SEO foundations for AEO
Use established SEO foundations—crawlability, speed, indexing, rankings, links, and topical authority—as the credibility base for answer-engine visibility.
40%
Best tweets about Answer Engine Optimization
50 Best Tweets About Answer Engine Optimization (2026)
Discover the best tweets about answer engine optimization, including AI answers, citations, content structure, visibility, measurement, and AEO strategy.
Evidence-based AEO strategy for earning visibility and citations in answer engines, with experiments, measurement, and practical methods.
- Creators
- 37
- Updated
Original Xholic analysis
What 50 top Answer Engine Optimization posts reveal
The conversation generally frames AEO as an extension of SEO rather than a replacement: maintain accessible, evidence-rich content; develop credible off-site presence; and measure prompt-level visibility by engine. Frequently proposed tactics include reverse-engineering cited sources and addressing answer gaps. Posts also caution against scaling one page per fan-out query, assuming a universal playbook, or using citations as the only success metric.
- Dominant tone
- Positive
- Median score
- 10.1
- Leading format
- Opinion
- Recent posts
- 46%
46% of posts
All-time engagement
34% of posts
Published in 90 days
Conversation map
The themes creators return to
Extractable answer content
Create concise, standalone, answer-first sections using clear headings, Q&A, definitions, lists, tables, schema, and machine-readable information that models can extract and cite.
38%
Third-party brand distribution
Earn off-site brand presence in reviews, listicles, comparison pages, editorial coverage, forums, newsletters, podcasts, YouTube, LinkedIn, and other third-party sources.
36%
AEO measurement and monitoring
Track AI mentions, citations, source sets, prompt coverage, referrals, sentiment, and engine-specific behavior rather than relying on organic rankings or clicks alone.
34%
Original evidence and trust
Build differentiated, factual content through first-hand experience, original research, proprietary data, balanced analysis, expertise signals, and fresh updates.
24%
Citation and query reverse engineering
Reverse-engineer cited sources, AI answer sections, SERP gaps, fan-out queries, and competitor formats to identify content opportunities and improve existing pages.
16%
Community visibility
Use Reddit and other communities for helpful participation, brand discussion, reputation, and source visibility in AI-generated answers.
16%
Entity salience and topical focus
Build clear category association, consistent brand entities, focused topical coverage, and product knowledge that answer engines can understand and recommend.
8%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 27
- Median reposts
- 3
- Median replies
- 6
- Median views
- 2K
Posts with media make up 54% of this collection. Their median all-time score is 14.5, compared with 3.13 for text-only posts.
Format mix
- Opinion 34% · score 2.62
- Case Study 20% · score 6.89
- List 16% · score 14.7
- Tutorial 16% · score 56.5
Consensus and debate
Where creators agree, and where they do not
Shared view
AEO builds on technical SEO
A recurring approach is to retain crawlability, indexing and other SEO fundamentals, then add machine-readable product or content data and concise sections that can stand alone as answers.
Shared view
Make answers easy to extract
Posts and shared research highlight clear definitions, examples, Q&A, tables, structured sections, evidence, expertise signals and non-promotional presentation as patterns associated with extractable or cited content.
Shared view
Distribution extends beyond the site
Visibility is discussed as both on-site and off-site. Reddit, YouTube, reviews, newsletters, editorial sources and other third-party surfaces are presented as relevant places for brand discovery or citation.
Shared view
Track prompts, sources and engines
The posts recommend monitoring target prompts, fan-out queries, citations and source sets. One cited analysis also distinguishes sources an engine considered from those it ultimately cited.
Open debate
How predictive are organic rankings?
Posts agree that SEO remains relevant, but differ on how tightly organic ranking predicts AI visibility. One frames SEO as credibility infrastructure, while an experiment and cited research describe citation outcomes beyond Google’s top results.
Open debate
Optimization tactics versus fundamentals
One post advocates optimizing several extractable answer chunks. Others emphasize accessible, straightforward data and caution that no universal GEO playbook applies across brands or models.
Open debate
Citation acquisition’s business value
Some posts advocate competitor comparisons and outreach to pages already cited by AI tools; one outreach post says paid placement may be necessary. Another post reports that, across its client set, citations showed little measurable impact compared with bottom-funnel mentions.
What performs
Patterns behind standout posts
High-engagement posts span practical AEO topics
The five supplied engagement outliers cover Reddit/community strategy, extractable on-page chunks, fan-out analysis, an SEO-to-AI framework and platform AEO guidance. Their all-time scores range from 97.61 to 281.12.
Leading outliers include actionable workflows
Three leading outliers present concrete methods: a community-strategy introduction, a step-by-step on-page workflow, and a fan-out-query clustering workflow. This is a useful editorial pattern to test, not proof that format itself caused engagement.
Research provides testable inputs
Research-led posts provide testable inputs, including reported relationships between structure, tables, Q&A, evidence and citations, as well as platform-specific citation patterns.
Statistical standouts
- View standout post 1 Score 281.1 · 27.81× median
- View standout post 2 Score 167.6 · 16.58× median
- View standout post 3 Score 131.6 · 13.02× median
- View standout post 4 Score 123.9 · 12.25× median
- View standout post 5 Score 97.6 · 9.66× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 20% of the selected posts.
-
1. Aleyda Solis 🕊️
@aleyda
2 posts
-
2. Okara
@askOkara
2 posts
-
3. Cody Schneider
@codyschneider
2 posts
-
4. Glenn Gabe
@glenngabe
2 posts
-
5. ILIAS ISM
@illyism
2 posts
-
6. Jake Ward
@jakezward
2 posts
Aleyda covers structured commercial content
Aleyda Solis’ two posts cover platform guidance on machine-readable catalogs, intent and trust, and shared research on data-grounded, scannable commercial content.
Okara offers an execution checklist
Okara’s posts present an execution checklist spanning technical accessibility, first-hand evidence, comparisons, third-party mentions, prompt review and recurring citation checks.
