How do you get recommended by ChatGPT?

1. Be readable — necessary, not sufficient

If the systems cannot read your pages, nothing else can help. Three failures account for most cases.

Client-side rendering. Vercel’s measurement found GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot and PerplexityBot did not execute JavaScript. If your content is assembled in the browser, they receive an empty page. Test this by disabling JavaScript and reloading — if the page is blank, you have found your problem, and it is a larger one than anything else on this list.

Crawler access. Check what your robots.txt actually serves, not what is in your repository. Hosting providers and CDNs increasingly inject managed rules that block AI crawlers by default, and the file you wrote may not be the file being served.

Entity clarity. One consistent company name, one canonical description, coherent Organization markup, and consistent details across the site and any external profiles. Systems resolve entities; ambiguity costs you.

This layer is a floor. Completing it does not make you recommendable — it makes you eligible.

2. Say something a competitor cannot say

This is where most of the outcome is decided, and it is not a technical task. If your description is "AI-powered platform for enterprise", a model has no basis to prefer you and every reason to produce the category sentence with your name attached.

The test we apply: write the claim, then substitute your closest competitor’s name. If it still reads as true, it is not a position — it is a category description, and it will not survive contact with an assistant.

Specificity means nouns a competitor cannot borrow: a named method, a defined segment, a measurable threshold, a certification, a constraint you accept that others do not. Adjectives are free, which is exactly why they carry no information.

3. Get it corroborated — the part that decides it

A model discounts what you say about yourself, because everybody praises themselves and that signal is worthless at scale. What it weights is agreement between independent sources.

So the programme is: get the specific claim repeated, accurately, by publications, analysts, communities, comparison sites, partners, customers and the catalogues that list your category. Not with your marketing language — with the claim itself, stated in their words.

This is slow. It is also the reason the outcome is defensible: no software product performs it, and it cannot be bought convincingly. Purchased mentions and syndicated filler are detectable, increasingly by the systems themselves, and a corroboration record built from them is a liability with a delay on it.

4. Publish things worth citing

The most efficient way to get corroborated is to publish work other people need to reference: original research, real benchmarks, a documented method, data nobody else has. When someone cites it, your claim travels with the citation and you did not have to ask.

This is also the one asset in this market that cannot be counterfeited. In a category full of manufactured proof, a study someone can check is worth more than a page of logos.

5. Measure, and be honest about variance

Sample the answers deliberately, on a schedule, with the same question set — because absence produces no signal anywhere else. Run each question several times: these systems vary between sessions, and a single run is an anecdote.

Then accept the limits. You will not be able to attribute revenue to a change in an AI answer with any rigour, and a vendor who offers to is guessing with a spreadsheet.