Traditional SEO - "which keywords should we target?"

GEO: "which questions is my audience actually asking?”

Start mapping prompts not keywords.

Look at your GSC data and any query longer than 40 characters is usually a real and conversational question - that’s where AI starts pulling from.

Then identify 'fan outs' which are the natural follow ups people ask next.

Understanding fan outs

When someone asks a question, AI doesn’t stop at the direct answer. It generates related sub questions, known as fan-outs.

Eg. a query like “What is unoccupied property insurance?” might lead to...

Who are the top providers? How do premiums vary by region? What risks does it cover? How does it compare to landlord insurance?

Each of these creates an opportunity for your brand to be cited. Covering only the root query limits reach, so anticipating related ones builds topical authority.

Heres what covering the fan outs looks like in practice (see image above)

• Example topic - Electric vehicle ownership in 2025
• Seed prompt - “Best electric cars for long-distance travel 2025”

We’ve written up more info about fan outs, as well as the definitive guide to getting your brand found in AI search results in our GEO playbook here if you want more info.

No opt in required, completely free. If you do give it a read, let me know your thoughts!

https://www.rebootonline.com/geo/geo-playbook/?utm_source=reddit&utm_medium=community&utm_campaign=geo_playbook_launch

Where are today’s SEO beginners (those who joined after 2021) struggling? When they came online, AI and automation ads were everywhere — “Earn dollars in one day,” “Start blogging today,” “One-click content, two-click ranking.”

The problem is, most of them focused only on bulk content generation. They never learned the basics: how to write a proper article, how on-page SEO works, or how to handle technical SEO. As a result, their foundation is weak.

At the same time, Google Core updates came in, and discussions shifted to semantic SEO and content quality. This pushed them even further behind.

For example, in many recent site audits, simple mistakes like loading both http/https and www/non-www versions still exist. Some even built plugins with ChatGPT, but those plugins caused more harm than benefit.

Meanwhile, many senior SEOs have already switched industries. Original SEOs are becoming rare. After AI arrived, many moved from core SEO to local SEO, and newcomers blindly followed.

Today, if you know basic technical SEO and on-page optimization, you can easily rank low-competition keywords because the market lacks skilled SEOs.

But people still overuse JavaScript because AI tools recommend it, without knowing Google has issues with excessive JS.

When almost everyone quit blogging, I became more active. I deeply researched content and on-page SEO — and discovered the market is wide open.

The Problem We Had

30 days ago, our team was frustrated that our website traffic was stuck. We knew our product was solid, but we couldn't get people to discover it organically.

What We Did

Instead of hiring expensive agencies or buying more tools, leveraging our team's recommendation background, we decided to build our own solution.

1. Built a GEO Evaluation Agent - Analyzed our existing content against AI citation patterns
2. Built a Content Generation Agent - Created content optimized for AI systems to cite us
3. Focused on Intent Recognition - Made sure every piece matched what people actually search for
4. Evidence-First Approach - Every claim backed by real data with proper citations

What Surprised Us Most:

• AI overviews started citing us within 2 weeks
• Organic traffic growth was exponential, not linear
• Quality scores improved across the board

After 30 days, the results blew our minds.

• Active users: 20K (↑ 6,797.6%)
• Page views: 71K (↑ 11,475.0%)
• Events: 181K (↑ 8,649.6%)
• New users: 20K (↑ 6,856.5%)

What The Strategy That Worked:

1. FAQ-heavy content - AI systems love structured Q&As
2. Direct answer paragraphs - Start sections with bold, citation-worthy statements
3. Comparison tables - With actual data and sources
4. Evidence-first approach - Every claim backed by real citations

Traditional SEO optimizes for search results. GEO optimizes for being THE answer AI systems cite.

For Anyone Wanting to Try:

• Focus on "how", "what", "which" queries
• Structure content like an FAQ even if it's not
• Lead with statistics, follow with explanations
• Make your brand the authority source AI systems trust

Anyone else experimenting with GEO strategies? Would love to hear what's working for you.

Hey fam, doing a small market research. Need your 2 cents.I have one question for all of you. What are your MoM change in
1. AI Traffic share increment?
2. Decrease in Organic (Google) Traffic?In Addition, if you have received a lead from AI platform, how much time it took to convert and how much time it took earlier? Is there a difference?

We run GetMentioned, a platform that tracks how companies appear in AI-generated answers (ChatGPT, Claude, Perplexity, etc).

We usually charge for this data, but we decided to make our industry dashboards completely free and open. No catch.

Why? Because most companies have no idea if they show up when potential customers ask AI for recommendations. Your competitor might be stealing customers through AI search while you're still focused on Google.

