Measurement and monitoring
Tracking mentions, citations, citation share, prompts, competitors, sources, referral traffic, conversions, and changes over time.
40%
Best tweets about AI Visibility
50 Best Tweets About AI Visibility (2026)
Find the best tweets about AI visibility, covering brand mentions, citations, answer engines, LLM monitoring, measurement, content, and search strategy.
Brand and content visibility inside AI assistants and answer engines, including citations, measurement, monitoring, experiments, and strategy.
- Creators
- 37
- Updated
Original Xholic analysis
What 50 top AI Visibility posts reveal
AI visibility is framed as a discovery and recommendation discipline: measure citations and outcomes, design prompts around real intent, and strengthen clear on-site information plus credible off-site signals. The conversation also warns that answers and dashboards can be volatile, while quick-win tactics may be manipulable or short-lived.
- Dominant tone
- Positive
- Median score
- 6.53
- Leading format
- Case Study
- Recent posts
- 40%
58% of posts
All-time engagement
40% of posts
Published in 90 days
Conversation map
The themes creators return to
Citation and content optimization
Creating clear, structured, expert-led, intent-focused pages, comparisons, research, and answers that AI systems can understand and cite.
32%
Offsite brand signals
Building credible third-party presence through Reddit, YouTube, reviews, forums, LinkedIn, Wikipedia, editorial coverage, and digital PR.
32%
Sustainable quality and trust signals
Favoring authority, authentic evidence, product clarity, real user validation, trustworthy sources, and durable brand reputation over manipulative shortcuts.
32%
Tracking reliability and reporting pitfalls
Addressing answer variability, model and web-access differences, repeat sampling, misleading share-of-voice dashboards, and transparent methodology.
24%
Prompt design and intent
Using representative, customized prompts, personas, query intent, topic clusters, and category priorities to evaluate meaningful AI visibility.
20%
AI visibility strategy
Positioning AI assistants and answer engines as a core discovery, recommendation, and buying channel alongside or beyond traditional SEO.
16%
AI visibility experiments and tactics
Testing listicles, comparisons, publishing velocity, brand mentions, microsites, and other tactics that can quickly influence AI answers.
14%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 25
- Median reposts
- 2
- Median replies
- 4
- Median views
- 2.2K
Posts with media make up 80% of this collection. Their median all-time score is 6.63, compared with 5.57 for text-only posts.
Format mix
- Case Study 40% · score 5.68
- Opinion 40% · score 5.15
- Announcement 12% · score 18.4
- Story 8% · score 19.9
Consensus and debate
Where creators agree, and where they do not
Shared view
Measure beyond rankings and clicks
Posts argue that AI visibility should be assessed through citations, referral traffic, conversions, query context and change over time—not conventional rankings alone.
Shared view
Make content clear and answer-ready
The shared direction is to make products, use cases and answers explicit, with clear structure, expertise and intent-focused information that systems can understand and cite.
Shared view
Off-site reputation shapes visibility
Several posts position reviews, communities, editorial coverage and other third-party sources as material to how AI systems describe or recommend a brand.
Shared view
Prompt intent needs deliberate design
Monitoring is presented as more useful when prompts reflect audience scenarios, category priorities and real discovery intent rather than generic defaults.
Open debate
Fast tactics versus durable strategy
Some posts report rapid gains from self-promotional listicles, while others warn such tactics are easy to manipulate, may face enforcement, or are unlikely to last.
Open debate
Schema’s role in AI citations
One cited analysis links structured content qualities with citation behavior, but Ahrefs tests reported no major or measurable citation uplift after adding JSON-LD schema.
Open debate
Confidence in tracking dashboards
New reporting products emphasize citation share, prompts and historical comparison, while critics say biased prompts, blended scores, model differences and answer variability can mislead reporting.
What performs
Patterns behind standout posts
Measurement and monitoring led the themes
Measurement and monitoring was the largest theme at 40% of tweets and had a 9.02 median all-time score; its evidence emphasizes citations, context and revenue relevance.
Strategic framing earned strong engagement
AI visibility strategy had the highest theme median all-time score, 12.3. High-scoring posts cast assistants as a core product-discovery channel and visibility as a strategic metric.
Experiment stories produced standout posts
AI-visibility experiments had a 12.158 theme median all-time score, and the strongest outlier reported a listicle-based brand-mention experiment. The evidence itself also invites caution about durability.
Media posts outperformed text posts
Deterministic analytics show media posts had a 6.63 median all-time score versus 5.57 for text posts.