Jake Ward broadens the visibility lens
Jake Ward places AEO within a broader “search everywhere” model and argues that AI-answer visibility may require measurement beyond direct traffic.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Answer Engine Optimization tweets
Top Answer Engine Optimization tweets from 37 creators
Ranked 01–50
- 01
- 02
@Charles_SEO ·
We're now being cited in Google AI Overviews for core SEO terms.. right next to Moz and SEMRush 👀 No links, no authority play, just clever old school NLP SEO re-tuned for the new AI search interface... Here is the STEP-BY-STEP play: 1 - Reverse engineer SERP gaps; Your site needs to be able to rank in the traditional algo first, so pages where you are already in the top 100 are a must and the higher the start, the better the result. 2 - Identify the gaps between what THEY cover and what the AI Overview is trying to answer. 3 - Write a section on YOUR page that fills that exact gap, formatted clearly with a definition, example, or list that Google can easily extract as a standalone chunk. I added several more anchor text types using this exact method, "generic" wasn't the only one I targeted here. 4 - Make sure that chunk can stand alone as a complete answer to a sub-question within the broader topic. That's it! You're not competing for the whole page, you're competing for ONE chunk of the AI Overview. It's very similar to how we used to optimize for featured snippets, but with a lot more dynamic inputs required - It's usually not the one H2 anymore, you need to optimize (at least) several chunks to have the best chance of getting visibility. In this case, we were cited for the definition because our page had the clearest, most concise explanation with a practical example - Something our competitors either buried in paragraphs or didn't isolate properly. Unfortunately, we usually don't get to directly "win" a #1 spot anymore in these new SERPs, BUT the upside is you can now get visibility for queries your page would NEVER have ranked #1 for traditionally.. and you can get cited MULTIPLE times across the same AI Overview if you optimize several chunks well. Less clicks, more visibility and "brand awareness" - A lot of corporate marketers would actually prefer this anyway.... And this all rewards going broader and deeper on your pages. The more well structured, extractable chunks you have, the more chances you give Google to pull from you. The traditional algo is linear, this new search is much more dynamic, less ranking, more retrieval.
- 03
@lilyraynyc ·
One of the quickest and easiest AI search workflows (after setting up prompt tracking) is to export all fan-out queries and cluster them into core topics for analysis and content mapping. Trying to optimize for individual fan-out queries is not a great use of time, and building one page per fan-out will likely lead to SEO spam problems down the line. (Reminds me of popular pre-Helpful Content Update tactics 😅) But analyzing query fan-outs *at scale,* clustering them into core topics, and identifying the key trends among them is one of the best places to start with AEO/GEO, in my opinion. (Assuming you’re tracking a comprehensive set of prompts!) The output is a matrix similar to the keyword research matrices we’ve built for SEO for years, and it lets you compare your existing content portfolio to the key questions language models ask when researching your brand, products, and services. That said, I still believe SEO tools that use *actual search volumes* (not highly estimated / made-up “prompt volumes”) should stay part of this process. I just did this for a client in 5 minutes using @peec_ai, which allows for a quick export of all fan-out queries (as do several other LLM trackers). Then I uploaded the list into Claude for clustering. Another bonus is that you can see how fan-outs differ by language model. I see this as a new layer on top of our existing keyword and topic research. It gives us a window into how LLMs actually break down and research a topic, a signal we didn’t have access to before, and it provides deeper insights than what we can gather with traditional keyword research tools.
- 04
@jakezward ·
"I don't know how to do SEO in 2026" Start from level 1 in The New SEO Game: SEO isn't just Google rankings anymore. It's now "Search Everywhere Optimisation". Reframe your “New SEO” project as a game, and you'll become addicted to levelling up. Level 1: Traditional SEO - Fix technical problems killing your rankings - Research keywords and target quick wins - Optimise on-page elements (titles, content) - Earn quality backlinks through outreach and PR Level 2: AI Search Optimisation - Format content so AI can parse it easily - Build pages that AI platforms want to cite - Structure information for machine consumption - Test how your brand appears in AI search results Level 3: Paid Search Visibility - Run Google Ads for high-intent keywords - Target competitor terms with YouTube Search Ads - Capture Bing traffic through Microsoft Ads - Measure paid performance across every platform Level 4: LLM Answer SEO - Produce authoritative content LLMs trust - Build a knowledge base for AI training data - Position your brand as the definitive source - Monitor brand mentions in LLMs with Mentions .so Level 5: Brand Authority SEO - Get unlinked brand mentions across the web - Feature in industry roundups and expert lists - Build brand recognition without traditional backlinks - Track brand mention volume and sentiment Level 6: Community SEO - Provide value in relevant Reddit threads - Share expertise on Quora in your space - Engage in Slack communities and Discord servers - Build reputation in industry forums and groups Level 7: Parasite SEO - Repurpose content on Medium and LinkedIn Pulse - Publish beehiiv newsletters to rank in Google - Guest post on high-authority platforms/websites - Leverage existing domain authority for quick rankings Level 8: Platform-Specific SEO - Optimise for Amazon search if selling products - Focus on YouTube SEO for video content - Master TikTok's algorithm for short-form content - Optimise App Store listings for apps/extensions Level 9: Topic Domination - Own conversations across ALL channels - Create content ecosystems to reinforce each platform - Become the go-to expert mentioned everywhere - Monitor and maintain authority across all channels Completed all levels? SEO is constantly evolving going into 2026. Stay ahead or get left behind.
