新创产品在大模型搜索中难被发现，优化SEO比直接搞AI优化更有效。
The Discovery Gap: How Product Hunt Startups Vanish in LLM Organic Discovery Queries
- 测试112个产品在2240个查询中表现，发现命名识别率高但发现类问题成功率极低。
- 大模型对新品的发现率仅3.3%~8.3%，远低于命名查询的99.4%~94.3%。
- 传统SEO和社区声量比专门的AI优化（GEO）更能预测产品可见性。
本研究调查了大语言模型（LLM）在新产品发现中的表现。从2025年Product Hunt前500名中随机选取112个初创产品，测试其在2240个查询中于ChatGPT（gpt-4o-mini）与Perplexity（sonar with web search）的表现。当用户以名称提问时，两模型识别率分别达99.4%和94.3%；但面对“今年最佳新AI工具”等发现式问题时，成功率为3.32%和8.29%。结果显示，生成式引擎优化（GEO）与实际可见性无相关性。对于Perplexity，引用域名数（r = +0.319, p < 0.001）和Product Hunt排名（r = -0.286, p = 0.002）具有预测力，清理后的Reddit数据也显示社区存在感（r = +0.395, p = 0.002）显著。结论是：应先夯实传统SEO基础，而非直接优化AI可见性。
原文摘要 · Abstract (English)
When someone asks ChatGPT to recommend a project management tool, which products show up in the response? And more importantly for startup founders: will their newly launched product ever appear? This research set out to answer these questions. I randomly selected 112 startups from the top 500 products featured on the 2025 Product Hunt leaderboard and tested each one across 2,240 queries to two different large language models: ChatGPT (gpt-4o-mini) and Perplexity (sonar with web search). The results were striking. When users asked about products by name, both LLMs recognized them almost perfectly: 99.4% for ChatGPT and 94.3% for Perplexity. But when users asked discovery-style questions like "What are the best AI tools launched this year?" the success rates collapsed to 3.32% and 8.29% respectively. That's a gap of 30-to-1 for ChatGPT. Perhaps the most surprising finding was that Generative Engine Optimization (GEO), the practice of optimizing website content for AI visibility, showed no correlation with actual discovery rates. Products with high GEO scores were no more likely to appear in organic queries than products with low scores. What did matter? For Perplexity, traditional SEO signals like referring domains (r = +0.319, p < 0.001) and Product Hunt ranking (r = -0.286, p = 0.002) predicted visibility. After cleaning the Reddit data for false positives, community presence also emerged as significant (r = +0.395, p = 0.002). The practical takeaway is counterintuitive: don't optimize for AI discovery directly. Instead, build the SEO foundation first and LLM visibility will follow.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。