Statistical standouts
- View standout post 1 Score 771.9 · 118.21× median
- View standout post 2 Score 180.8 · 27.69× median
- View standout post 3 Score 97.6 · 14.95× median
- View standout post 4 Score 66.5 · 10.18× median
- View standout post 5 Score 47.6 · 7.3× 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. Brodie Clark
@brodieseo
2 posts
-
3. Glenn Gabe
@glenngabe
2 posts
-
4. Jake Ward
@jakezward
2 posts
-
5. Kaleigh Moore
@kaleighf
2 posts
-
6. Mehrab | SEO Mode
@mehrab_build
2 posts
Aleyda Solis pairs guidance with assessment
Aleyda Solis’s evidence combines AEO/GEO guidance on machine-readable catalogs, intent and trust with a scored AI-search-readiness checklist.
Glenn Gabe foregrounds evidence and reporting
Glenn Gabe highlighted both the schema citation study and Bing’s expanded visibility reporting, connecting experimental evidence with measurement capabilities.
Brodie Clark stresses measurement limits
Brodie Clark’s posts flag self-promotional listicle risk and point to evidence that AI recommendation lists can be inconsistent, reinforcing a cautious monitoring stance.
Since the previous snapshot
What changed since Aug 12, 2026
- 62% of the selected posts remained.
- The creator count changed by -1.
- The leading sentiment remained stable.
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 AI Visibility tweets
Top AI Visibility tweets from 37 creators
Ranked 01–50
- 01
@mehrab_build ·
It's stupidly simple to get your brand mentioned in AI models right now Two weeks ago I blasted out "best X" listicles for a client Checked this week. 10x more brand mentions across almost every major LLM 😆 I just fed them our brand name + a unique selling point more often than our competitors. Here's how you can do it as well 👇
- 02
@marclou ·
My friend @AlexandruGlv is building a micro SaaS while working a 9/5, but the growth is very slow, so he asked for my opinion. (for context, his product is a database to find YouTube influencers to sponsor) I went to ChatGPT and asked: "How to find youtubers to sponsor?" It came up with DIY solutions or large generic databases, nothing that fit my use case. If I had to start a new SaaS today, I'd think "How will people interact with my product in 5 years?" In most cases, the answer is through AI assistants, so I'd set AI visibility as my North Star metric and build everything backwards. I'd do everything so that potential customers can 1. Find my product on ChatGPT 2. Onboard on ChatGPT 3. Get value from ChatGPT llms.txt, markdown files, get mentions on Reddit/YouTube, etc... It's still unclear what you need to do to get mentioned, but I'd try everything to become an AI agent first startup, as @wickedguro did with Postiz ($150K MRR). And who knows, maybe along the way I'd discover a new product worth 100x more than my current SaaS? Fuck Around and Find Out 😊
- 03
@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
- 04
@glenngabe ·
Interested in Schema impact on AI citations? Here's the latest study from @ahrefs -> We Tracked 1,885 Pages Adding Schema. AI Citations Barely Moved "We tracked 1,885 web pages that added JSON-LD schema between August 2025 and March 2026, matched them against 4,000 control pages, and measured citation changes across Google AI Overviews, AI Mode, and ChatGPT. Adding schema produced no major uplift in citations on any platform." https://t.co/cinIs15p9M
- 05
@SEOKeval ·
It can take 6-12 months to rank in Google. But it only takes a few days to show up in AI models. They're so easy to manipulate. It feels like a crime. I blasted out "best X" listicles to help a brand's AI visibility a week ago. Within three days... They were appearing at the top of Google's AI Overviews, ChatGPT, and Claude. Three. Friggin'. Days. I wasn't optimizing for Google back in the early 2000's... But I imagine this is what it felt like. It's comical to think back to 2-3 years when AI was gaining steam and everyone thought the SEO industry was cooked. You know who's actually cooked? Humanity. Because everyone trusts AI with their lives. And I can change its results before the weekend.
- 06
@aleyda ·
✅ The AI Search Winning Brands Assessment Checklist: I've created an easy to use checklist (available to copy and use for free) to assess the main characteristics of AI winning brands based on the infographic I shared yesterday! For each characteristic, it provides: * Validation Items * Why This Matters * How to Verify * Scoring level As an outcome you obtain an AI Search Readiness scoring via a Summary Dashboard : 🟢 80–100%: Strong AI search readiness: Focus on maintaining and refining. 🟡 50–79%: Moderate readiness: Prioritize weaker characteristics. 🔴 Below 50%: Significant gaps: Start with Accessible, Useful, and Recognizable. Access the checklist, along with further explanations of each characteristic to facilitate your AI search audits 👇 https://t.co/gTHC70m75c
- 07
@neilpatel ·
Check out the new AI visibility stack. Most marketers focus on the stuff on the bottom, like technical SEO, but they forget the stuff towards the top, like measurement. Everyone wants more visibility, but if the visibility never drives any revenue, does it really matter? This is why things like measurement are important.