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- 05
@aleyda ·
🚨 @MSAdvertising has published a must-read guide about AEO/GEO with practical data to optimize retailers presence in AI search, AI assistants and AI browsers, going through: 1. How traditional SEO focused on clicks and now Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) determine visibility in LLM-powered ecosystems. 2. How products surface in conversational and generative ranking 3. How competition is shifting from discovery to influence (SEO to AEO/GEO) 4. A break down of how AEO and GEO apply when a user interacts with an AI assistant, browser or agent. 5. Actionable recommendations: --- Data structure: Make your catalog machine-readable --- Content enrichment: Design for intent and context --- Trust signals: Establish authority and credibility The most actionable guidance by an AI platform so far 🔥 Check it out: https://t.co/bYLUKCjcyE /HT @Kevin_Indig
- 06
- 07
@SEOKeval ·
Here's the easiest way to generate more revenue from SEO in just a few months: Make a list of your top competitors. Publish blog content targeting these keyword variations: > [COMPETITOR BRAND] alternative > [YOUR BRAND] vs [COMPETITOR BRAND] > [COMPETITOR BRAND] vs [COMPETITOR BRAND] For the first two keyword variations, position your brand as the best option to purchase from. For the third variation, fairly compare the two competitor brands, but then suggest your brand as a better alternative to both. Add CTA's through each blog post promoting relevant Products. Build a few backlinks to each blog post. Once they rank, sales will start rolling in because these are very high purchase-intent keywords. You'll also start getting mentions in Google AI Overviews and other AI models because AI models LOVE to cite this kind of of content. I run this strategy for every brand that let's me. And it prints every time.
- 08
@illyism ·
just got off a SEO consulting call with a founder who built a crazy cool product but that nobody knows about yet 🤙 SEO is awesome at demand capture, but not at demand generation so here is the exact playbook we mapped out: 👇 how to do seo for a product nobody searches for: 1. write a "top 20 best <category>" listicle for your niche 2. put your product at #1 3. include 19 other non-competing indie products 4. email those 19 founders: "i just featured you, can you include us in your listicles?" boom 💥 free, highly relevant backlinks from real businesses 👍 bonus insight: find the exact articles that chatgpt cites for your target keywords (press on "Sources" in the bottom), email those specific authors to get added to their existing posts stop fighting for impossible keywords, build alliances instead! 🙌
- 09
@codyschneider ·
stop overcomplicating this AI search is just SEO these are the only levers you can pull to actually move the needle 1. publish articles for bottom of funnel keywords and go to page 1 - 3 to get referral traffic find best x for y, x alternative, tools like x, better than x, apps like x scrape what is ranking page one currently define the product differentiation of your product versus what you just scraped write a blog post that includes your product and how it is different who it is for publish that article make sure it gets added to your site map for indexing pro tips - if you have a ton of posts on the site, on the sitemap have 100 pages per sitemap URL this will make indexing faster - make the page load extremely fast due to being extremely small and you'll get more crawl budget. ) 2. Get mentioned on citations that are already ranking for those same keywords, find the citations that are being used by AI search platforms se something like prompt watch to identify this export all the citations, then find the email addresses of the site owner or the individual article writer use instantly AI to cold email them asking to be included in the citation, you're probably going to have to pay to get this placement pro tip: - not all citations are created equal. If you map all the citations within your category, you're going to find that certain links get cited more often than others. So you can rank stack the citations by priority and this means that it is ok to potentially pay more for those citations because it will create a higher impact faster
- 10
@askOkara ·
"GeO iS EaSY" GEO: > add internal links > build topical authority > update outdated stats > publish original research > quote reputable sources > add screenshots and demos > add direct answers at the top > make sure js content is crawlable > get mentioned on reddit, g2, youtube > update dateModified when you make changes > build how to, best tool for x, comparison pages > check that your cdn/waf isn't blocking crawlers > allow oai-searchbot, perplexitybot and googlebot > keep your founder profiles and brand description consistent > type prompts your icp types into chatgpt, claude and google > open the cited pages and study the exact section the answer came from > find what those pages are missing, then add something more useful > recheck rankings and citations every month because they change constantly
- 11
@askOkara ·
how to get mentioned by chatgpt in 2026: > nail seo fundamentals (crawlable, fast, simple html) > run a full seo + geo audit with okara ai cmo > share first-hand experience (experiments, case studies) > publish best and comparison pages > get cited by reputed sources in your niche > appear in listicles where competitors are listed > get featured in youtube videos > reply to relevant reddit threads > collaborate with youtube creators > write for prompts your icp types into llms > keep content fresh and updated
- 12
@SEOKeval ·
SEO may be the most important marketing channel out there right now. Why? Because it's a prerequisite to appearing in AI models. Good traditional SEO gets you 50–60% of the way toward appearing in AI models. And the other 40-50% is just an extension of SEO: > It's publishing "best X" listicles, featuring your product at the top, on relevant, high-authority 3rd party websites. > It's finding relevant Reddit and Quora threads, and mentioning your brand in the replies. The goal is to "seed" your brand around the web, so when AI models pick up those references, they cite you for relevant prompts. In other words, you're doing parasite SEO. It's nothing mind-blowing. It's also nothing new. It's just an extension of what we've always been doing in SEO.
