HACKER Q&A
📣 nworley

How does ChatGPT decide which websites to recommend?


For years, SEO has meant optimizing for Google’s crawler.

But increasingly, discovery seems to be happening somewhere else: ChatGPT Claude Perplexity AI-powered search and assistants

These systems don’t “rank pages” the same way search engines do. They select sources, summarize them, and recommend them directly.

What surprised me while digging into this: - AI models actively fetch pages from sites (sometimes user-triggered, sometimes system-driven) - Certain pages get repeatedly accessed by AI while others never do - Mentions and recommendations seem to correlate more with contextual coverage and source authority than traditional keyword targeting

The problem is that this entire layer is invisible to most builders.

Analytics tools show humans. SEO tools show Google. But AI traffic, fetches, and mentions are basically a black box.

I started thinking about this shift as: GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization)

Not as buzzwords, but as a real change in who we’re optimizing for.

To understand it better, I ended up building a small internal tool (LLMSignal) just to observe: - when AI systems touch a site - which pages they read - when a brand shows up in AI responses

The biggest takeaway so far: If AI is becoming a front door to the internet, most sites have no idea whether that door even opens for them.

Curious how others here are thinking about: - optimizing for AI vs search - whether SEO will adapt or be replaced - how much visibility builders should even want into AI systems

Not trying to sell anything — genuinely interested in how people here see this evolving.

  👤 theorchid Accepted Answer ✓
However, there is a lack of information when a user opens your website after interacting with AI.

Google Search Console shows the user's query if the query is popular enough and your website is in the search results. Bing shows all queries, even if they are not popular, and if your website is in the search results.

But if AI recommends your website when answering people's questions, you cannot find out what questions the user discussed, how many times your website was shown, and in what position. You can see the UTM tag in your website analytics (for example, GPT adds utm source), but that is the maximum amount of information that will be available to you. But if a user discussed a question with AI and only got your brand name, and then found your site in a search engine, you won't be able to tell that they found you with the help of AI advice.

👤 theorchid
This is especially important when launching new SaaS projects. Google does not trust new domains for the first 6-12 months. But if you publish information about your project on other sites, the AI will recommend your site in its responses. Just post a few times on Reddit, and in a week, GPT will be giving out links to your SaaS product. AI doesn't need exact low-frequency or high-frequency keywords like SEO does. AI is good at understanding user queries and giving out the right SaaS that solves the user's problem. You don't need to create a blog on your website and try to rank it in search engines. It is enough to post articles on other websites with information about your project.
👤 marcwajsberg
The attribution point is huge: the “decision” can happen in the model’s answer, and your analytics only see the last hop.

A practical mental model for recommendations is less “ranking” and more confidence:

Does the model have enough context to map your product to a problem? Are there independent mentions (docs, comparisons, forum threads) that look earned vs manufactured? Is there procedural detail that makes it easy to justify recommending you (“here’s the workflow / constraints / outcomes”)? For builders, a good AEO baseline is: Publish a strong docs/use-case page that answers “when should I use this vs alternatives?” Seed real-world context by participating in existing discussions (HN/Reddit/etc.) with genuine problem-solving and specifics. Track influence with repeatable prompt tests + lightweight surveys (“how did you hear about us?”) since last-click won’t capture it.

It feels like early SEO again: less perfect instrumentation, more building the clearest and most defensible reference for your category.