- 08
@glenngabe ·
Big news from Bing. And you can compare changes over time. This is what @kmadhavan77 shared in April and now it's rolling out -> New AI Visibility Insights in Bing Webmaster Tools: Intents, Topics, Citation Share, Compare "AI-generated answers are dynamic, contextual, and often synthesized from many sources at once. Understanding visibility in these systems requires more than a single metric or surface-level citation count. With these expanded preview capabilities, Bing Webmaster Tools is expanding first-party reporting to provide deeper insight into the query context, thematic patterns, relative citation presence, and changes over time that shape how content appears in AI-powered experiences." "With the new Intents feature, grounding queries in the AI Performance Report are now classified into broader categories such as Informational, Commercial, Navigational, Learn and Solve, Research, Creation, Local, and more. This helps publishers move beyond simply seeing which queries triggered citations and begin understanding the broader query context our systems associate with those citation appearances." "We are also introducing Topics, which group related grounding queries into broader thematic clusters. AI systems reason across concepts and themes rather than isolated keywords. Topics help publishers understand visibility in the same thematic structure that modern AI systems use to organize information." "While total citation counts show how often your content appears in AI-generated answers, Citation Share shows how much of the citation space your site receives for a specific grounding query. It is calculated as the percentage of citations attributed to your site out of all citations shown across all sites for that same grounding query." https://t.co/FEoz44fFxz
- 09
@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.
- 10
@ShubhAgrawal26 ·
something really basic I did today that made me feel like - "damn! AGI is almost here and technology has gone so far" I was building some content and growth infra which had an elaborate directory of thousands of LinkedIn posts, tweets, newsletters, and internal docs inside an Obsidian vault on my Mac mini. I then had to visit a hospital to meet a friend for his surgery, while in the hospital, I had my macbook with me. I realized I needed this obsidian vault's data to connect with ahref's, google search console and promptwatch - check our AI visibility and self create structures of blogs for AEO from existing past content, by identifying whatever is missing or noot ranking in our sitemap. but this vault was on my mac mini at home , which is also where I had the claude code instance running. I was able to ask claude code via remote control using my phone -> make a copy of the vault and paste it from my local mac mini folder to my icloud -> opened this vault on my macbook and complete the entire task. insane!! we're truly living in the future API's and MCP's fetch real time metrics and data from SaaS tools markdown files that seld update with relevant company context Agents that can control and take actions on your computer while you run them from ur phone complete analysis to great results end to end. beautiful
- 11
@emilylai ·
Playing around with an AI visibility tool and looking into what people prompt into gpt, claude, perplexity For "make money" there's a few prompts around clipping, ugc, and content creation For "Ethereum" the first one is "Will Ethereum's usage increase if Base gains more traction" lol alongside prompts asking ai to help with announcements and articles For "Solana" the first one: "Provide a detailed trading strategy using MobyScreener for Solana." and other prompts around price predictions For "crypto" i'm seeing all sorts of prompts from troubleshooting to tax questions if certain exchanges are available in geos
- 12
@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/iv0Gzu2BYl.