- 13
@aleyda ·
💰 From Retrieved to Cited: How Commercial Content Earns Citations in AI Search - excellent research from @_oshdavidson showing how: * Early-Discovery Content Earns a 20% Higher Citation Likelihood When Claims Are Grounded in Data * Pages That Make Shortlisting Options Scannable Earn 18.8% More Citations * Comparison Content With Tables Earns 25.7% More Citations * Validation Pages With Organized Lists Earn Up to 27% More Citations * What This Means for Content and SEO Teams A must read: https://t.co/6wBmI2w2r9
- 14
@glenngabe ·
Cool post from @dejanseo -> How AI Search Grounding Actually Works: Google vs OpenAI vs Anthropic "For Google, the funnel barely narrows: 7 received, 7 cited. This is the defining trait of Google’s grounding — it doesn’t expose pages it didn’t use." "OpenAI’s wide-receive / narrow-cite split is a visibility trap. Being one of the 37 pages OpenAI read is very different from being one of the 2 it cited. Both are worth tracking, but they’re not the same win." "Anthropic gives the richest “considered set” (cited + rejected) but hides the snippet text, so reconstructing what it actually read costs a second pass — and real time and tokens." https://t.co/ZaKM3N8bqM
- 15
@foley_seo ·
A lot of SEOs & SEO agencies are going to have had clients asking why organic performance has declined. So, client education is key. In this example a client came for an SEO audit because clicks were dropping off, they exhibited concerns about their current SEO agencies ability to deliver, but when you look at the right hand image you can see categorically POSITIVE movement from the SEO. I explained to the client over a loom video about their exposure to "INFORMATIONAL" queries which was where a majority of clicks had been lost to and explained that the agency hadn't done anything wrong. But, this is a REAL issue. Google lied - Liz Reid VP and head of google search said: “We’ve found that with AI Overviews, people use Search more, and are more satisfied with their results” and that “the links included in AI Overviews get more clicks than if the page had appeared as a traditional web listing. But she knew this was a lie. 25+ years people who use search engines click on links to get their answers / wants / needs. So when you launch something that answers questions IN SEARCH that is 1000% NOT going to increase clicks, its going to decrease clicks. The ISSUE here is two-fold, but the main one being: IF you train your LLM on peoples content and then resummarise peoples content but you don't give them the click you take away the EXCHANGE OF VALUE. Google + Publishers have had a relatively stable relationship over time - EXCHANGE of value looked like this: 🌟 10 years ago: 🩷 Google crawled roughly 2 pages for every 1 visitor it sent to publishers 🤮 Six months ago: Google’s crawl-to-click ratio rose to 6 : 1. OpenAI's crawl-to-click hit 1,500 : 1. Anthropic’s was a staggering 60,000 : 1 🤢 Today (as of July 2025): Google: 18 : 1 OpenAI: 1,500 : 1 Anthropic: 60,000 : 1 Do you see what's happening here? SEO thrived on the production of informational content. For many shit agencies it was an easy route for deliverables and irrelevant vanity traffic growth. For good agencies it provided an opportunity to reach people in different stages of their "CONSIDERATION" phases. But when you errode the benefit what then? So - the ADOPTION MODEL for SEO is and will continue to change: 1. You need to work HARDER for clicks 2. You need to work HARDER on conversion - make each click of greater opportunity to convert 3. DO NOT produce content for the sake of it - produce it to REALLY solve a problem, strike a cord, influence a decision and distribute it FURTHER than just uploading it as a page on your site SEO is still TOTALLY viable, but, it just got harder. In a way, it will drive a gap between THOSE who CAN do a good job and those who capitalise on people who don't understand SEO but want it (sheisters). Let me make this clear - Google OWES publishers I'm not anti-Google but I am anti what they are doing Google should ABOLISH AIOS and allow 2 models of search 1. Traditional Search 2. AI Mode conversational search
- 16
@codyschneider ·
AI search 101 for b2b saas find keywords people search for your brand find citations that currently come up for those searches using something like prompt watch api then use agent for find owner of site or author cold email asking for brand mention placement on page you'll probably have to pay, give me kicker with affiliate commission show up in chat quickly since citations are already being referenced
- 17
@jakezward ·
I analysed 66,796 sites to understand where their SEO traffic came from last month. (You can too at chatgpt-vs-google .com) Google still dominates at 40.31%. ChatGPT is just 0.24%. But here's what most people miss: Traffic isn't the ONLY metric that matters anymore. Zero-click searches are everywhere now. ChatGPT processes 2.5 billion prompts every day, but barely any of them send direct traffic. AI Overviews now appear in 60% of U.S. searches. And position 1 CTR dropped by -34.5% when AI Overviews appear. People aren't clicking through like they used to. They're getting answers directly from AI, and that creates a massive blind spot. Your brand could be mentioned 10,000 times in ChatGPT responses. Your product could be recommended in Claude conversations. Your company could appear in Google AI Mode answers. None of that shows up in your traffic data. That's why I've been building Mentions for the past few months. I needed a way to track this visibility. Because the future of SEO isn't just ranking on Google. It's being visible wherever people ask questions.
- 18
@semrush ·
67% of URLs featured in AI Overviews also rank in Google’s top 10 organic results – reinforcing that SEO remains essential. But for AI to use your content, it needs to understand it, trust it, and easily incorporate it into answers. The difference between being featured or overlooked usually comes down to three factors: 1. Structure 2. Freshness 3. How easy your content is to cite Here are 7 steps to try today ⬇️ https://t.co/Xkk316hqJa.
- 19
@Hartdrawss ·
We just built a full AEO pipeline for a US family office. To simply explain; AEO = Answer Engine Optimisation. Instead of ranking on Google, the goal is to get cited inside ChatGPT, Perplexity, Claude and Gemini. Here’s the system we built: - Discovery Layer: Pulled quick-win keywords from Google Search Console (positions 5–20), cross-checked with Keyword Planner, then used Exa + AI to find real questions people are asking AI tools that traditional SEO completely misses - Content Layer: Competitor analysis to find angles others missed → structured briefs → articles written with ICP context + specially formatted Q&A blocks designed for how LLMs cite information → strict 6-dimension quality scoring before publishing. - Indexing Layer: Daily automated publishing with instant cache revalidation so new content is immediately visible to crawlers. - Tracking Layer: Daily GSC sync + dashboard that flags when keywords move, stall, or drop. This is the new SEO. Most agencies are still selling backlinks. What do you think though. is AEO already changing how you think about content?
- 20
@neilpatel ·
Teams are treating GEO as a replacement for SEO. It isn't. It's a second layer on top of it. AI Overviews and other AI search interfaces pull from web content. They favor sources with strong domain authority, consistent publishing histories, and deep backlink profiles. Everything traditional SEO built. Teams that gutted their SEO budgets to go all in on GEO are showing up to AI search with nothing for LLMs to trust. SEO spent years building the credibility foundation that GEO now borrows against. The two layers do different jobs. SEO earns you the domain authority and backlink profile LLMs use to evaluate whether a source is worth citing. GEO shapes how your content answers questions, so when an LLM reaches for a source, yours fits the answer pattern. A brand with strong GEO but weak domain authority won't get cited. A brand with strong domain authority and no attention to answer-formatted content will get bypassed by a newer player who understood the game earlier. The channel changed. The credibility infrastructure underneath it didn't.
