From my experience working at the intersection of SEO, AEO (Answer Engine Optimization), and GEO (Generative Engine Optimization), one strategy clearly outperformed everything else in driving visibility both in traditional search results and AI-generated answers: structuring authoritative content for both human intent and machine retrieval. Instead of treating SEO as "rank and wait," we rebuilt our core content hub to satisfy two simultaneous signals: Traditional SEO: strong on-page relevance, clean metadata, internal linking, and backlink authority AI-centric visibility: clear entity definitions, schema markup, FAQ/answer blocks, and conversational phrasing optimized for AI systems like Google's AI Overviews, ChatGPT, Perplexity, and Gemini This dual-layer content model ensured our pages ranked well in classic SERPs while also being easily parsed, cited, and included in AI-generated answers, effectively reaching users whether they clicked through or received direct answers from AI interfaces. Approximate hours invested: Across strategy, content creation, optimization, and monitoring, roughly 360 hours over 6 months. Results achieved: * +68% organic traffic growth from traditional search * ~42% increase in zero-click visibility from AI answer placements * Multiple high-authority AI citations in responses on ChatGPT and Google's SGE expansions within target topics How long it took to see results: The earliest ranking boosts appeared at ~10 weeks, while consistent AI-answer mentions solidified around 16-20 weeks after launch. What made the difference wasn't just "more content"; it was content designed for both machines and humans. Traditional SEO established relevance and authority, but the carefully structured, entity-rich sections, especially FAQs formatted for answer engines, unlocked visibility in AI-driven responses. In today's landscape, appearing in an AI summary can be just as impactful as ranking #1 on page one. Detail's Name: Zeeshan Yaseen Company name: Zeeknows Website: https://zeeknows.com LinkedIn profile: https://www.linkedin.com/in/zeeshan-yaseen/
The one change that made the biggest difference for us was rewriting important pages so the answer appeared immediately at the top of the page. We took pages that were already getting some impressions and rewrote the opening section so they answered the core query in the first few lines, in plain language, without devising readers dig through a long introduction. This sounds simple, but it changed how the pages performed because they became easier for both users and AI systems to understand and extract from. We invested about 72 hours across selecting the pages and rewriting the openings. Over the next couple of months, the updated pages saw around 19 % higher organic clicks, several target keywords moved into the top 10, and 7 % increase in AI visibility. We saw early improvement in 3 to 4 weeks, with clearer ranking and traffic gains in about 6 to 8 weeks. If I had to give one practical takeaway, it would be to make the main answer obvious straight off. In our case, that single change did more for visibility than publishing more content or making small cosmetic SEO tweaks. Full Name: Pranjal Jain Company Name: Supablog Website: https://supablog.app LinkedIn Profile: https://www.linkedin.com/in/pranjal141/
The largest boost for us resulted from turning introduction paragraphs on 18 service pages into concise "direct answer" summaries written in Plain English. At about 3 hours per page, that was approximately 54 hours invested between us. We added a 45 word explanation underneath the headline which consisted of a single fact, number and short definition. Guess what? Search engines (and AI) pulled those sentences almost directly. Organic traffic to those pages increased 41% in 7 weeks. Six pages jumped from ranks 8-11 to 2-4. If you can believe it, AI answer visibility came soon after. Generative engines pulled from those summaries in about 11 of 20 total prompts relating to our service category. Organic search traffic doubled in 60 days with an additional 3,200 visits per month. Two industry blogs even quoted the explanation text directly which gained us 17 referring domains. The crazy part is the work was simple and little time was required. Plain English atop the page allows machines an easy sentence to pull. -- Patrick Beltran Marketing Director at Ardoz Digital ardozdigital.com
If we look beyond the standard practices of analyzing AI outputs and cited sources—which are fundamental in my view—the strategy that makes the most significant difference is Authority-By-Association through Strategic Digital PR and Brand Citations. In many cases, a client's website may have excellent content but lacks the inherent trust level that a Generative Engine (GEO) or Answer Engine (AEO) assigns to global powerhouses like Forbes, The New York Times, or major industry-specific authorities. To bridge this gap, we focus on distributing our core insights and expertise across these established, high-trust platforms. The most effective task within this strategy is the execution of targeted Press Releases and Brand Mentions on authoritative news and industry portals. These platforms act as "anchor points" for AI models during their retrieval process. By appearing in these high-trust environments, we essentially borrow their authority. Furthermore, participating in "Top 3" or partner ratings on third-party sites acts as a massive signal to AI models that our brand is a primary player in the niche. Performance Metrics: - Hours Invested: Approximately 4 to 6 hours for drafting high-value PR content and managing distribution to Tier-1 and Tier-2 publishers. - The Results: We track success through a steady increase in "AI Citation Frequency" and, more importantly, a rise in inbound leads. Using cross-channel analytics, we have identified a measurable growth in high-intent inquiries specifically originating from AI-driven discovery. - Timeframe: We typically see the first measurable impact on visibility and lead flow within 4 weeks of the publications going live. Andrew Antokhin Founder & SEO Strategist, Inverox Digital https://inveroxdigital.com/ https://linkedin.com/in/andrewantokhin