- 13
@levikov ·
Writing for LLMs is the most valuable and most ignored skill on the entire internet right now and the operators who master it in the next 12 months will control where every AI-generated recommendation points for the next decade… When someone asks ChatGPT or Perplexity or Claude "what's the best tool for X" or "should I buy Y" the AI doesn't browse the internet in real time and make a fresh judgment call. It synthesizes information from sources it was trained on and sources it can access. If your brand, your product, your name isn't in those sources in a way the AI can understand and extract, you literally don't exist inside the world's fastest-growing discovery channel Google searches are declining for the first time in the platform's history. Not because people stopped looking for information. Because they started asking AI instead. And AI doesn't show 10 links. It gives one answer. Maybe two. The brand that AI names first gets 80-90% of the attention. Second place gets scraps. Third place doesn't exist This is a completely different optimization game than SEO. With Google you could rank for hundreds of keywords and get traffic from all of them. With AI answers you either ARE the recommendation or you aren't. There's no page 2. There's barely a page 1. There's the answer The people figuring this out right now are doing things that sound boring but print stupid money. They're publishing original research that AI systems cite as sources. They're building structured data layers on their product pages so AI can parse specs without guessing. They're getting their brand mentioned in Reddit threads and forums that LLMs scrape as training data. They're making sure that when an AI system needs to recommend something in their category, their brand is the most referenced, most cited, most structured option available I know someone in the project management software space who figured this out 8 months ago. Instead of spending $80k/month on Google Ads he hired 3 people full time to do nothing but create original comparison content, publish detailed methodology pages, and plant structured recommendation threads across Reddit, Quora, and niche forums. His brand went from appearing in 0% of AI-generated software recommendations to appearing in roughly 40% within 6 months. Organic signups from AI-referred traffic are now his largest growth channel. Cost: $18k/month for the team. Revenue from the channel: $120k+/month. The CAC is absurd The wildest part is that LLM training data creates a compounding moat. Once your brand is embedded in the training data that these models learn from, removing it requires retraining the entire model. Your competitor can't just outbid you the way they can on Google Ads. They'd need to generate MORE mentions, MORE citations, MORE structured data than you across the entire internet. First mover advantage in LLM visibility is the most durable competitive advantage in marketing right now because the switching cost for the AI itself is astronomical (btw this is also why the Reddit SEO play I've talked about before is getting 10x more valuable. Reddit threads don't just rank on Google anymore. They get scraped into LLM training data. A well-crafted Reddit post recommending your product doesn't just drive Google traffic for 2 years. It potentially gets baked into the AI's knowledge permanently. One post influencing millions of AI-generated recommendations for years. The ROI on that is incalculable) the entire marketing industry is still optimizing for an algorithm that shows 10 links while the discovery layer that shows 1 answer is eating everything. the window where you can cheaply establish yourself as the AI's default recommendation is 12-18 months. after that the training data moat makes it almost impossible to displace the incumbents whoever owns the AI's answer owns the customer. and right now almost nobody is even trying
- 14
@peec_ai ·
We analyzed 30 million sources cited by ChatGPT, Google AI Mode, Gemini, Perplexity, and AI Overviews. The 10 most-cited domains: 1 Reddit 2 YouTube 3 LinkedIn 4 Wikipedia 5 Forbes 6 G2 7 Yelp 8 Facebook 9 Medium 10 TechRadar Facebook is #8 despite being mostly behind a login wall. Yelp is #7 despite being a review platform most B2B teams ignore completely. Where your brand shows up on these platforms determines a lot of what AI says about you.
- 15
@semrush ·
AI isn't only reading your website, it's also reading what everyone else says about you 🧐 Think Reddit threads, G2 reviews, and media mentions. That's where a lot of the citations actually come from. Wild example: Seer Interactive found that one bad review from 2018 was still changing how every major AI model talked about their brand. Years later. One review! Most brands have no idea what story AI is telling about them right now. So it's not that SEO is dead, it's just not the whole picture. You've got three layers to think about: your own site, how you're building your brand, and what others are saying about you out there. Getting a handle on all three is where it starts 👇 https://t.co/qMP2sDepJ0.
- 16
@neilpatel ·
20 years of SEO obsession over backlinks. Turns out branded mentions on credible sites predict AI visibility better. That's not a small shift. That's the whole strategy flipped. #SEO #AIOverviews #ContentMarketing #DigitalMarketing
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- 17
@elvissun ·
"is this shit legit?" run this prompt against your website right now. here's why: last week, we shipped https://t.co/aq7DBz7en5 as open source, and the install flow asks people to point their agent at a remote script via curl | bash. modern agents are smart. they will not execute random code on your machine just because you asked nicely. so i tested this by running the install in a fresh claude session and watched it interrogate my own brand. round 1: agent flags the install command as high risk. fix: link to where the install command actually lives. round 2: agent says the website could be hosting a different script than the repo. fix: open source the entire website. round 3: agent says the authors are unknown. fix: link my x, linkedin at the bottom of the page. round 4: agent says there aren't enough trust signals. fix: ship the thing, get real users, stars catch up. every round was the agent doing what a careful journalist would do before running a pitch. check the source. check the source of the source. check the byline. this is the test everyone should run on their own brand. open your site in claude right now. ask the agent if the company is legit in the most skeptical way possible. watch it research. watch it doubt. read the gaps in its reasoning back as a list of missing evidence. that list is your AI visibility roadmap. not "more press." specifically: which signals does the agent need before it stops being suspicious of you. trust used to be a feeling. now it's a checklist a model walks before it lets your name through the door. welcome to the new earned media.