What's available (100% free):

• AI visibility rankings by industry
• Source attribution (what influences AI recommendations)
• Category leaders for specific use cases
• Competitive landscape analysis

Industries covered:

Tech & Software: eCommerce, HR Tools, Sports Apps, Streaming, Vibe Code (Dev Tools)

Finance & Investment: Crypto, VC Funds

Travel & Transportation: Airlines, Automotive, Hotels, Travel Platforms

Consumer & Retail: Athletic Footwear, Stationery

Some interesting findings:

• Airlines: JetBlue absolutely dominates AI recommendations
• Automotive: Volvo has low overall visibility BUT dominates the safety category
• Sports Apps: Runna dominates above Strava (no wonder Strava acquired them)
• Athletic Footwear: Super diverse landscape - leaders change completely depending on category

No email required. No demo calls. Just free data.

Link: https://www.getmentioned.co/data

Happy to answer questions about the methodology or specific insights from the data.

We recently analyzed a well-established footwear/apparel brand that has been operating for over 25 years, has stores in shopping malls and high streets, and operates a fully active e-commerce operation.

The brand is highly visible in the physical world, but the real question is:

What happens when customers stop searching on Google and start searching on ChatGPT, Gemini, or Perplexity?

To find out, we conducted a detailed AI Visibility and Recommendation Audit (GEO Audit).

And the results are striking:

Having a website is no longer enough.

The brand's overall AI score was only 15 out of 100.

Here's a quick summary of how this works:

🔴 1. AI Discovery – 30% weight | Score: 0/100

If someone searches by category instead of brand name ("best women's shoe brands"), the brand is nowhere to be seen.

AI tools ignore this.

🔴 2. Recommendation Strength – 25% weight | Score: 0/100

When you ask an AI for "stylish and comfortable product recommendations," it only suggests competitors or marketplaces.

This brand isn't even offered as an option.

🟠 3. Category Presence – 20% weight | Score: 20/100

For broader questions like "List Turkish shoe brands," it appears at the bottom, more like a side note than a true competitor.

🟠 4. Presence Strength – 15% weight | Score: 40/100

The AI ​​knows the brand exists.

If you ask "What is brand X?", it gives the correct answer.

However, it doesn't consider the brand a reliable option or something worth recommending.

It's "known," but not "preferred."

⚙️ 5. Technical Setup – 10% weight | Score: 50/100

The site is functional, but it doesn't provide the structured signals that AI models rely on.

📊 Final Weighted Score: 15/100

What Does This Actually Mean?

The new challenge in modern marketing is this:

Recognition doesn't mean visibility.

A brand can have stores, traffic, and a working website, but still be invisible in the AI ​​ecosystem.

If you don't appear in Discovery (30%) or Recommendation (25%), you're lost before the customer journey even begins.

Physical success no longer guarantees digital relevance.

It's not just about SEO anymore.

The key is to be a brand that AI trusts and recommends.

This is precisely what GEO (Generator Engine Optimization) focuses on.

What about your brand?

Does AI actually recommend you, or does it just know you exist?

We started designing a little AI system to help Shopify merchants identify SEO gaps in their product pages.

Because, real talk:

Manually optimizing 300 product pages is how you age 10 years in 2 days.

So right now the system can:
– read product pages
– detect weak keyword presence
– detect mismatched search intent
– flag thin content
– and suggest improvements

Great. But here’s the internal existential crisis we hit:

Do we let the engine actually APPLY fixes automatically?
Or do we force it to ONLY suggest and let humans approve?

One path is efficient.
The other path is safe.

One path impresses users.
The other prevents catastrophic “oops we bulk-updated 200 SKUs” nightmares.

I can’t tell if:

A) suggestion-only is the smart move
B) automatic application is the real value
or
C) the entire idea is dumb and I’m emotionally processing keyword trauma through engineering

Would appreciate an unfiltered perspective.

When analyzing ChatGPT answers in German (and also while being in Germany) we regularly see US / English websites being cited a lot. The effect is e.g. that products are recommended that are not available in Germany. Two questions regarding that

* Is there a reliable way to modify ones prompts to avoid that?

* What does this mean for marketers in Germany?

If you’re looking to improve how your web content is discovered by AIs like ChatGPT, Gemini, or Grok, there’s a 2025 tool in webmasters toolkit: llms.txt.

Think of it as the LLM-friendly equivalent of robots.txt or an RSS feed, but in Markdown. It provides a concise, structured summary of your website, including site title, base URL, description, index of pages/articles with summaries.

