How to get recommended by ChatGPT

You get recommended by ChatGPT by being described clearly, accurately and positively on pages it can find and trusts: your own site, and above all the third-party pages it cites for your buyers' questions. There is no setting, tag or payment that guarantees it. There is a sequence of work that improves the odds.

This guide covers that sequence, in the order it tends to pay off.

How does ChatGPT decide what to recommend?

ChatGPT can answer from what it learned in training, and it can also search the web and read what it finds. When it searches, it works from the pages it retrieves, and it may cite them. For questions like "what's the best tool for X", the answer usually draws on pages that discuss the category: roundups, reviews, comparisons, forum threads and vendor sites.

Beyond that, keep claims modest. How it weighs sources is not fully public, and it can change. The stable lesson is that being on the pages it reads matters. The underlying mechanics are described in how ChatGPT decides which brands to recommend, and the split between memory and search in training data or live search.

What should you do first?

Start by finding out where you stand, then work backwards from the evidence.

1. Write down 10 to 20 questions your buyers ask, in their words, with no brand names. How to find the questions your customers ask AI shows how.
2. Ask ChatGPT each one, signed out, more than once. Save the answers. This is covered in how to check if ChatGPT recommends your business.
3. Record who is recommended, and which pages are cited.

That last list is your map. The brands recommended tell you who you compete with. The pages cited tell you where the competition is decided.

Why do the cited pages matter so much?

Because assistants lean on them. If ChatGPT's answers to your key questions keep citing the same few roundups, and those roundups list your competitors but not you, then the quickest path to a recommendation runs through those pages, not through another round of edits to your homepage.

For each cited page, ask:

• Is it a page you can be added to (a roundup that accepts submissions, a directory, a community list)?
• Does it list products like yours, with what criteria?
• Is the information about your competitors current, and could yours be too?

Earning a place on such pages takes real work: a product that fits, an honest pitch and sometimes a review or a correction. See how to get onto the roundup and review pages AI relies on.

What should your own site do?

Your site is the source of record. Make it easy for a reader, and a machine, to understand what you are.

• Say what you are, plainly, near the top. One sentence: what it is, who it is for, what it does. A homepage built on slogans is hard to summarise. See why your homepage confuses AI assistants.
• Make facts findable. Pricing, features, integrations, locations, and who you are not for. Specific, checkable statements are easier to quote than adjectives.
• Write pages that answer real questions. A page titled with the question a buyer asks, answered in the first paragraph, is easy to use.
• Publish honest comparison content. A comparison page assistants trust is fair to competitors and says when you are not the right choice.
• Let the crawlers in. If your robots.txt blocks the relevant crawlers, parts of the web search path may not reach you. See AI crawlers and robots.txt.

What about reviews and community mentions?

Third-party voices carry weight because they are independent of you. Real customer reviews, discussions in forums and communities, and mentions in the press all contribute to how a brand is described across the web. You cannot manufacture these honestly. You can make it easy for real customers to leave them and take part where your buyers already ask questions. More in reviews, forums and community answers in AI recommendations.

What should you avoid?

Some tempting shortcuts do harm or achieve nothing.

• Writing fake reviews or planting posts. It is dishonest, platforms act against it, and a damaging discovery costs more than any gain.
• Stuffing pages with the phrases you want to be known for. Assistants summarise meaning. Repetition does not make a page more useful.
• Hiding text for machines only. It adds nothing a reader values.
• Chasing a single run. One answer is one draw from a range. Answers change every time you ask, so act on patterns.

How will you know it is working?

Measure the same question set on a regular schedule and compare like with like. Track how often answers recommend you, how often they cite your site, and whether the third-party pages that matter now list you. Treat a change as real only when it exceeds ordinary variation. The routine is in how to track AI visibility over time.

Expect progress to be gradual. A new page must be published, found and read before it can matter, and recommendations vary even after that.

What if you are a new or small brand?

Smaller brands rarely win the broadest questions, where assistants name the best-known names. The openings are in narrower ones: a specific use, a budget, a type of buyer. Write pages for those exact situations, say plainly who you are for, and look for specialist lists and communities where your kind of buyer asks. Specific needs are where a specialist can be the clear answer.

If you want a starting point, the Citewake checker shows how a site looks to AI assistants today. The measures behind that kind of tracking are explained in the methodology.