The biggest difference for improving visibility across both traditional search and AI-generated answers came from restructuring existing content around answer intent instead of keyword density. Rather than publishing new articles, I audited pages that were already receiving impressions in Google Search Console and identified queries where the page ranked on page one or early page two but did not directly answer the user's question in the opening section. The task involved rewriting intros, adding concise answer blocks under clear subheadings, strengthening entity relationships, and inserting short sections that explained concepts in plain language before deeper detail. I also added FAQ-style sections where relevant because both search engines and AI systems tend to surface content that resolves a question quickly and then expands naturally. For one cluster of service pages, I invested roughly 12-15 hours across two weeks, including query analysis, content edits, internal linking improvements, and schema validation. The results became visible in about four to six weeks. Several target pages improved their click-through rate because search snippets matched user intent better, while rankings moved upward for long-tail variations that were previously unstable. More interestingly, those same pages began appearing more often in AI-generated summaries because the content contained clean answer patterns, strong topical clarity, and direct supporting context instead of long promotional copy. Traffic increased gradually rather than instantly, but impressions grew first, followed by stronger engagement and broader keyword coverage. The biggest lesson was that content written for human clarity often performs best for both search engines and generative systems because AI retrieval models reward structure, specificity, and direct usefulness more than traditional keyword repetition.
After assessing my experience with SEO and AI-generated answer performance improvements, I found that major improvements came from changing how existing content is structured into questionbased topics instead of continuing to create new posts. I performed an audit of well-ranking pages in Ahrefs and SurferSEO and implemented clear headings for answers to questions, added easy-to-read definitions, and provided relevant examples to assist AI systems finding answers to questions. Total time invested in the project was approximately 25-30 hours; this included all keyword clustering, content editing, and internal linking improvements. Improvements resulted in increased performance for long-tail keyword queries and higher existence as a content source for AI generated summaries because content became much easier to read by search engines. Many times, updating current content will generate faster return on investment than generating new pages especially when the new pages generated are already regarded as highauthority content from search engines.
One strategy that made the biggest difference was creating comprehensive topic hubs instead of isolated articles. Strategy implemented: Rather than publishing standalone posts, we build structured topic clusters where a central guide covers the main subject and several supporting articles address related questions. These pages are tightly connected through internal linking and consistent terminology so search engines and AI systems can clearly understand the topic authority. Approximate hours invested: Roughly 12 to 16 hours across the core article and supporting content. Results achieved: The approach improved rankings for multiple related keywords and increased topical authority, which led to higher organic traffic and more frequent appearances in AI-generated search summaries. In several cases, a single hub page ranked for dozens of long-tail variations after implementation. Timeframe: Meaningful ranking improvements and visibility gains usually appeared within 8 to 10 weeks. Name: Shoaib Mughal Company: Marketix Digital Website: https://marketixdigital.com.au LinkedIn: https://www.linkedin.com
Founder & GEO Consultant, The Visible Practitioner at The Visible Practitioner
Answered a month ago
I run two Substack publications. The Visible Practitioner is where I document GEO strategy. MoonInMental is where I test it. The one move that improved both traditional search and AI visibility: five exact brand terms, deployed identically everywhere. Not synonyms or paraphrases. The same strings in every bio, every post header, every image alt text, across every platform the brand lives on. "Trauma-informed astrology." "Clinical aromatherapy." "Nervous system regulation." "MoonInMental Method." "Emotional transit forecast." Before that: AI systems either couldn't locate MoonInMental or described it wrong. After: accurate, consistent descriptions across Perplexity, ChatGPT, and category searches. Traditional SEO indexes the consistency. GEO triangulates the entity across independent sources. Same action serves both. That's the infrastructure.