- 18
- 19
@AIStackLabX ·
If ChatGPT were asked about your industry today... Would it mention your brand? I tested @pallasai_io using Canva as an example brand to see how it appears across AI search engines. What surprised me wasn't the content generation. It was the visibility layer. Within minutes, I could: ✓ Identify competitors automatically ✓ Map audiences, scenarios, and search intent ✓ Track brand mentions across AI platforms ✓ See how AI actually describes the brand ✓ Generate GEO content to improve AI visibility The bigger takeaway? We're no longer competing only for search rankings. We're competing for AI recommendations. Millions of people now use ChatGPT, Claude, and Perplexity to discover products, compare solutions, and make decisions. When they ask AI a question, they don't get a page of links. They get an answer. Your customers are already asking AI for recommendations. The question is whether AI is recommending you or your competitors.
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- 20
@gaetano_nyc ·
I just took a VP of marketing through a “LLM visibility monitoring” dashboard to reveal all the ways they are getting tricked in the reporting. 1. Filter includes brand prompts which inflates their “share of voice” score. 2. Visibility dashboard shows a blended “share of voice” where they already have high recommendation rates for their flagship category. 3. Company has a strategic priority to break into a new category, which is not being tracked or monitored. This is marketing’s way of not reporting on a “bad” visibility score. 4. Prompts are biased and contain seeded phrasing where the brand will be dominant by default. Example: they are a compliance tool and the prompt leads with “For a VP of compliance at a mid-market company…” These tools are highly manipulate-able and executives don’t understand how it all works.
- 21
@thinking_slow ·
does adding schema markup help your pages get cited in AI search? probably not 👇 we (@ahrefs) analyzed 6M URLs and found schema is more common on heavily cited pages BUT that's probably correlation, not causation: schema markup is more common on pages with good SEO generally so we tested 1,885 pages that actually added JSON-LD schema and compared their citations before and after verdict: across Google AI Overviews, AI Mode, and ChatGPT, we saw *no measurable difference* in citations (or even a tiny negative effect) schema matters for plenty of reasons in SEO and AI search, but adding schema to your pages is probably not some magic fix for improving your AI citations ✌
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- 22
@Marie_Haynes ·
Some thoughts on Google's new guidance on ranking in AI Search - including info on Bing's blog post about the purpose of the index changing so as to serve for grounding for AI.
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- 23
@ViperChill ·
Since joining Ahrefs five months ago, I've documented 106 product updates. Here are my favourite announcements from January… (This looks a bit better on LinkedIn where there are additional images, so I've also included some commentary) 1. AI visibility reports now include traditional search metrics Now, when you look up the top cited domains and pages for the prompts you care about, you'll see some familiar stats. Site / page traffic, Domain Rating and URL Rating have been added first, with more on the way. 2. Historical ranking data for newly tracked keywords If you add new keywords to Rank Tracker, you can import historical ranking data so your reporting no longer starts from scratch. Optionally, you can also add years of ranking history to terms you're already monitoring. 3. The Social Media Manager tool has had some serious upgrades There are almost too many to cover here, including the ability to leave the first comment on posts, improved performance charts and enabling multiple attachments per post. It's currently free (including unlimited posts and channel connections) for all account levels. 4. Generate custom prompts to track your AI visibility We take your brand, competitors and (optional) custom instructions to generate relevant prompts to monitor responses for. You can still enter prompts manually, and use this new tool for inspiration on angles to tweak. We'll soon ground prompt suggestions in keyword and website data to take this to the next level. ** I bought my first Ahrefs subscription over 12 years ago, and it wasn't until I joined the company that I realized how often new updates go live. That was the primary inspiration behind this new 'Ahrefs Ships' angle. If seeing monthly product updates in this way is useful, please let me know and I'll keep these coming every month 🙌
- 24
@alexmdees ·
AI can't recommend your brand if it doesn't understand what you actually do. Your website used to be built for humans browsing. Now AI is: - Visiting your site every single day - Reading every page - Trying to figure out what you do and who you do it for Brands should be thinking about AI as the most consistent user they'll have for the next hundred years. If your products, use cases, and pain points are only implied on your site, AI has nothing to work with. People/brands that spell it out clearly are the ones getting surfaced. The fix takes an afternoon.