- 21
@brodieseo ·
Ecommerce SEO: when it comes to ranking within free listing results on Google, there is a sphere of influence for data sources. This relates to features such as product grids, product knowledge panels, within the Shopping tab, AI Mode and more. In general, the influential data sources include: 1. Website Content 2. Product Feeds data (from Merchant Center Next) 3. Structured Data (based on schema .org, with merchant listing validation) While each of these data sources play their role with the information that appears within free listings, there are certainly caveats to the ordering of each data source. For instance, the information provided via Merchant Center for the title of a free listing result comes directly from GMC Next. The product title from the page content or within the Structured Data will not influence the appearance of this information in search results. But when it comes to something like the price of a product, if there are discrepancies across the website content, within the product feed, along with the structured data, Google will override all the external layers and default to the price shown within the website content. And often when there is a mismatch between the feed and the website, a notice will appear in GMC Next that will alert you to exclusion of the product from being delivered within free listings. This is where the new Merchant API should operate better than the Content API (especially for price mistmatches). The free listings space is going through a lot of changes in general right now. A major reason for the migration from Google's end to the upgraded Merchant Centre 'Next' edition of GMC is to allow product discoverability to be less reliant on feeds, with there being the ability to surface products from a website that may sit outside of the feed itself. This is then combined with recent discussions within a Search Off The Record podcast from Google – stating that Google may look to unify the approach among Structured Data and GMC Next feeds, which could be a drastic change to how we approach eCommerce SEO. In general, the best approach is to provide as much rich content to Google across each surface (content, feeds and structured data) and for there to be consistency among the surfaces for best results. This can be quite a complex area of eCommerce SEO to get your head around, but it is only becoming more important as the year progresses.
- 22
@om_patel5 ·
THIS SMALL LANDING PAGE CHANGE BOOSTED MY CONVERSION RATE BY 80% i added ONE section at the bottom of my landing page it lets visitors ask ANY AI (chatgpt, claude, gemini) what it thinks about my product right there on the page before they buy they click on any of the options and it redirects them to the AI with a prompt already loaded asking "is this product worth it" they get an instant honest answer with pros and cons pulled from real sources here's why this works so well: these AI models don't make stuff up about your product they pull from real indexed sources like reddit posts, medium articles, product reviews, and SEO content to form their answer so when a potential customer asks the AI and it comes back with a genuine positive response backed by real sources, that's more convincing than any testimonial or sales copy you could ever write you're not telling them your product is good. a third party AI that most people trust nowadays is telling them based on real data from the internet 80% of people who clicked the AI response buttons actually converted based on the data i've tracked the key though is that for the AI to say good things about your product, your product needs to actually exist on the internet first > post about it on reddit a few times across a few subreddits so it gets indexed > write about it on medium > get it reviewed or mentioned somewhere real (could be a paid partnership) > build GSEO and SEO presence so the AI has real content to pull from it's pretty easy. just a post a day for the next 7 days. indexing happens fast once that's in place the AI responses basically sell your product for you 24/7 without you doing anything you can build this section in 10 minutes with claude code or codex. simple embed that redirects users to an AI with your product prompt already loaded every startup landing page should have this. it's free social proof that never sleeps
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- 23
@gaetano_nyc ·
Most people don't know that ChatGPT defaults to branded search in its query fan outs. It uses its own training data to determine which brands are best associated with a category level search. I am going to produce a larger write-up based on what I am seeing for B2B SaaS. TLDR: The brands with the strongest category entity salience are winning in AI search. The takeaway is to build entity association with your desired flagship category and don't spread the water too thin across too many seeds. Topical drift is now a real problem if you want to be successful in GEO/AEO. Topical drift was not a massive problem for traditional SEO. We saw Patrick Stox rank some ridiculous pages like "purple laser pointers" to prove a point about topical authority being overrated. But for GEO/AEO topical drift is a problem that will hinder your success.
- 24
@shivsakhuja ·
Today we're launching goose-aeo, an open-source CLI + skill built for AI agents like Claude & OpenClaw to check your brand's visibility on answer engines. It's really easy to use: 1️⃣ npx goose-skills install aeo --claude 2️⃣ claude 3️⃣ /aeo It will: 1. ask you some questions to understand your brand and competitors. 2. generate queries for answer engines and a cost estimate 3. run the queries across all engines (ChatGPT, Claude, Perplexity, Grok and Gemini), analyze the responses and present a report 4. audit your site for LLM visibility 5. make recommendations about things to do to improve your visibility You can chat with Claude or view the results in a dashboard. It's 100% free, and open-source. BYOK. We believe AI agents will run GTM for most companies in the future. To do this, they need tools built natively for AI. We hope goose-aeo is a step towards that future.
- 25
@neilpatel ·
NP Digital ran 4,300 prompts across 500 commercial keywords. Here's what we found: 75% of AI citations pull from sources outside Google's top 10. Rank #1 still only gives you a 31% shot at appearing in AI answers. You now have two scores that matter. Most brands are only tracking one. #SEO #AIMarketing #GoogleSearch #AISearch
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@semrush ·
AI search platforms like ChatGPT, Google AI Mode, and Perplexity are changing how content gets discovered. But what makes one piece of content get cited while another gets ignored? To answer this, we analyzed thousands of citations and compared them to similar pages ranking in Google. Our goal was to identify which text-only qualities most strongly correlate with AI citation behavior, and whether these patterns differ from traditional SEO signals. Based on our research, we found five content qualities that showed a strong positive correlation with AI citations, plus one that showed a negative correlation: • Clarity and summarization: +32.83% • EEAT signals: +30.64% • Q&A format: +25.45% • Section structure: +22.91% • Structured data elements: +21.60% • Non-promotional tone: -26.19% In short: content that delivers clear answers, demonstrates expertise, and uses structured formatting is more likely to be cited. Full breakdown: https://t.co/ozzQjFU0hw.