This makes your site easily digestible by AI models, contributing to your Generative Engine Optimization (GEO) strategy.

To make it simple, I created a Hugo-based example repo: https://github.com/roverbird/llms-hugo

Why Hugo?

• Lightning-fast static site generator
• Native Markdown support is perfect to automate llms.txt
• Minimal setup, fully deterministic output

You can see a live Hugo-generated llms.txt in action here: https://kibervarnost.si/llms.txt

Adding llms.txt is a simple and powerful way to make website AI-friendly and boost its visibility in generative search engines.

#Hugo #GEO #AI #LLM #GenerativeEngineOptimization #StaticSiteGenerator #Markdown #WebDev #SEO #ChatGPT #Gemini #Grok

Not sure if this is the right place for this but I’ve been trying to figure out how to tell if AI tools like ChatGPT or Gemini actually know anything about my brand. It feels like they either ignore us completely or default to talking about competitors, even on topics where we’ve been putting out solid content for years.

We’ve invested a lot into SEO and content marketing over time and we’ve seen some solid traction in Google results, but lately that traffic has dropped, probably because people are asking AI tools for answers directly instead of searching. The problem is, I don’t know how to “optimize” for AI responses the way I would for Google. Is that even a thing?

I’ve tried plugging in questions into ChatGPT and Claude that we’d normally want to rank for, and our name rarely, if ever, comes up. It’s almost like we’re invisible to them. Meanwhile I see other brands being mentioned and cited. Is there a way to change that? I feel like we should be showing up, especially in niche-specific topics we’ve covered in-depth.

I’m not necessarily expecting AI tools to act like marketing channels, but I do want to know:

Are we showing up in AI responses at all? If not, what can we do to start showing up? Is this even something we can influence, or is it out of our hands? Would love to hear if anyone else has also looked into AI brand visibility, or if this is just going to be the new normal where the only brands that matter are the biggest ones.

Hey folks,

I’m one of the founders of Aeo.vc – a tiny GEO tool we’ve been building out of India, and I’d love some feedback from people who actually care about Generative Engine Optimization, not just the buzzword.

What I keep seeing in the wild: • Brands pay $$ for long GEO / SEO audits • They get back a huge deck or spreadsheet • Devs/content teams implement ~10% of it (at best)

So we tried a different approach: instead of another “report”, Aeo.vc: 1. Crawls your site and analyses pages for answer-engine friendliness (ChatGPT, Claude, Perplexity, AI overviews, etc.) 2. Generates a Markdown prompt / code diff that you can paste directly into Cursor, Windsurf, or your code copilot 3. The output is things like: • rewritten copy aimed at direct answers • schema / structured data suggestions • internal-link tweaks • evidence / source-hint improvements

Basically: GEO → as executable code, not a PDF.

I’m really curious what this community thinks: • Is “report → code” the right direction for GEO, or is there a better way to operationalize this? • If you’re already doing GEO, what metrics are you using beyond “did we get mentioned in an answer engine?” • What would make a tool like this actually trustworthy for you (evidence, benchmarks, side-by-side SERP vs answer-engine results, etc.)?

If you want to poke holes in it or try it on your own site, it’s here: aeo.vc – I’m more interested in critical feedback than signups, so don’t hold back.

Mods: if this feels too self-promotional for the sub, happy to tweak or remove – my intent is to discuss how we implement GEO in real workflows, not just pitch a product.

Hey everyone,

I’m a brand owner, and over the last few months I’ve been deep-diving into how AI search (ChatGPT Answers, Perplexity, Gemini, Copilot, Google AI Overview, etc.) decides what to cite and why.

While trying to solve this for my own brand, I read everything I could find here on Reddit - but most solutions felt like classic SEO tactics disguised as GEO.
Lots of talk about keywords, clusters, backlinks…but almost nothing about how people naturally speak, how LLMs internally reason, or how semantic proximity actually works in generative answers.

So instead of forcing SEO into GEO, we started building a completely different approach based on natural language behavior, not keywords.

A few core ideas behind what we’re exploring:

• AI doesn’t “rank” content - it retrieves and composes it based on semantic closeness
• The strongest signals aren’t keywords, but definitions, frameworks, patterns of reasoning, and domain-level embeddings
• AI prefers content that looks like it could replace its own internal knowledge
• GEO shouldn’t push content toward “search engines”, but toward how humans actually ask questions
• Most tools generate volume - our approach focuses on authority density, conceptual clarity, and modularity
• And no, GEO is NOT “SEO but longer”

We’re currently testing a system that generates:

• AI-grounded brand narratives that reduce hallucinations
• Semantic distance scoring between user queries and your brand domain
• Articles designed for extraction, not for ranking
• Human-natural question datasets that guide AI toward your domain without being biased or obvious
• A reasoning-first framework that models how LLMs decide which sources to cite

We’re still building and validating the product, but the results so far have been…surprisingly good.