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- 25
@brodieseo ·
Brilliant read on the issue of consistency of AI tools when asked for a list of brands/products. This is a big industry-wide issue. And with the explosion in popularity of LLM tracking tools and SEOs now offering GEO services, it's only going to become more of an issue. The results from @randfish study confirm this: • AIs rarely give the same list of brands or recommendations twice (<1 in 100 times, no matter the question). • You can, with enough prompts run enough times, get a dartboard-pattern-like answer comparing you with others. • The variation in AI answers is likely much higher than what this controlled experiment revealed. Make sure to check out the full study and pass it on to others so they are aware of the shortcomings. Also, as Rand suggests, we should be encouraging AI tracking providers to publish transparent data around this. Read here: https://t.co/6w9mV3yqSA
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@yusukelp ·
I turned my AI visibility dogfooding for LandingBoost into a local dashboard. It now tracks: - Google index status - GSC movement - search positions - Reddit/source rankings - AI mentions/citations across Perplexity / OpenAI web search / online models - next actions to improve visibility Current state: - 13 dogfood runs logged - 4 target pages indexed by Google - LandingBoost is #7 for “landing page audit tool for saas” - Perplexity mentioned/cited LandingBoost for “best tool for a SaaS landing page audit” - OpenAI/Google-style answers are still not there yet This is the loop I wanted: 1. publish/edit pages 2. measure search + AI answers 3. see what sources are being used 4. decide the next page/FAQ/comparison edit 5. repeat Still early, but this finally feels like a system instead of random GEO guessing.
- 30
@SEOKeval ·
A lot of people are running AI SEO strategies that are NOT future-proofed. "Oh, you just need to blast listicles?" *Proceeds to blast listicles on 100 bullsh*t PBN sites with no authority or keyword rankings* Yeah, that works right now. But, come on... Do you really think that will last? Do you really think Open AI, Anthropic and Google won't realize people are gaming the system that way? Doing that is akin to ranking sites in Google with a volume (not quality) approach to link building. Yeah, it worked for a while. But then all of sites that utilized that tactic tanked. It's absolutely in your best interest to run AI SEO strategies the right way. Post listicles on real sites. Make sure those sites actually rank well. Make sure those sites have good authority. Yeah, it'll be more expensive for you. But it'll significantly increase the odds of your AI visibility standing the test of time.
- 31
@KaiCromwell ·
What we're doing differently in the last 60 days: - more topical authority content for health/beauty brands >> Has directly contributed to higher money page rankings, more revenue generated, and more AI citations. - stricter content standards >> I now review every single piece of content that our team produces before it goes to the client or to their website. Every feedback video is sent to Manus to update our frontend AI content workflows for continuous optimization. - killed 10+ AI projects that were 'in the works' >> vibe coding is cool, but it can also be a huge waste of time. If it's not actively making us more money or saving us time/money, we killed it. Lessons learned: you have to religiously execute on the fundamentals 24/7 (no shortcuts) and build an ops system that supports these fundamentals.
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@peeplaja ·
We surveyed 100 CFOs and VPs of Finance on how they buy software. The first question: where do you START the vendor search? → 38% ask peers / their network → 26% go to LLMs (ChatGPT, Claude, Gemini) → 20% Google it → 9% hit review/analyst platforms (G2, Gartner) → 7% go to known vendors directly Finance people trust their peers above everything else. LLMs have overtaken Google as the #2 starting point for software vendor search. Here are examples of what the CFOs told us on how they use LLMs: "When we are looking for a vendor, first I usually ask Gemini or ChatGPT to give me an overview of the available vendors, pros and cons." "I would describe to a LLM the nature of my business, desired outcome, and experience in attempting to solve the problem to date and inquire for suggested solutions." "Use LLM to produce a paper on options, feedback and cost. LLM will also help team to produce a tender pack." These aren't early adopters. These are CFOs running the buying process. What this means if you sell to the finance function: 1. Peers still dominate. Customer advocacy and CFO community presence aren't "nice to haves", they're your primary discovery engine. 2. Your SEO strategy alone won't cut it anymore. LLM visibility is now a parallel channel you need to win. Cold outreach? Not even on this chart. Zero respondents said "I start by looking at my inbox." Zero. The buying process is bifurcating: Trust channels (peers, network) → for shortlisting AI channels (LLMs) → for market mapping Google → still there but no longer alone
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@AICommerceGuy_ ·
AI Search Decoded — Day 4 of 10 Where AI pulls "truth" about your brand. Your website matters. A lot. It's where your structured data, schema markup, product specs, and policies live. It's the source AI cross-references everything else against. But it's not the only place AI looks. And that's the part most brands miss. 85% of brand mentions in AI answers reference external sources alongside the brand's own site. AI builds a picture of your brand from multiple surfaces, not just one. Your website is the foundation. These platforms are the amplifiers: Reddit — 24% of all Perplexity citations come from Reddit. But 99% of those point to real discussion threads, not brand pages. AI cites genuine conversations about your product. YouTube — Strongest single predictor of AI visibility at 0.737 correlation across 75,000 brands. AI reads transcripts and descriptions. Product reviews and demos are now search content. LinkedIn — Moved from #11 to #5 on ChatGPT in three months. Cited in 14.3% of ChatGPT responses. Your posts are now dual-purpose: audience building and AI training data. Wikipedia — Top 3 source across every platform. If your brand has an entry, AI treats you as a verified entity. That changes everything. Review platforms — Brands