I work as an AI SEO Strategist at Cloudways, and I use AI tools like Profound and Spotlight to analyze gaps in how our content is discovered. Once I identify these gaps, I take action by planning updates and creating new content that fills those gaps. The most important part of this process has been restructuring existing pages so they are easily readable by both LLMs and Google. I achieve this by building topical authority using a semantic SEO framework, which ensures that each page fully covers a topic and connects related subtopics in a clear, logical way. I spend about two to three hours daily reviewing AI visibility insights, updating content, and planning new pieces. Within four to six weeks, I usually see results in the form of higher rankings, more traffic, and increased mentions in AI generated answers. This approach not only improves visibility but also ensures our content is genuinely useful and discoverable to readers and AI systems alike. Full Name: Ramsha Zaib Company: Cloudways by DigitalOcean Website: https://www.cloudways.com/en/ LinkedIn: https://www.linkedin.com/in/ramsha-zaib-252a03152/
I've had the biggest cross-over gains from rebuilding key pages into "answer-first" hubs: one page per core question, with a 40-60 word direct answer at the top, clear subheadings that match the follow-up questions, and a short FAQ section that I mark up with FAQPage and HowTo schema where it fits. I also add a small "definitions and limits" block (what it is, what it isn't, who it's for) because that text gets reused in AI answers more than feature blurbs do. I put about 22 hours into one B2B SaaS client in the payroll compliance space (content plan, page rewrites, internal links, schema, and a pass in Screaming Frog and Google Search Console). Over about 10-12 weeks, their main "what is..." and "how to..." pages moved from page 2-3 into the top 5 for 6 of 9 target queries, organic sessions to those pages rose roughly 35%, and demo requests from organic were up about 18%. In the same window, we started seeing the brand name show up in AI Overviews and ChatGPT-style answers for a handful of those questions a few times a week when we spot-checked, and "unlinked mentions" in those tools became more common than before. Josiah Roche, JRR Marketing (www.josiahroche.co), https://www.linkedin.com/in/josiahroche/
Proven GEO Strategies to Boost LLM Visibility in 2026 Hi, I'm Scott Benson, Founder and Principal Strategist at Benson SEO. With 11 years in Technical and On-page SEO and the last 2 years focused on Generative Engine Optimization (GEO), we've helped brands stay visible not just in traditional search, but in AI-driven platforms like ChatGPT, Perplexity, Google AI Overviews, and Google AI Mode. Here's what's working right now in LLM optimization (proven strategies): 1. Structured Data: LLM web crawlers reward semantically ordered HTML (when on your own website) like sequential Heading tags, and Structured Data markup to help them understand the content they are extracting. 2. Brand Mentions Over Backlinks (to an extent): Unlike Google (historically), LLMs value high-quality brand mentions from reputable sources even if they're unlinked. As a 20+ year SEO however, I'll still take the link with anchor text, and a brand mention along with it, as that's just a stronger signal in my opinion. Really we're talking about growing your quality citations. 3. Extractable Content: This goes along with the structured data, but also, simple design and user experience elements like bulleted lists, FAQs and pull quotes seem to be favored by the AI web crawlers when looking for content to extract and display in an AI search result. 4. Classic SEO: The three bullet points above are really still quality SEO. Locking down your Technical SEO is critical. Creating content that is searched for is still the primary way to get into AI search results. Create web content that can be easily accessed, extracted, and displayed in search results, no matter the application. Biggest Mistake: These AI web crawlers are not as sophisticated as Google. They behave much more like the early days of GoogleBot since they don't execute JavaScript. What I see time and again, is small and large brands are overuse JavaScript to display their content and links like main navigation. If the bots can't crawl your website because they can't "see" your content and links, then your brand will be invisible in AI applications. They rely too heavily on real-time (grounded) searches of the web, and of Google and Bing search results. Another reason to lock-down your technical SEO. Happy to provide any clarification on these points. I look forward to reading and sharing your article. https://www.linkedin.com/in/scbenson/ https://www.linkedin.com/company/benson-seo/ https://bensonseo.com/
