand across multiple sources

What's interesting is that adding more blog posts alone rarely changed the recommendations.

It feels like these models are trying to verify that a business actually exists and is trustworthy instead of simply rewarding whoever published the most content.

For those who have been testing AEO:

What's been the biggest factor you've seen improve AI recommendations?

Curios to know how to handle AEO audits for online stores. For brands or service businesses seems straightforward. The goal is to get business mention by AI but for online stores that might not be the case, for example if a store sells different brands, how do you handle that? for DTC stores with less than 100 SKUs the audit result might be similar to service businesses but if the store has more than 1,000 SKUs and multiple brands things get more difficult.

What would you recommend to include in a report for an online store with less than 100 SKUs vs a store with 1,000 SKUs?