on G2, Capterra, Trustpilot, and Yelp see a 3x citation multiplier vs brands without those profiles. How it actually works: Your website provides the structured truth. Product data, schema, pricing, policies. This is what AI reads first to understand what you sell. External sources provide the validation. Reddit, YouTube, reviews, press. This is how AI decides whether to trust what your website says. If your website data is clean but nobody talks about you externally, AI has the facts but not the confidence to recommend. If external sources mention you but your website data is messy, AI has the buzz but can't verify the details. You still get filtered out. You need both. The website is the source of truth. External presence is the trust signal. The part most people get wrong: There is no universal top source. Reddit leads on Perplexity but barely registers on Gemini. LinkedIn skews heavy on ChatGPT but not on others. Each AI engine pulls from different places. Treating "AI visibility" as one channel is a mistake. What to do about it: First: get your website right. Structured data, schema markup, complete product information, machine-readable policies. This is the non-negotiable foundation. Then: build real presence on the surfaces AI reads. Not brand accounts posting promotions. Real discussions. Real content. Real reviews mentioning specific product attributes. Your website tells AI what's true. Everything else tells AI whether to believe it. Tomorrow Day 5: 93% of AI sessions end without a click. Your traffic is dropping and your dashboard can't explain why. Bookmark this series. By Day 10 you'll understand AI visibility better than 95% of marketers.
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@TheCoolestCool ·
Pro Tip: If you're using the default prompts that an LLM / AI Visibility tool is giving you... with no customization: You're tracking & working against AI-Slop prompts. I've seen 10 accounts this month filled with prompts that make absolutely no sense to track... This is why SEOs need a seat at the AI visibility table. SEOs understand intent. A lot of the new-age marketers have no clue what to track because they don't know how people search or discover products. It's a shame.
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@AgenticOperator ·
Got a message yesterday morning that made the last 3 months worth it. A SaaS founder I've been working with sent me his numbers. His product now shows up in roughly 90% of relevant prompts across Claude and ChatGPT. Renewals jumped 30% this quarter. Traffic and revenue both way up. A few months ago he was invisible. Same product. Same market. Zero AI presence. Here's what was actually broken. His product was solid. Customers loved it. But when a buyer asked AI "best tool for [his category]," AI had nothing to work with. His site was built to convert humans. Every page was a sales pitch. No page answered the question AI was being asked. His competitors weren't better. They just had one clean comparison page, a few Reddit threads from real users, and product data AI could actually parse. That's all it took to win the recommendation. What we did wasn't complicated. Rebuilt his key pages so each one answered a specific buyer question instead of pitching. Got his existing customers talking on Reddit and review platforms. Made sure his product data was structured for machines, not just humans. Added honest comparison content his team was scared to publish. No magic. No secret framework. Just making the brand visible in places AI actually looks and giving it something worth citing when it gets there. The part that surprised him most: Google rankings didn't change. Same positions. Same traffic. The entire lift came from AI visibility alone. A channel his team wasn't tracking 4 months ago is now driving 30% more renewals. He texted me "your AEO stuff is legit working." Honestly that's the whole pitch for this space right now. It works. Most brands just haven't started.
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@mehrab_build ·
Ahrefs tracked 1,885 pages that added schema The result? AI citations barely moved :)) Schema is on 53% of AI-cited pages, but those sites also have great content, authority, and backlinks! Next time a LinkedIn guru starts preaching about schema being the key to AI visibility, drop this study in the comments 🙂
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@ViperChill ·
February was a record for new Ahrefs sign-ups self-attributed to AI. 🤖 Mentions of Claude grew the most, and are on track to double in March. AI referrals only account for a small % of sign-ups — and we understandably get a lot of general answers ("social media") — but it's really nice to see the channel growing. (If multiple platforms were mentioned in a response, we didn't count it, so the numbers are technically a bit higher). As I've said before, I'm aware that self-attribution data isn't perfect. It’s affected by recency and recall bias, and it's not easy to account for every variation and typo. It's not the only data source we look at, but it's fun to dive into. (And especially interesting when people talk about specific YouTube channels, podcasts, blog posts, and so on, which convinced them to join.) I report on so many other companies talking about how AI is impacting their marketing, so I think we should do a bit more on that front as well. Hopefully it's interesting! 🤝
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@msftClarity ·
𝐍𝐄𝐖: Citations in Microsoft Clarity is now generally available. 🙌 SEO rankings tell you where you appear in search. Citations tells you whether your content is actually shaping AI-generated answers. We're thrilled to share that Citations is now generally available in Clarity, giving users visibility into how their content shows up across AI-generated experiences. 🔥 Here's what you can now measure: → Page citations → Share of authority → AI referral traffic → Queries AI systems use to find your content → Your most cited pages AI discovery is here. Now you can measure it 📊 Ready to understand your influence in AI answers? Visit the Clarity blog to learn more and get started 👉https://t.co/vntwIcSnLT
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@profitfounder ·
I published one listicle on Medium and another on LinkedIn. Both ranked fast on Google. One was cited in Google AI Overviews in about 72 hours. Tanya's point: AI visibility can move faster than classic SEO, especially in a noncompetitive niche.