In my experience, the single biggest factor in winning both traditional search and AI-generated answers is moving away from a site-centric mindset and focusing on cross-platform consistency and third-party validation. AI engines don't just crawl your website; they synthesize information from across the web to build a "confidence score" about who you are. If your social presence, professional profile, industry directories, third party mentions, and website all tell a slightly different story about your services or leadership, AI sees the friction and is less likely to cite you as a definitive source. Here's an example, we conducted a comprehensive audit for a high-profile corporate client. This involved mapping every public-facing mention of their brand and leadership from LinkedIn profiles and executive bios to Crunchbase and industry-specific directories. We standardized their core facts (services, mission, key executives) and used Organization and Person Schema on their main site to explicitly link these digital footprints together for crawlers. We also began developing their organic and up to date presence on platforms like Reddit, which rank well on Search and are often quoted by AI. Last but not least we began reaching out to third party outlets to increase our clients visibility and provide a fuller picture with multiple perspectives that feed the same narrative. In this case, we invested roughly 30-40 hours in the initial audit and cross-platform alignment, followed by 5 hours a month for maintenance and monitoring of third-party citations. Results: - 35% increase in "Position Zero" featured snippets for our client's core brand queries. - The brand began appearing as a cited source in Google AI Overviews and Perplexity for "best-in-class" industry comparisons where they were previously absent. - Traditional organic traffic grew by 18% as Google's trust in the site's E-E-A-T (Experience, Expertise, Authoritativeness, and Trust) improved. We began seeing shifts in AI-generated mentions within 4 to 6 weeks, while the traditional SEO rankings saw a steady climb over 3 months. AI models are remarkably quick to update their "understanding" of a brand once the corroborating signals across the web become consistent.
Name: Bianca Wyler Company: Clozze Website: https://clozze.com LinkedIn: https://www.linkedin.com/in/biancawyler One of the most impactful strategies I've implemented for improving visibility across both traditional search results and AI generated answers is structured Reddit search participation and sentiment optimization. My background includes serving as Head of Digital Collectibles at Reddit and later working as a Reddit strategist for companies focused on SEO, AEO, GEO, and online sentiment. Through this work, I've seen how Reddit discussions increasingly influence how search engines and language models interpret authority and relevance. In 2024, Google expanded its data partnership with Reddit, licensing Reddit content to help train large language models and improve search results. As a result, Reddit threads now frequently appear in Google AI Overviews, ChatGPT responses, Perplexity results, and other generative search experiences. Because these systems rely heavily on conversational data, real discussions often influence answers more than traditional blog content. The strategy involves identifying high intent search queries tied to industry topics, locating Reddit discussions ranking for those queries, and participating in those conversations in a transparent and helpful way. The focus is not promotion, but contributing expertise, structured explanations, and practical insights while naturally referencing the relevant product or platform when appropriate. Approximate hours invested: Initial research and mapping typically requires 10-20 hours, followed by 1-3 hours per week monitoring and participating in discussions. Results achieved: * Appearances in Google AI Overviews and generative answer panels * Increased brand mentions in ChatGPT, Perplexity, and other LLM responses * Higher visibility for branded and category searches * Organic traffic growth ranging from 20% to 70% depending on the industry Time to results: In some cases visibility appeared in as little as one week, while most campaigns show measurable impact within 4-12 weeks depending on competition. The key takeaway is that search is shifting toward conversation driven authority. Because Reddit is one of the largest public repositories of real user discussions, participating meaningfully in those conversations has become one of the most effective ways to influence both search rankings and generative search citations.
