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How to get ChatGPT to recommend your product
The short answer
A recommendation is a specific moment. Someone asks ChatGPT for the best tool for a job, and the model answers with a couple of product names. If yours is one of them, you got recommended. You can’t buy that spot, and you can’t tell the model to hand it over. What you can do is stack up the evidence that makes naming you the obvious call.
What a recommendation actually is
A recommendation is the model naming your product as a good choice for one specific use case. Someone types “best invoicing app for freelancers” and ChatGPT replies with two or three names in a sentence or two. That’s the whole space. No ad slot underneath it, no sponsored line, no way to pay in. The mention goes to whichever product the model has the most reason to trust for that exact question.
So the work is mostly about evidence. You’re trying to make the answer to “is this a good pick here” easy for a model to reach, using sources it already reads.
Reviews carry more weight than you’d guess
Models lean on review sites. G2 and Capterra sit near the front of how a lot of software gets judged, and the model treats ratings and recency as trust signals. A product with a steady run of recent, positive reviews looks like a safe thing to recommend. One with a handful of reviews from three years ago looks stale, maybe abandoned.
Recency matters as much as the star count. Fresh reviews say people still use this and still like it. That’s the signal you want feeding the answer.
Give the model a reason to name you
A few other things help, on top of reviews. None of them are tricks. They’re the raw material a model needs to connect your product to a question.
- Strong, recent reviews on the sites models read. G2, Capterra, whatever covers your category. Ratings and recency both count, so keep them coming instead of collecting a burst once and letting it age.
- Pages that map your product to specific use cases and buyer types.If nothing on the web says you’re built for solo consultants, the model has no reason to name you when someone asks for a tool for solo consultants. Spell it out.
- Outside voices that back your own claims. Roundups, mentions, comparison posts, community threads. When a third party agrees with what your homepage says, the claim gets sturdier. These are your brand mentions and AI citations, and they pull as hard as anything you publish yourself.
- A clear, consistent entity. The model should never be unsure what you are. Same name, same category, same one-line description everywhere it finds you. Contradictions turn you into a coin flip.
Aim at the right questions
One common mistake: people test their AI visibility by typing their own brand name and admiring the paragraph that comes back. That tells you almost nothing. Of course the model knows about you when you hand it your name.
The prompts that matter are the unbranded ones. “Best [category] for [use case].” “Alternatives to [competitor] for [job].” Those are the questions a buyer asks before they’ve heard of you, and those are the answers you want your name inside. Write for the use case, not the brand search.
Where to start
Find out what ChatGPT says today, before you touch anything. Ask it the unbranded questions your buyers ask, run each a few times, and note who it names. A free AI visibility audit does that pass for you across ChatGPT, Gemini and Perplexity, so you’re not pasting prompts all afternoon.
Then close the gaps. Fix the reviews. Write the use-case pages. The slow, compounding version of this is just publishing content that keeps earning the mention, which is the whole idea. Recommendations follow the evidence, so your job is to make sure the evidence points at you.
Common questions
- Can I pay ChatGPT to recommend my product?
- No. There is no ad slot inside the answer and no sponsored line to buy. The mention goes to the product the model trusts for that question, and that trust comes from reviews and outside validation, not budget.
- Why does ChatGPT recommend a competitor but not me?
- Usually because the competitor has more of what the model reads: stronger recent reviews, pages that clearly match the use case, and outside sources that back their claims. It's rarely personal, just a gap in evidence.
- How specific should my use-case pages be?
- Specific enough that a model can match one to a real question. "Invoicing for freelance designers" beats "invoicing for everyone." Name the buyer and the job, so there's an obvious reason to name you when someone asks about that buyer and that job.