GEO in Practice: How to Get ChatGPT to Proactively Recommend Your Brand

In the age of AI search, traditional SEO strategies can no longer meet the demands of brand exposure. GEO (Generative Engine Optimization), as an emerging optimization methodology, is becoming a core topic in digital marketing.

This article takes an in-depth look at how to use entity graph injection to get AI models like ChatGPT, Perplexity, and Gemini to proactively mention and recommend your brand when answering user questions. We’ll break down the core GEO methodology from technical principles and implementation steps to result validation.

First, we need to understand how AI search engines work. Unlike traditional search engines, AI models rely on entity relationship graphs in their training data to generate answers. Therefore, brands need to establish structured entity information on the internet that AI models can recognize.

The specific implementation steps include: 1) creating Schema.org structured data for your brand; 2) publishing brand-related knowledge content on high-authority platforms; 3) enhancing page machine-readability with JSON-LD and RDFa markup; 4) building a relationship graph among brand entities. Through systematic execution of these steps, our clients have seen significant increases in AI search recommendation rates within 3 months on average.