I'm Trevor Jones (Rhythm Collective, Knoxville) -- 13+ years building lead-gen systems for service businesses and $140M+ in tracked client revenue -- and the biggest needle-mover for both Google and AI answers has been turning "local proof" into a machine: relentless Google Business Profile + review velocity + service-area landing pages that mirror how people actually search (city + service + problem) and then backing it with consistent directory data (citations) so every source agrees. Strategy: rebuild the GBP (primary category, services, photos, Q&A, weekly Posts), launch a simple review pipeline (SMS/email right after job completion with a direct link + short script + internal owner), then publish/refresh 10-25 location/service pages tied to real job types and neighborhoods, and clean up listings so NAP/service categories are identical everywhere. Hours invested: ~25-40 hours in month one (setup + page templates + listings cleanup), then ~1-2 hours/week to keep reviews/posts/pages fresh. Results example (Knoxville-area home services client): within ~60 days we saw Maps impressions and calls climb materially, and within ~90-120 days the location pages started ranking top 3-5 for multiple "near me" and "[service] [city]" terms; the unexpected AEO/GEO win was that AI answers started pulling the same "proof stack" (rating count, years in business, service area, and the exact service phrasing from GBP/services) because it's consistent across Google, directories, and on-site pages. What most people miss: AI systems seem to "trust" consistency more than clever copy. If your business name/service categories/service area/reviews don't line up everywhere, you can rank decently and still get ignored in AI summaries because the model can't confidently reconcile who you are and what you do. Trevor Jones | Rhythm Collective | https://rhythmco.com | https://www.linkedin.com/in/trevorjonesmarketing/
**Amber Brazda | AuraSearch | aurasearch.com.au** The single biggest lever I've pulled for clients is what I call the "Attribution Flip" -- moving a specialist firm from complete absence in AI Overviews to becoming the featured source for high-value commercial queries in 90 days. The method wasn't content volume. It was engineering what I call Cognitive Snippets: structured data blocks explicitly formatted for extraction into AI-generated summaries, not just readable by humans but architecturally designed for AI retrieval. The investment was roughly 60-80 hours across technical schema implementation, content restructuring, and AI Visibility Diagnostics -- essentially auditing how generative systems perceived the client versus competitors before touching a single page. The results: citation rate went from zero to consistent first-position mentions across Perplexity and Google AI Overviews for their target queries, with referral traffic from AI platforms carrying measurably higher engagement and conversion rates than traditional organic traffic. The lesson most people miss: AI systems don't reward more content, they reward *extractable* content. If your answer isn't structured so an LLM can lift it verbatim and trust the source, you're invisible regardless of how well you rank.
