Video Insights

How to Get ChatGPT to Recommend Your Business (Full GEO Tutorial)

Source: How to Get ChatGPT to Recommend Your Business (Full GEO Tutorial) · Published 2026-06-14 · By SEONIB

In this video

This video explains how to adapt your website for Generative Engine Optimization (GEO) so LLMs like ChatGPT recommend your business. It covers on-site techniques (robots.txt, schema markup, FAQ pages with expert quotes and statistics) and off-site strategies (reviews, brand mentions), plus how to track referral traffic using Claude, Zapier, and Google Analytics.

SEONIB's Perspective

Our take on this video

A short editorial from the SEONIB team on why this content matters.

Summary

GEO is the new SEO frontier—optimizing for LLMs like ChatGPT requires structured data, authoritative citations, and off-site brand mentions rather than traditional backlinks.

Insight

This tutorial stands out by bridging on-site technical fixes (robots.txt, schema) with off-site tactics (reviews, brand mentions) and a practical tracking method using Claude + Zapier, a workflow SEONIB also recommends for AI-driven SEO analytics.

Recommendation

Business owners and digital marketers should immediately audit their robots.txt, implement FAQ schema with expert stats, and start collecting reviews and brand mentions on high-DA platforms.

Key Insights

Key Terms

#GEO

Generative Engine Optimization: optimizing content for AI-driven answer engines like ChatGPT.

#ChatGPT

A large language model chatbot developed by OpenAI, used for answering queries and generating content.

#Schema Markup

Structured data in JSON-LD format that helps LLM crawlers understand and extract key information from a page.

#Robots.txt

A file that instructs web crawlers which parts of a site they can or cannot access.

#FAQ Page

A page listing frequently asked questions and answers, optimized for LLM extraction with quotes and stats.

#Brand Mentions

Unlinked references to a brand name on authoritative sites, boosting visibility in LLM responses.

#Google Analytics

A web analytics service used to track referral traffic, including from LLMs.

#Claude

An AI assistant by Anthropic that can be connected to Zapier and Google Analytics to automate data queries.

Frequently Asked Questions

How do I allow ChatGPT crawlers to access my website?

Edit your robots.txt file to include lines like 'User-agent: ChatGPT-User' and 'Disallow:' to explicitly permit crawling.

What is schema markup and why is it important for GEO?

Schema markup is structured data (JSON-LD) that tells LLM crawlers exactly what your page is about, making it easier for them to extract and cite your content.

How do I create an FAQ page that boosts GEO rankings?

Use AI to generate 20+ FAQs, then write answers with expert quotes and statistics. Embed the FAQ as JSON-LD schema on your site.

Why should I include expert quotes in my FAQ answers?

LLMs treat content attributed to recognized experts as more authoritative and citable, increasing the chance your answer is used.

How do statistics improve my content's chances of being picked by LLMs?

Statistics provide quantifiable data that LLMs can easily cite, making your content more reliable and extractable.

What off-site strategies help with GEO?

Collect reviews on platforms like Google and Trustpilot, and earn brand mentions on high-authority sites like LinkedIn, Reddit, and YouTube.

How can I track referral traffic from ChatGPT and other LLMs?

Connect Claude to Google Analytics via Zapier, then ask Claude to pull referral traffic data. You can also generate charts and reports automatically.

Does Instagram or TikTok help with GEO?

Not directly, because these platforms have login walls that prevent LLM crawlers from accessing content.

What is the difference between SEO and GEO?

SEO focuses on backlinks and search engine rankings; GEO focuses on brand mentions and attributions by LLMs like ChatGPT.

How should I write content for GEO instead of SEO?

Treat every paragraph as a standalone unit, use expert quotes and statistics, and avoid pronouns like 'we' or 'our' so LLMs can extract cleanly.

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