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@kaleighf ·
So much of AI visibility is happening on offsite surfaces, a.k.a. not on your website. Human expertise is at the core of what earned citations, so here’s a quick explainer on how brands need to start thinking about this.
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@RandallKanna ·
A successful mentor in tech once told me it's more important to do one thing well than many things poorly. And that's what I'm working on right now in my startup. For us, it's accuracy. AI visibility tracking can be a mess. Every answer can change based on the model, prompt, context, wording, user, etc. We’re not just running a prompt once and pretending that is the “truth" to our users. We're doing a few things differently to be a source you can trust: 1. We run prompts multiple times to get a more reliable baseline. 2. We track results historically so brands can see whether they are gaining or losing visibility over time. 3. We added persona types (today) so you can understand how your brand shows up for different customers. And we’re continuing to build around the idea that AI visibility is not about one perfect answer once. It’s about patterns. - Are you being mentioned more often? - Are competitors showing up ahead of you? - Are you being described accurately? - Are AI answers pulling from the right sources? - Are you visible in the kinds of searches your actual customers are making? That’s what Kelsey is focused on. Helping brands understand how they appear in AI answers, why they appear that way, and what to improve next.
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@msftClarity ·
If you’re still measuring performance the same way you did two years ago, you’re missing part of the funnel. AI assistants are reshaping discovery and influencing decisions before users ever land on your site. Traditional KPIs aren't designed to capture that impact. From AI referral traffic and AI citations to the metric that ultimately matters, AI referral conversions, we break down five forward-thinking KPIs to help you measure AI’s role in growth. 📊🤖 🔗 Explore 5️⃣ KPIs for an AI-mediated web: https://t.co/1LFID1Z5AG
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@kaleighf ·
Why I'm leaning into YouTube for AI visibility: YouTube shows up in roughly 16% of AI answers, ahead of Reddit's 10% in cross-company data. Google's own AI features love it most: over half of their social citations come from YouTube. Perplexity leans on video heavily too (38.7% of its social citations). Two data details: 1. 94% of YouTube citations go to long videos, not Shorts. 2. Popularity doesn't drive it: a 40,000-subscriber channel that answers a question thoroughly beats a 4-million-subscriber channel that entertains around it.
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@siliconvalleymm ·
THAT’S CRAZY: I have 18M followers across platforms - and I was still invisible in ChatGPT. I’ve interviewed CEOs of Microsoft AI, Perplexity, GitHub, General Motors. Didn’t matter. Here’s why: → AI treated my show like a vlog → It understood me more as a creator than serious media → Older podcasts ranked higher just because they’d been around longer The fix took ~8 hours and cost $0. What we changed: — added proper schema to my site — fixed my Wikidata profile — rewrote Spotify / Apple / YouTube descriptions — replaced vanity metrics with real authority signals Now I show up for searches like: “best AI podcast” “female-led tech podcast” Big lesson: AI doesn’t rank you by audience size. It ranks you by how clearly the internet explains who you are. If you have a podcast, personal brand, or company and you’re missing from AI answers, this is probably why.
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@JulianGoldieSEO ·
Google just made business dashboards feel ancient. Local business owners who ignore this are going to waste hours doing work Gemini can now handle in one sentence. What Changed: → Gemini now connects directly to Google Business Profile → It can read your reviews, customer questions, profile data, and performance stats → You can ask about calls, direction requests, search impressions, and customer engagement without opening another dashboard The Real Time-Savers: ✓ Draft review replies based on the exact words customers used ✓ Update holiday hours, menus, photos, attributes, booking links, and ordering links from chat ✓ Spot unanswered customer questions before they quietly cost you leads The Bigger Upgrade: ✔ Business Notebooks remember your website, profile, sources, and chat history ✔ Gemini can surface missed questions and forgotten holiday hours before you ask ✔ You stop managing fields and start asking business questions Practical lesson: Your Google Business Profile is no longer just a listing. It’s becoming the control panel for local AI visibility.
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