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753% LLM TRAFFIC & 950% AI OVERVIEW SURGE IN 5 MONTHS
Between February and June 2025, PlushBeds experienced a sharp surge in both LLM and AI search traffic. Traffic from LLM (ChatGPT, Gemini, and Perplexity) exploded by 753%, and AI Overview results jumped 950% as Google ramped up its AI-generated summaries. And the momentum didn’t stop there: organic search traffic rose by 40% during the same period.
THE PROBLEM: THE SITE STUCK IN A PRE-AI ERA
In 2025, PlushBeds partnered with ResultFirst to launch an organic growth strategy focused on capturing long-tail, high-intent mattress queries, especially across AI-driven search experiences.
During our initial audit, we uncovered a clear gap:
- As of February 2025, traffic from AI Overview results was just 14, and LLM-driven traffic totaled only 155 sessions across platforms like ChatGPT, Gemini, and Perplexity.
- In short, PlushBeds was nearly invisible in the AI-powered corners of the search ecosystem, where users were asking questions and expecting instant answers.
- ChatGPT
- Gemini Appearances
- Perplexity Clicks
- AI Overview Answers
- 143 sessions
- 4 listings
- 8 sessions
- 14 results
KEY ISSUES WE IDENTIFIED
- Low visibility on platforms like ChatGPT, Gemini, and Perplexity
- Fragmented performance across AI-driven SERPs
- AI Overview underused despite rising impact
- No unified AI search strategy for scalable growth
- Disorganized content not aligned for AI or snippets
- Headings unclear; summaries weak; structure lacked snippet readiness
- Missing schema on key product and FAQ pages
- AI efforts siloed; focus remained on traditional SEO
SOLUTION: OPTIMIZED FOR GOOGLE
SEARCH, BUT TUNED FOR LLM
We didn’t just slap on some keywords and call it a day. Instead, we rebuilt PlushBeds’ content for humans. Our team brought in an SEO/AI strategist. Think of them as a hybrid between a data whisperer and a UX nerd.
Here’s what we changed:
- LLMs.txt Implementation: We added an llms.txt file to explicitly allow and guide crawling by LLM agents like OpenAI, Anthropic, and Perplexity for future-proofing discoverability.
- Semantic Content Engineering: We restructured long-form copy for Natural Language Understanding (NLU), not just readability:
- Integrated salient entities using Google’s NLP API, e.g., “organic latex mattress,” “GOLS certified,” and “Talalay process,” to improve contextual trust signals.
- Used Named Entity Disambiguation (NED) to associate brand terms like "PlushBeds" with specific product categories.
- AI Overview Optimization: Our experts approached AI as if it were a new kind of audience, not some robot overlord, but more like a tough bouncer at the door. If you want your content to get in, you’ve got to impress it first. No fluff, just clear, structured information.
- We added schema markup (FAQ, HowTo, Product) across top-performing product and blog pages.
- Summarized core pages with AI-friendly, snippet-ready copy blocks (TL;DR summaries, list-based answers).
- Optimized meta titles/descriptions to sound like natural answers. Made them sound more conversational hooks.Added Q&A blocks on product and blog pages using real search phrases
- Added Q&A blocks on product and blog pages using real search phrases
- Embedded natural language Q&A with likely user prompts (e.g., “What is the best organic mattress for side sleepers?”)
- ChatGPT Shopping Assistant Integration: The team actively submitted a product list to the AI shopping assistant to ensure PlushBeds' products appear in ChatGPT results.
EARLY AI TRACTION VALIDATED
OUR STRATEGY
By March, we started seeing consistent LLM traffic from ChatGPT, Gemini, and Perplexity, early signs that our AI-first strategy was paying off.
IMPACT: SPIKE ACROSS ORGANIC
AND AI SEARCH RESULTS IN 5 MONTHS
AI Overview
ChatGPT
Gemini
Perplexity
Within 5 months, tremendous growth in search visibility was recorded across LLM and AI search traffic. AI-focused strategies not only changed traffic dynamics on LLMs like Gemini, Perplexity, and ChatGPT but also positively impacted AI Overview visibility.
HOW WE TRACK LLM AND AI OVERVIEW TRAFFIC
We use a custom setup combining Google Looker Studio with Search Console and GA4 to monitor AI-driven traffic in real-time.
For LLM traffic (ChatGPT, Gemini, Perplexity, Claude, Copilot), we track:
- Sessions, engaged sessions, and key events using GA4.
- Landing page performance and session duration via Looker Studio dashboards.
- Device and location insights to fine-tune targeting
For AI Overview visibility, we rely on:
- Google Search Console to track clicks and impressions from AI-generated SERP features
- Custom filters and reports in Looker Studio to monitor page-level trends and summary appearances
Partner tools like Looker, Log Analyzer, and others help us track what’s working and what’s being surfaced across AI-first search platforms.
TAKEAWAY: DON’T JUST DO SEO. THINK GEO
This case proves what many are just starting to realize: Generative Engine Optimization (GEO) isn’t a pivot away from SEO; it’s an evolution.
When you:
- Structure content with clarity
- Align with real-world questions
- Add schema to signal meaning
- Write like a human (but format for bots)...
...you don’t just rank. You resonate across Google, ChatGPT, Gemini, Perplexity, and whatever comes next. Curious about optimizing your growth strategy for LLMs? Let’s map it out together.
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