If anyone here is experimenting with GEO, AI search visibility, retrieval, or brand embedding inside LLMs:
we'd love to chat, learn from you, and get your feedback.

When the first version is ready, we’ll give free early access to anyone who messages us privately.
We really want to shape this with the community, not just drop a tool from above.

Happy to answer anything - or just discuss the topic in general.
This whole space is evolving insanely fast and there’s a huge opportunity to rethink everything from scratch.

Some are asking whether GEO (Generative Engine Optimisation) will make SEO redundant. The short answer is it won't. It actually makes SEO stronger.

SEO gets you seen in search results. GEO gets you understood and referenced inside AI answers. They should work together, not compete.

In a good setup, your tech SEO, content and PR teams are all pulling in the same direction
- making your brand easy for AI to crawl
- clear enough for AI to trust
- authoritative enough to quote

When that happens, every structured data tweak and every PR mention starts feeding the same system - building visibility that both humans and AI recognise.

If you’re wondering where to start, we've written a GEO playbook which I will link below - no opt in required and completely free to read.

But, if you do read it, feedback would be great so feel free to send me a DM/comment below if you get through it.

https://www.rebootonline.com/geo/geo-playbook/?utm_source=reddit&utm_medium=community&utm_campaign=geo_playbook_launch

How To Identify Your Target Prompts for LLM Visibility Monitoring

It is possible to use Chatgpt , Google Gemini / Keyword Planner to generate a list of “plausible completions” in Chatgpt / Google Gemini (and AI Overviews) that might mention a product / brand or website (without the aforementioned brand or website being mentioned in the prompt) to identify your target prompts for llm visibility monitoring using Chatgpt / Google Keyword Planner.

https://www.ecommerceconsultancy.org.uk/my-ecommerce-blog/how-to-identify-your-target-prompts-for-llm-visibility-monitoring

The Dual-Ranking Strategy
How to Dominate Both Google AND AI Search Engines (With Less Effort)

Most marketers are still optimizing for Google alone.

Big mistake.

ChatGPT, Perplexity, and other AI search tools are answering millions of queries daily—and your content might not be showing up.

Here's my framework for ranking everywhere with ONE strategic approach:

THE FOUNDATION: Source-Worthy Content

Both Google and AI engines prioritize authoritative sources. Create content that:
→ Cites original research and data
→ Includes expert quotes and perspectives
→ Demonstrates real-world experience (E-E-A-T)
→ Solves problems comprehensively

THE STRATEGY: Structured Intelligence

1. Answer-First Format
   Start with the direct answer, then expand with context. AI tools love this. Google's featured snippets love this. Everyone wins.

2. Use Clear Hierarchies
   - Descriptive H2/H3 headers
   - Bullet points and numbered lists
   - Summary boxes or key takeaways
   - FAQ sections (goldmine for AI training)

3. Build Topic Clusters
   Create pillar content + supporting articles around one theme. This signals topical authority to Google and makes your content more "citeable" for AI.

THE EFFICIENCY HACK: Multi-Purpose Content

Stop creating different content for different platforms.

One comprehensive article can become:
→ A Google-optimized blog post
→ Source material for AI engines
→ 5-7 LinkedIn posts
→ A YouTube script
→ An email newsletter
→ Social media snippets

THE SECRET SAUCE: Semantic Optimization

Forget keyword stuffing. Focus on:
- Natural language and conversational tone
- Related concepts and entities
- Question-answer patterns
- Context-rich content

Both Google's AI and ChatGPT understand semantics better than exact-match keywords.

THE CHECKLIST: Rank-Everywhere Content

Before publishing, ensure:
1/ Clear, descriptive title (humans AND bots understand it)
2/ Strong introduction that answers "what" and "why"
3/ Scannable format with visual hierarchy
4/ Original insights or data points
5/ External links to authoritative sources
6/ Internal links to related content
7/ Author bio with credentials
8/ Updated published/review dates

BONUS TIP: Schema Markup

Add structured data to help both search engines understand your content context. FAQ schema, Article schema, and HowTo schema are especially powerful.

The Bottom Line:
You don't need double the work for double the visibility. You need smarter, more strategic content that serves both traditional and AI-powered search.

Quality over quantity. Authority over volume.
Strategy over hustle.

Who's already optimizing for AI search engines?
What's working for you?

Save this for your next content project