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Head of Marketing - Earned Media
Digital Marketing | SEO
Traditional SEO targets Google rankings and website clicks. This approach...
By Narender Singh
Jun 29, 2026 | 5 Minutes | 
| 
Traditional SEO targets Google rankings and website clicks. This approach targets mentions in AI answers where readers may not click through.
On Google, you want the top spot. In ChatGPT or Gemini, your win is a mention. AI answers often solve problems fully, creating zero clicks even when your brand is cited.
| Aspect | Traditional SEO | LLM SEO |
|---|---|---|
| Goal | High Google rank | Cited in AI answers |
| Success | Click rate | Citation count, share of voice |
| Content | Long, keyword-heavy | Short, question-answer |
| Key Signal | Backlinks, authority | Training data, Bing index |
| Timeline | 3-6 months | Days (RAG) to months (training) |
Don't abandon traditional SEO since it helps LLM visibility too. But Google-only strategies miss a new visibility layer that matters.
LLMs use two distinct pathways to find content online. Both matter for appearing in AI answers about SEO for LLMs today.
LLMs train on web snapshots from Common Crawl, a non-profit archive. ChatGPT's data includes snapshots through April 2024. Gemini and Claude use different datasets. Brands with years of good content build presence in training data through normal indexing.
This is a long-term signal. New sites won't appear in training data right away at all.
RAG means Retrieval-Augmented Generation for finding content. When ChatGPT's live search is on, it queries Bing's index in real-time. Perplexity does the same. This happens fast, at query time.
A brand on Google but not on Bing is invisible to ChatGPT's live search. This path is fastest since you don't wait for model training.
Not all content is quotable by LLMs at all. Keyword-heavy text yields nothing useful. LLMs can't pull quotes from it. Clear, modular content gives LLMs snippets they can use.
This is the fastest step to boost LLM visibility with zero content changes needed. ChatGPT's live search uses Bing's index. If you're not there, you're absent from live answers.
Steps:
Most Google sites also appear on Bing. But verification and sitemap submission speed things up fast.
This is the highest-impact step with the least work needed overall. FAQ schema from H3 headings shows up in 100% of top pages. Most CMS platforms like WordPress make FAQPage schema from H3s under FAQ H2. No developer help needed here.
Your CMS builds the schema automatically. You write Q&A. LLMs use Q&A pairs more easily than dense text.
LLMs quote what sounds quotable and natural to readers. Keyword-heavy text doesn't sound quotable at all. Questions, numbered steps, and clear terms give LLMs words they can use.
Compare these examples:
Not quotable: "Search engine optimization requires integration of on-page and off-page strategies for maximum visibility."
Quotable: "LLMs find content two ways: training data from Common Crawl and live RAG. Your content needs both to show up."
The second example is clear and human-sounding. LLMs can quote it as-is without editing.
Brand mentions in trusted publications boost your training data. Brands cited often across good sources get higher LLM confidence. This is why why backlinks remain a core authority signal. PR and backlink work help by raising your brand presence in training data.
Most teams skip this step, which is why LLM work produces no visible ROI. You can set up baselines today without paying for tools.
Set up filters in GA4 to catch traffic from chat.openai.com, perplexity.ai, gemini.google.com, and copilot.microsoft.com. These referrals show an LLM cited your site and users clicked through.
Steps:
Before buying LLM tools, set a baseline for your brand. Pick 10 to 20 queries you care about most. Run each in ChatGPT, Gemini, and Perplexity weekly. Log:
This takes 20 minutes per week and shows real patterns.
Share of voice is the percent of AI answers to your queries where your brand appears. If your brand shows in 40% of 10 ChatGPT responses, your share is 40%.
Track this with Google rankings to see the full picture. A rank 3 on Google with 0% AI mentions shows a gap to close.
LLM SEO, Generative Engine Optimization (GEO), and Answer Engine Optimization (AEO) all chase AI citation. They come from different groups but use the same tactics overall. Optimize for AI citation instead of Google rank.
RAG retrieval can surface your content within days after Bing indexes it. Training data citations take much longer (months to years) since LLMs retrain rarely. Expect quick wins from Bing setup. Expect slow gains as your brand enters training data.
Adapt what you have instead of starting over. Check top pages: Are they easy to read? Do they have FAQ schema? Are they in Bing? Most changes are structural like adding FAQ sections. Start with top-traffic pages.
No. They work together as complementary approaches. Content on Google often shows in LLM answers. Bing indexing (which powers ChatGPT live search) usually means Google rank too. Do both.
Read your content aloud to yourself. If it sounds natural and clear, LLMs can quote it. If it sounds machine-made, LLMs will rephrase or skip it. Write for people first, SEO second.
Branded query growth tells LLMs you're legit. Raise branded search volume in Bing Webmaster Tools to boost LLM mentions. This ties SEO for LLMs to brand-building and PR work.
Partially yes. AI helps with keyword research, outlines, and audits. See our guide on how to automate SEO with AI tools. But LLM citation work stays manual. You read LLM output, test your content, and tweak based on quotes.
It makes backlinks pay off more than before. Backlinks boost your training data, which boosts LLM citations. A backlink from a big publication signals trust to both Google and LLMs. Your how long SEO authority signals take to compound timeline applies here too.