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@aaina_narang ·
here's how you can optimize GEO for 10x results: - write content that answers specific questions your ICP is asking - use original data and real numbers, AI cites sources it can verify - build topical authority around one core use case before expanding - get your brand mentioned in newsletters, Substacks, and publications your ICP reads - structure content so AI can extract a clean, quotable answer from it - add proper schema markup and structured data to your site - earn backlinks from trusted sources in your category - get cited in Reddit threads, Slack communities, and forums your buyers are active in - track where you appear in AI answers, not just Google rankings
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@TheCoolestCool ·
Most AEO/GEO marketers spend 90% of their time thinking about things they can do on their own site. The smartest marketers are recognizing that third party citations DOMINATE the LLMs and more than ever before they need to be elsewhere. It's not just about your blog. It's about review sites, podcasts, category sites, niche newsletters, competitors content, alternative pages, Reddit, LinkedIn, YouTube and more.
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@arvidkahl ·
Customer just sent me this. So I'm not doing any active GEO or AEO, but it looks like the big players have picked up Podscan. Confluence of any number of these things, I presume: - podcast data samples publicly available and in the sitemap - thorough MCP implementation - agentic-centered landing pages You could argue that it is GEO or AEO, but I consider it just being straightforward with presenting the available data and its accessibility to those I know will ultimately make the implementation (Claude code) or a value judgment on the data (the person using Claude and asking Claude a question).
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@hdxswx ·
The 5 biggest myths about AI search optimization (and what actually works) I've analyzed millions of AI citations across ChatGPT, Perplexity, and Google AI Overviews. Most of what you hear about AI search is either hype or just wrong. Here are the biggest myths I keep seeing: Myth 1: "AEO is completely different from SEO" The truth is more nuanced. AEO builds on SEO fundamentals, but it's not just rebranded SEO. Success is measured by mentions instead of clicks. LLMs break down queries into multiple parallel searches. Responses are highly personalized and probabilistic. (more on this in a separate post) Myth 2: "Flood the internet with AI content" This will destroy you. Mass AI content triggers algorithm penalties, tanks your credibility, and makes you invisible everywhere. AI platforms cite authoritative sources. Spam doesn't scale sustainably. Myth 3: "Optimize for exact AI prompts" AI prompts are personalized and constantly changing. Chasing individual prompts is whack-a-mole. What works: Build topical authority around core themes. Myth 4: "Create separate content for AI vs. humans" Don't write for bots. Don't create scaled-down AI versions. The best content serves both by being clear, authoritative, and well-structured. Myth 5: "llms.txt is the secret" Lumen's data: Millions of citations tracked. Zero llms.txt references. It sounds technical, so it sells well. But there's no evidence it works If your AEO strategy sounds easy, scalable, and fully automated, it’s probably wrong. What is the craziest AEO take you have come across in the wild?
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@tiboel ·
One question I get more and more from people outside tech is: “How should we optimize our brand for LLMs?” The honest answer is: nobody really knows yet. Just like SEO, there won’t be a single GEO playbook. Every brand, every product and every model will be different. Here is what I currently believe: Just like SEO, start by creating unique, detailed, factual content about your products. Write to educate your customers first. GEO is unlikely to reward generic, AI-generated content. A common mistake is to build an FAQ around the questions you think people will ask ChatGPT. That’s probably too simplistic. LLMs don’t just retrieve answers—they build an understanding of your company from all the signals you provide. Use LLMs to optimize for LLMs. They are probably the best tools to tell you what information is missing, what is ambiguous, and how your content could be structured to be better understood by AI. Give LLMs a user manual. Don’t assume they’ll figure everything out. Explain how your site is organized, where the authoritative information lives, how products relate to each other, and how your content should be interpreted. Make your site easy for both humans and AI to navigate. Google spent 25 years building PageRank and link authority. LLMs don’t have an equivalent map of the web. Instead, they seem to rely on explicit signals of authority: trusted communities, social platforms, directories, expert content, documentation, and other well-established sources. Measure your GEO. Ask customers where they discovered you, monitor AI referrals, and use the new generation of GEO tracking tools as they emerge. This is just the beginning. The rules will change quickly as LLMs evolve and, more importantly, as they figure out how to monetize discovery. My guess is that LLM monetization will look much closer to Google’s SEO/SEM model than most people expect. If that’s true, improving your organic GEO today will likely reduce what you’ll have to pay tomorrow. Curious to hear what others are seeing. What would you add?
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@BradfordHuber4 ·
Why does it feel like every major company is jumping on the AEO bandwagon? Just this week we've had: Hubspot just released Hubspot AEO Webflow just announced Webflow AEO Agents Then you've got the SEO incumbents (Semrush, Ahrefs, etc) who've all spun up their own AEO thing. On top of that there's like 100 other AEO specific tools that have already been created and launched. My main gripe is it feels like all the marketing out there is selling these tools like the next greatest thing for marketers that will change the game. I currently pay for an AEO tool, and it's useful, but I don't see it as this game changing thing. The actual work to improve in AEO is still very similar to SEO, and getting reporting in place isn't going to suddenly give you the secret sauce to win in AEO. There's still tons of work to be done beyond that. We still don't have a reliable source of actual prompt volume either. Right now it feels like every company is trying to jump into AEO, and tbh I'm getting tired of all the hype
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@BritneyMuller ·
