13 SEO, AEO, and GEO Strategies to Improve Visibility in Traditional Search Results and AI-Generated Answers

Search is evolving faster than many businesses can keep up, with AI-generated answers now appearing alongside traditional results on major platforms. This guide compiles 13 practical strategies to improve visibility across SEO, AEO, and GEO, drawing on insights from industry experts who have adapted to these changes. These tactics work for both conventional search engines and the AI systems that increasingly shape how users find information.

Design Dual-Layer Pages For Retrieval

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.

Zeeshan Yaseen, CEO, ZeeKnows

Put The Core Response Upfront

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 making 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.

Pranjal Jain, Founder & CEO, Supablog

Use Plain English Direct Answers First

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, Ardoz Digital

Leverage Authority With Targeted Digital PR

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, SEO Strategist & Founder, Inverox Digital

Lead With Intent-Focused Openers

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.

James Tech, SEO Content, Rankviz

Restructure Content Around Reader Queries

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 question-based 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 high-authority content from search engines.

Mike Khorev, SEO and AI Visibility Consultant, Mike Khorev

Build Thematic Clusters Around Central Guides

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.

Shoaib Mughal, Founder, Marketix Digital

Standardize Exact Brand Terms Everywhere

I run two Substack publications. One where I document GEO strategy, and one 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.

Darlene Killen, Founder & GEO Consultant, The Visible Practitioner, The Visible Practitioner

Develop Subject Depth With Semantic Structure

I work as an AI SEO Strategist, 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.

Ramsha Zaib, AI SEO Strategist, Cloudways by DigitalOcean

Create Question-Led Hubs With FAQs

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, Fractional CMO, JRR Marketing

Prioritize Technical SEO For LLM Visibility

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 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.

Scott Benson, Founder & Principal Strategist, Benson SEO

Align Cross-Platform Signals And Citations

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.

Nir Shafrir, Partner, Percepto

Contribute Expertly In High-Intent Reddit Threads

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.

Bianca Wyler, Founder, Clozze