AI & Automation
Personas
SaaS & Startup
Time to ROI
Long-term (6+ months)
Last year, I was working with an e-commerce client who needed a complete SEO overhaul. What started as traditional keyword research quickly evolved into something unexpected - we discovered their content was already appearing in AI-generated responses from ChatGPT and Claude, despite being in a niche where LLM usage isn't common.
This discovery led me down the rabbit hole of what's now called LLM mention optimization or Generative Engine Optimization (GEO). While most marketers are still debating whether SEO is dead because of AI, I've been quietly testing how to actually get mentioned by these AI systems.
Here's what you'll learn from my real-world experiments:
Why traditional SEO still matters for LLM mentions
The chunk-level optimization strategy that actually works
How we tracked dozens of monthly LLM mentions in a traditional industry
The systematic approach to building GEO on top of SEO foundations
Why most businesses are approaching this completely wrong
This isn't theoretical - it's based on actual client work where we saw measurable results. Let me show you how AI-driven optimization is changing the game for e-commerce businesses.
Industry Reality
What everyone thinks they know about AI and SEO
The marketing world is split into two camps right now. Camp one believes SEO is completely dead because ChatGPT will replace Google. Camp two thinks AI is just a fad and nothing fundamental has changed.
Both camps are missing the point entirely.
Here's what the "experts" are typically saying:
Optimize for featured snippets - because AI pulls from these
Create FAQ-style content - to match AI question formats
Focus on authoritative backlinks - because AI trusts authority
Use structured data markup - to help AI understand content
Write conversational content - to match how people ask AI questions
This advice isn't wrong, but it's incomplete. It treats AI optimization like it's just another search engine when the reality is fundamentally different.
The problem? LLMs don't consume pages like traditional search engines. They break content into passages and synthesize answers from multiple sources. Your perfectly optimized page might get completely ignored if it's not structured for chunk-level retrieval.
Most businesses are either panicking about AI killing their traffic or completely ignoring it. Meanwhile, the smart money is figuring out how to get mentioned by these systems consistently. That's where LLM mention optimization comes in.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When I started working with this e-commerce client, my brief was straightforward: complete SEO overhaul for a Shopify store with virtually no organic traffic. Standard stuff - keyword research, content strategy, technical optimization.
But here's where it got interesting. During our initial audit, I discovered something unexpected. Despite being in a traditional e-commerce niche where most customers weren't using AI tools for research, we were already getting mentioned in LLM responses a couple dozen times per month.
This wasn't something we had optimized for - it happened naturally as a byproduct of solid content fundamentals. But it opened my eyes to a massive opportunity that most businesses are completely missing.
The client's industry was traditional retail, not tech. Their customers weren't early adopters asking ChatGPT for product recommendations. Yet somehow, our content was surfacing in AI responses when people asked related questions.
This discovery led me to start tracking LLM mentions systematically. I began testing different content structures, heading formats, and information architecture specifically for AI consumption rather than just Google ranking.
What I found challenged everything I thought I knew about content optimization. The rules for getting mentioned by AI systems are different from traditional SEO, but they're not replacing it - they're building on top of it.
Most importantly, I realized that businesses waiting for "definitive best practices" were missing the boat. Through conversations with teams at AI-first startups, I discovered everyone is still figuring this out. There's no playbook yet - which means there's a massive first-mover advantage for those willing to experiment.
Here's my playbook
What I ended up doing and the results.
After months of testing and tracking results, I developed what I call the Foundation-First GEO approach. Instead of abandoning traditional SEO for shiny new tactics, I built a layered system that works for both search engines and AI systems.
Layer 1: Traditional SEO Foundation
This might sound boring, but it's critical. LLM robots still need to crawl and index your content. Without solid SEO fundamentals, you're invisible to AI systems too. We focused on:
Quality, comprehensive content that covers topics thoroughly
Clear site architecture and internal linking
Fast loading times and technical excellence
Authoritative backlinks and domain trust signals
Layer 2: Chunk-Level Optimization
This is where most people get it wrong. AI systems don't read entire pages - they consume content in chunks. I restructured all content so each section could stand alone as a valuable snippet:
Self-contained paragraphs with complete thoughts
Clear topic sentences that work out of context
Logical information hierarchy within sections
Factual accuracy with clear attribution
Layer 3: Answer Synthesis Readiness
I optimized content structure specifically for how AI systems synthesize responses:
Used clear, descriptive headings that signal content topics
Included relevant statistics and data points
Created comparison tables and structured information
Added contextual explanations for technical terms
Layer 4: Multi-Modal Content Integration
Since AI systems are getting better at understanding different content types:
Added descriptive alt text that explains chart data
Created summary tables for complex information
Used schema markup for structured data
Included step-by-step process documentation
The key insight? Don't abandon what works. Build your GEO strategy on top of strong SEO fundamentals, not instead of them.
Foundation First
Traditional SEO remains your starting point - LLMs need crawlable, indexable content before they can mention it
Chunk Thinking
Structure content so each section works as a standalone snippet for AI synthesis
Testing Cadence
Track mentions monthly and iterate based on what topics generate the most AI citations
Attribution Ready
Include clear sources and factual accuracy to become a trusted reference for AI systems
The results weren't immediate, but they were measurable. Within three months, we tracked a consistent increase in LLM mentions across multiple AI platforms.
More importantly, the traditional SEO improvements were significant. The client went from virtually no organic traffic to thousands of monthly visitors. The LLM mentions were a bonus layer on top of solid search performance.
What surprised me most was which content performed best. The comprehensive, well-structured pages that answered complete questions got mentioned most frequently - not the keyword-stuffed content or the perfectly optimized snippets.
The timeline looked like this:
Month 1: Baseline traditional SEO improvements
Month 2: First tracked LLM mentions started appearing
Month 3: Consistent mention tracking across multiple AI platforms
Month 6: Notable increase in "brand + topic" searches
The most interesting discovery? LLM mentions seemed to have a halo effect on traditional search rankings. Pages that got mentioned frequently by AI systems also started ranking better in Google, possibly due to increased brand searches and engagement signals.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After implementing LLM mention optimization across multiple client projects, here are the key lessons I've learned:
Foundation beats optimization - Solid, comprehensive content outperforms clever tricks every time
Chunk-level thinking is crucial - Each paragraph should work independently
AI mentions correlate with search success - They're indicators of content quality, not replacements for SEO
Attribution matters more than ever - AI systems prefer factual, well-sourced content
The landscape changes rapidly - What works today might not work next month
First-mover advantage is real - Most businesses aren't even tracking this yet
It's additive, not replacement - GEO enhances traditional SEO rather than replacing it
The biggest mistake I see? Businesses treating this as either/or rather than both/and. The companies that will win are those who master traditional SEO fundamentals while experimenting with AI optimization layers.
My advice: Start tracking your LLM mentions now, even if you're not optimizing for them yet. Understanding your baseline is crucial for measuring improvement as you implement these strategies.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies looking to implement LLM mention optimization:
Focus on use-case content that answers "how to" questions
Create integration guides even without native connections
Document your API clearly with examples
Build comprehensive help documentation
For your Ecommerce store
For e-commerce stores implementing this strategy:
Create detailed buying guides for your product categories
Include comparison content between different products
Add educational content about your industry
Focus on problem-solution content formats