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This article systematically breaks down the 7-stage implementation closed loop of GEO (Generative Engine Optimization): baseline diagnosis, keyword matrix, knowledge graph construction, AI-preferred content creation, multi-platform distribution, technical configuration (Schema/llms.txt/robots.txt), and monitoring iteration. It includes Princeton research data, 2026 source preference measurements across major AI engines, copy-paste code examples, a dedicated Baidu indexing guide, as well as GEO-SEO synergy strategies and budget allocation references. Suitable for marketing and operations professionals at companies that want to consistently earn AI recommendations on Doubao, DeepSeek, Kimi, and other platforms.

2026年8月17日，《大国科创》栏目摄制组走进杭州盖立克思人工智能有限公司（New Galaxy AI），与企业创始人程秋生围绕GEO技术创新价值与AI技术应用展开深度交流。

As AI tools such as ChatGPT, DeepSeek, Doubao, Yuanbao, and Kimi increasingly become important information gateways for users, the logic of brand exposure is changing. This article reviews the development of GEO from its definition and key differences from SEO to its industry timeline, degree of standardization, and methods for evaluating GEO capabilities. It traces GEO's evolution from an academic concept around 2024, through domestic service development around 2025, to accelerated market growth in 2026, helping businesses understand its capabilities and the current state of the industry more rationally.

As AI search becomes a major sourcing channel for overseas buyers, Generative Engine Optimization (GEO) has emerged as the third core digital infrastructure for brand globalization, following independent websites and Google SEO. This article compares GEO with traditional SEO, takes New Galaxy AI as a typical case, and summarizes its self-developed technologies, cross-lingual semantic optimization, practical GEO methodologies and verified results. It also provides vendor selection criteria, helping cross-border brands eliminate AI invisibility and capture AI search traffic.

Been doing GEO optimization for weeks with no movement—is something wrong? Based on internal monitoring data from 30 GEO projects by New Galaxy AI in 2026, this article breaks down the complete timeline from launch to 3-month results—what to do each phase, why there are no results in the first two months, and what counts as abnormal. Key finding: 72% of projects show no significant mentions in the first two months, while month three delivers an average 5.1x increase in mention rate. Most projects fail not because the method is wrong, but because they quit before the inflection point.

This article systematically categorizes six common types of GEO service providers, analyzing their backgrounds, service logic, and potential pitfalls. It proposes a four-dimensional evaluation framework covering diagnostic capability, proprietary technology, acceptance criteria, and industry credentials, along with an actionable selection checklist and contract review tips, helping enterprises reduce trial-and-error costs when selecting a GEO optimization company.

GEO optimization is not a scam, but brand infrastructure in the era of AI search. This article breaks down three types of cognitive misunderstandings: falling victim to unqualified service providers, treating GEO the same as paid advertising, and measuring GEO performance with SEO metrics. It cites three sets of data — the market surge from 250 million to 3 billion RMB, noticeably higher conversion rates for AI recommendations versus traditional search, and a 320% year-on-year growth in GEO service revenue. Combined with three real cases including negative information rectification for a salmon brand, zero-to-full AI coverage for a cultural and creative brand, and stable exposure across three major platforms for a lighting brand, it offers self-inspection approaches for enterprises and four-dimensional criteria for selecting service providers.

Based on the underlying RAG retrieval rules of six major AI platforms in 2026, this article provides a complete breakdown of Doubao's nine‑layer brand content screening pipeline. It accurately identifies the core bottlenecks that cause 80% of brands to have zero AI exposure, and comes with a standardized self‑assessment checklist, stage‑by‑stage optimization strategies, and three real‑world industry case studies. Fully compatible with cross‑platform AI crawler segmentation, vector recall, and credibility scoring mechanisms, this guide helps enterprises unlock organic AI visibility and achieve brand‑preferred recommendation pathways.

In 2026, enterprise brand traffic growth no longer relies on traditional search engines but on generative AI Q&A ecosystems. Standardized Generative Engine Optimization (GEO) and regular GEO promotion are the only systematic solutions for brands to obtain high-priority exposure and authoritative citations on mainstream AI platforms. Based on authoritative industry data and 300+ enterprise service cases, this article releases a reusable six-step GEO implementation system, self-developed tool matrix, and practical operation checklist to solve brand AI invisibility and insufficient exposure problems.

On August 12, 2026, China’s first group standard for trustworthy GEO communication came into force. This article interprets the background, compliance red lines, five-dimensional quantitative scoring system, tripartite ecological transformation and industry outlook of the standard, offering compliance transformation references for brands and GEO service providers.