I'm Jennifer Bagley, CEO of CI Web Group (ciwebgroup.com) and Co-Founder of JustStartAI.io; we run SEO + "AI search" for HVAC/plumbing/electrical at scale, so I get to see what actually moves rankings *and* gets pulled into AI/zero-click answers. Biggest needle-mover: rebuild the site + GBP into an "AI-readable entity," meaning clean service/location architecture, fast UX, and complete, consistent business data everywhere (site + Google Business Profile + directories) so engines can trust and summarize you. Task/strategy: we migrated a contractor from WordPress to a speed-optimized Webflow build, rewrote every core page to match real buyer questions (service + city + problem/intent language), and tightened the local signals (GBP service lists, posts, Q&A, consistent NAP/citations). We also added structured service/area clarity and made sure phone/city info is obvious sitewide--this is what AI systems and local packs reward when they're trying to answer "who do I call right now?" Hours invested: ~70-90 hours total (site/platform migration + IA/content rewrite + GBP rebuild + listings cleanup). Results: in ~4 months we saw 4,235 keyword ranking improvements, +188% organic traffic (939 - 2,704 sessions), +22.5% more booked jobs, and +33.8% revenue growth from organic leads; GBP improvements alone drove +8% more calls and +11% more website clicks. Timeline: first lift showed in 3-6 weeks (crawl/index + GBP engagement), with compounding gains through month 4 as content depth and local trust signals stacked. Jennifer Bagley | CI Web Group | ciwebgroup.com | LinkedIn: linkedin.com/in/jenniferbagley
Nearly 17 years running SEO for home service contractors--HVAC, plumbers, roofers, restoration companies--gives you a front-row seat to what actually moves the needle across both traditional and AI-driven search. The single biggest shift came when we stopped treating Google Business Profile as a set-it-and-forget-it listing and started treating it as a living authority signal. For a mold remediation client, we built close to 200 Google reviews and 300+ across other platforms, added regular photo updates, created a product showcase, and used Google Posts to push content consistently. That sustained GBP activity didn't just lift local map rankings--it fed the E-E-A-T signals that AI systems now pull when generating answers about local service providers. The part most agencies skip: we also reported keyword-stuffed competitor listings as map spam, regularly and systematically. Cleaning up the competitive environment compounded our client's visibility gains faster than almost any on-page tactic we ran simultaneously. We invested roughly 8-10 hours monthly maintaining this, and within 3-4 months the client was ranking in the map pack for "mold remediation," "mold inspection," and "air quality testing" in a hybrid service area. By month six, the business was being cited in AI-generated local service answers--not because we chased AI optimization directly, but because authoritative, consistent, verified signals are exactly what these systems trust.
One of the most defining improvements in my work has been the update of high-intent pages by simply putting the answer at the top using simple language then adding one example from real life and then including a small FAQ section (which typically contains 3 questions). I spent between 6 and 8 hours working on a handful of core commercial and educational pages. In updating the pages, I was able to improve the headings so that they were more closely aligned with the relevant search questions, shorten introductions, add attributed expertise, and generally made it easier for both Google and AI to pull data from pages. The results were an increase in long-tail rankings, more featured snippets, and increased likelihood of AI-generated responses corresponding to the same subject matter. Specifically, we saw an increase in organic traffic to a B2B site of approximately 18% over two months across the various updated pages and a corresponding increase in the number of AI citations within 3 to 6 weeks afterwards. Overall, what I see is that modifying existing, trusted pages has a greater effect than creating new pages when you have a short amount of time.
5+ years building Webflow sites across Healthcare, SaaS, AI, and B2B -- I've had to care deeply about how content gets discovered, whether by Google crawlers or AI models pulling answers. The single biggest move I made was restructuring client content around **structured data markup combined with conversational, question-based headers**. Instead of generic H2s like "Our Services," I rewrote them as "What does [Company] do for B2B SaaS teams?" -- exactly how someone would ask an AI. This made pages dramatically more "quotable" for generative engines. For one SaaS client, I invested roughly 40 hours restructuring their existing pages this way -- no new content, just restructured hierarchy and added FAQ schema. Within 3 months, they started appearing in AI-generated answers for mid-funnel queries, and organic traffic lifted ~28%. The insight most people miss: AI models don't reward volume, they reward **clarity of authorship and directness of answer**. A page that directly answers one specific question with structured markup will beat a 3,000-word generalist article in AI citations almost every time. **Divyansh Agarwal | Webyansh | webyansh.com | linkedin.com/in/divyanshagarwal**
We tightened page hygiene to help machines better understand intent. We removed sections with mixed intent and merged overlapping pages. We also rewrote headings to focus on one clear promise per page. A simple update cadence was added, with visible last reviewed dates and a short change log to show freshness without unnecessary details. This process took about 16 hours for a small section of the site. In three weeks, crawl efficiency improved and fewer pages competed for the same queries. By week six, we saw an increase in clicks for the cleaned topics, along with better sitelink visibility. AI-generated answers started selecting our pages more often because the structure was clear and intent was straightforward.