🔥 AI-Proof Your 2026 Marketing [The Orange Labs Checklist] Stop letting AI strip your content for zero-click answers. In 2026, you’re either the source or you’re the free training data. Use AI for the heavy lifting (vector embeddings, internal linking, briefs), but build an entity moat. If they can't replicate your content/data, they're more likely to cite you by name. 1. Optimize for "Answer-First" Design ☐ Lead with a TL;DR: Summaries at the top of every page. ☐ Be Objective: Swap "We are the best" for "Product X offers 20% more storage than Y." ☐ Structure: Use clear topical sections and relevant FAQs. ☐ Edit: Omit needless words. 2. Infiltrate the Training Data Go where the conversations happen! (Hint: Use SparkToro to find them). ☐ Listen First: Spend time adding value before you ask for anything. ☐ Don't fear the "Reddit bros": Let them critique your work. It creates the engagement signals AI models crave. (Google "BERT 101" to see how I've leveraged this). ☐ Pivot Fast: After 3 months, double down on the 2–3 platforms showing real traction. 3. Technical Edge & On-Site Wins ☐ Vector Embeddings: Use them to find topical gaps your competitors missed. ☐ Automated Internal Linking: (Check Everett Sizemore’s Moz post for the blueprint). ☐ Strategic Content Briefs: Leverage real-time SERP analysis to build data-driven briefs in minutes. Pro Tip: Use WordCrafter if you don’t want to build this infrastructure yourself. ☐ Original Data: Use HTML comparison tables (not images) so AI can parse your data. ☐ Real-Time Sentiment: Use the Reddit API to surface trending desires, brand critiques, and product gaps. 4. Lean Into Your "Human" Advantage AI has ZERO real-world awareness, no friends & no hot takes. ☐ Verification: Use real bios, real photos, and real-world opinions. ☐ Be a Contrarian!: If 10 sites say a product is "perfect," be the 11th site with a nuanced, reasoned critique. AI (especially within Google) has an incentive to surface "balanced" answers, be that source. ☐ Personality: Inject humor, hot takes, personality, unique writing, and stories. —AI is soulless & people are growing tired of AI slop. "Here piggy piggy," said no qualified Marketer ever. 5. Name Your Data! Build an Entity Moat! ☐ Own the Entity (Be the Source): Don’t just say "we tested this". Create the "[Brand] Index" or the "[Brand] Score." —When you name a proprietary metric, AI is forced to cite your specific brand name because it's a unique entity! 🎯 Goal: Bake your entity into more relevant benchmarks, papers, sites, convos, datasets, etc. 6. The "Turkey Sandwich" Rule Distribution is 80% of the battle. ☐ Promote > Publish: "Your big content piece is the 'Turkey.' Now go make 20 'Turkey Sandwiches' (clips, posts, quotes) for other platforms." —Daisy-ree Quaker 🚀 Last week to join the top-rated [Live + Hands-On] Actionable AI For Marketers Course. Don’t just read the checklist, come build the solutions with us.
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@victor_bigfield ·
reddit is the #1 source cited by perplexity ai 46.7% of all citations. that's nearly half of everything it references. if you're not building a presence on reddit, you're invisible to the next generation of search. your competitors who post helpful answers in niche subreddits? they're showing up everywhere. google indexes reddit and ranks it on page one. perplexity cites reddit as its primary source. chatgpt trains on reddit discussions. every major ai system is drinking from the same well. reddit is the new seo. most founders haven't realized it yet - they're still obsessing over backlinks while reddit threads dominate the serps
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@victor_bigfield ·
here's proof that seo isn't dead and it helps you rank in chatgpt i tested it on chatgpt for this query: tool find lead on reddit and my latest blog post already ranks in chatgpt (see source) also i noticed that for the same query if i ask it multiple times i don't always get the same answers so publishing articles still works in 2026
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@glenngabe ·
Google's Nick Fox (@thefox) was asked about GEOs entering the scene and gaming Google, and how a similar thing happened in the early 2000s. Are we seeing that again?? Nick: We published a document last week covering how to optimzie for AI Search (which is basically what you should do for SEO)... But it's important to go beyond the surface level with your content. The content that will perform the best in AI goes deeper. (Me: i.e. "Non-commodity" content.) And regarding the cat and mouse spam game, we'll how that plays out. The models are really smart so they should be able to figure it out... He does worry about prompt injection and Google is keeping an eye out for spammy tactics trying to game AI/Google. https://t.co/kEuZx38TJn
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@kaleighf ·
The answer to "how do we get cited or show up in AI search results" is not "push out more AI-generated content." It's getting really strategic about what your brand can uniquely add to the conversation.
Watch video
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I was reviewing the last profiles submitted on JobBoardSearch 🔎 Some came from Google. Some from LinkedIn posts. Some from Reddit or Instagram. Someone literally wrote: "Asked Claude about job search websites." Every click is a job seeker and a potential visitor to your board Remember to work on AOI / GEO (yes, job seekers are using AI agents to search for job boards!) AOI / GEO tips for founders: - Direct Answer First (Power Snippets) - Emphasize E-E-A-T & Info Gain - Use Structured Data (Schema Markup) - Target Conversational Queries - Optimize for Entities, Not Just Keywords - Improve Content Readability & Structure
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@jbobbink ·
I've seen SEOs spend days rebuilding their sites in Markdown to rank in AI search. Tturns out it was all for nothing. Profound just ran the first proper A/B test on this. 381 pages across 6 real websites, tracked over 3 weeks with randomized control groups. The result? Markdown pages got roughly 1 extra bot visit over 3 weeks compared to HTML. One. That's it. The 16% average lift that looks promising on paper is driven entirely by pages that already had heavy bot traffic. The typical page saw almost zero difference. Even ChatGPT-User, which makes up 73% of all AI bot traffic, showed no statistically significant preference for Markdown. Here's the part that should make every SEO pause: Google's John Mueller said LLMs have trained on parsed web pages since the beginning and have no problems dealing with HTML. Bing's Fabrice Canel went further. He called Markdown files "sub-standard" and asked a question every SEO should hear: "how will you know when your .md transform is half-broken on a page? who will fix it?" He also pointed out something critical. Bing ranks based on what customers see, not what bots see. This matters because Markdown for bots creates a second version of your site that humans never review. It's the same problem as cloaking, where you serve different content to different visitors. And we all know how that story ends. Glenn Gabe compared it to AMP, except AMP at least had clear rewards from Google. Markdown has none. After all these years in the SEO threnches I've seen this pattern repeat. A tactic sounds logical. Early adopters report gains. Everyone rushes in. Then the data arrives and shows it was noise all along. Save your engineering hours. Focus on what actually moves the needle: crawlable HTML, clear structure, fast pages, and content that genuinely answers what AI models are looking for. The format you serve bots is not your leverage point. At least not yet.
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@sharyph_ ·
60% of Google searches now end without a click. Read that again. People search. AI gives them the answer. They never visit your site. Most content creators are panicking about this. I'm doubling down. Here's why: If AI is answering questions with your content, you're winning. Getting cited by ChatGPT or Perplexity is the new featured snippet. It's digital authority on steroids. Only 11% of websites get cited by both ChatGPT and Perplexity. That's not a problem. That's an opportunity for early movers. The shift isn't "make content AI can't steal." It's "make content AI wants to cite." How? → Clear question →answer structure → Original data and proprietary insights → Specific details over generic advice → Short paragraphs (60-100 words max) → Semantic variation over keyword stuffing I tested this on 12 posts. 3 are now cited regularly by AI models. Those same 3 rank on page 1 of Google. Here's the insight no one's saying: Content optimized for AI also wins in traditional search. Because Google's algorithm is becoming more AI-like. It's looking for: → Clear answers → Natural language → Semantic relevance → Structured information The creators who figure out AEO (Answer Engine Optimization) in 2025 will dominate discovery for the next 5 years. Everyone else will still be chasing SEO tactics from 2019. By 2026, 25% of search volume shifts to AI chatbots. You can complain about it. Or you can get cited by it. Your move.
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@fatjoedavies ·
What will SEO retainers look like in 2026? Pretty much how they did in 2025, if it included these: - Ensure a technically sound and fast website, with great UX - Building content and pages that serve the intent buyers are searching for - Building a knowledge base that answers every question about the service/product - Attracting or soliciting brand mentions and backlinks from bloggers and media - Getting features in listicles, editorial reviews and buying guides - Encouraging positive brand sentiment on forums and review sites If those are in your retainer, you're going to be featured in search engines and AI engines. There are of course some things to focus on for AI (brand mentions and brand sentiment), but for the most part, GEO is 90% SEO.
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@kristakdoyle ·
🤓 NEW RESEARCH: I spent the past month analyzing 33,000+ citations across 1,000 queries sourced from and modeled after real B2B buyer questions to get a snapshot of how third party sources are *really* showing up in AI search right now. The results are in. Here's what stood out: 📊 Reddit and YouTube account for more B2B AI citations than every other off-site platform combined. Most B2B brands are still insanely underinvested in these two channels, but AI engines are treating them as primary sources for understanding your brand and its products. 📊 Google AI Overviews now trigger on 84% of B2B queries. Remember "10 blue links"? Ahh, a simpler time. Now, AIOs sit above the traditional SERPs for the vast majority of B2B searches. If your brand isn't showing up in those answers, you're invisible in the place that likely still matters most. 📊 The average cited YouTube video was referenced 2.3x across queries. Good news for brands who are scared of YouTube because it's a heavier lift: a single good video can (and usually does) compound visibility across multiple queries and AI search engines. Do not sleep on testing this channel. 📊 80% of AI-cited Reddit posts had fewer than 20 upvotes. Aka don't let anyone trick you into thinking you need virality to get visibilty on Reddit. AI often cites more focused Q&A and discussion threads averaging just 80 words. You don't need to game any algorithms here -- but you do need to be intentionally present and helpful in the right conversations. 📊 Only 7.7% of cited URLs appeared in more than one AI engine. Optimizing for one engine does not necessarily give you visibility in the others. Each engine has its own source preferences, its own trust signals, and its own retrieval patterns. That means you need an engine-aware strategy, not a one-size-fits-all approach. I built this report because I kept hearing the same thing from B2B marketing leaders: "Off-site is a black box to us, we have no idea how or where to get started." Now you do. 🫴 Here's 21 pages of data, strategy, and platform-specific takeaways. Free download now at: https://t.co/4p6OkZVJMG
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@kristakdoyle ·
Citations are great, yes, but the real unlock for Reddit, YouTube, LinkedIn etc with AEO is being so consistently present and helpful there that you become the actual training data over time. Growing citations is a natural byproduct of that and you’ll see results pretty quickly, but you really want to be influencing and measuring direct traffic, AI mention rate, and sentiment. These platforms are community/social/brandom principles first and foremost, AEO results are the byproduct.
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@donnellycss ·
Brands have seen +200% AI traffic in under 30 days… If you want to win search in 2026, you need to understand how it’s changing. Here are the five main types… SEO Google rankings via keywords & backlinks. It’s slow, competitive, but still very powerful. To rank target high-intent keyword clusters + refresh old posts. GEO Getting cited by ChatGPT, Perplexity, and Gemini. Right now, there’s an early mover advantage. To rank use entity-rich pages, clear FAQs, tables, and forums. AEO Winning zero-click answers & snippets. There are fewer clicks but more authority To rank answer questions in 40–60 words and use schema. AIO This is how AI understands your brand. Builds trust with AI tools and is good for long-term brand recall. To rank, use consistent structured content on trusted sites. SXO Turning traffic into revenue. This is where money is made. To rank, have a fast site, mobile UX, and clear CTAs. These will decide if your brand is found or forgotten in 2026. Which one are you optimising for right now? 👇
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@kaleighf ·
On expanding the creator definition for the AEO context: Creator is a wider umbrella than it sounds in this context. The instinct is to read "creator" as "influencer," and stop there, but that reading leaves value on the table for B2B. There's certainly a case to be made for B2B/LinkedIn creators within this equation, but I believe some of the strongest creators for AEO in a B2B category are often the employee experts who work inside a company. Think about the solutions engineer with a point of view, the product manager who has posted about their niche for years, the VP of customer success who answers real questions in real communities like Reddit--these employees are creators and influencers in every sense an LLM cares about (even if they would never put the word on a business card or call themselves one.) If they have expertise, they publish under their own names, consistently post about a specific topic, and they have standing on the surfaces where buyers go to research…that’s an influencer (like it or not.) We’ve just been calling them “employee advocates” up to this point. But now, it’s time for us to broaden that definition.
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@RandallKanna ·
One thing I’ve noticed recently while I'm doing outreach for Kelsey... Most companies have no idea whether they show up in AI answers. There’s no equivalent of “rank tracking” yet. So teams are optimizing blindly and trying random scattered things. I’ve been digging into this gap and analyzing how different sites appear (or don’t). The differences are often surprisingly fixable once you see them. But the best thing I've figured out is tracking who is showing up and why THEY are instead of trying to guess at optimizations.
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