How to Get Recommended by ChatGPT: Get Your Products Into the “Best Of” Lists It Cites

Here is how to get recommended by ChatGPT: get your product into the pages ChatGPT reads before it answers. For "best X" prompts, those pages are mostly third-party "best of" lists, reviews and forum threads. Find the lists AI assistants cite for your category, earn a place on them through editorial pitches, affiliate programs and product samples, and make your Shopify store the clearest source of facts about each product.

That is slower than rewriting your own pages. It works for the same reason word of mouth works: an AI answer reflects what several independent sources agree on. This guide is the process we use for Shopify brands, including the parts most guides skip: how to find the lists that matter, what editors need from you, and how to handle samples when a product costs $3,000 and ships on a pallet.

Why "best of" lists decide what ChatGPT recommends#

When someone asks ChatGPT for the best pellet grill or the best sauna under $5,000, it usually searches the web, reads a handful of results and writes a summary with citations. For commercial prompts, the results it reads are dominated by listicles, review roundups, comparison articles and discussion threads.

A "best of" list is a ready-made answer to that prompt. It names several products, says who each one suits and usually comes from a publisher the model has seen cited many times. If three of the five pages ChatGPT reads name the same four grills, those four grills are the answer. Your product page is one source saying your grill is good. A list is an independent source saying it's one of the best.

Google's AI Overviews and AI Mode behave the same way on product searches, which we cover in how stores get cited in AI Overviews. Whether an assistant answers from training data or live search, the sources decide the answer.

Step 1: Write down the prompts your buyers use#

You can't find the lists that matter until you know which questions you want to be the answer to. Build a prompt set of 30 to 50 real buyer questions, drawn from Search Console queries, Google's People Also Ask boxes, Amazon search suggestions, sales calls and support tickets.

Use the words buyers use: sizes, room types, price caps, climates, skill levels. "Best e-bike for a 250 lb rider" pulls a different set of sources than "best e-bike".

Step 2: Find the lists AI assistants cite for your category#

Run every prompt in ChatGPT with search on, Perplexity, Google AI Mode and Gemini. Each one shows its sources: ChatGPT puts citations inline and in a Sources panel, Perplexity lists them above the answer, and Google shows links beside the AI Overview or AI Mode response. Log every cited URL in a sheet.

Answers vary between runs, so run each prompt two or three times and count how often each URL appears. Then add the Google top 10 for each "best" query, because many of the pages AI assistants cite also rank on page one. After 30 prompts a pattern shows: a small group of domains carries most of the citations in your category. Those are your targets.

Step 3: Sort the lists by who decides#

Not every list can be won the same way. Group your targets by who controls them, because that decides your approach.

Prioritize lists that are cited often, that you have a real reason to be on (a price band they don't cover, a feature nobody else has), and that have a reachable human behind them.

Step 4: Build a reviewer kit on your Shopify store#

Editors check facts, and so do AI assistants. If your price, dimensions or warranty differ between your product page, your Amazon listing and a press sheet, you've given everyone a reason to leave you out.

Create a page in Shopify (Online Store > Pages) at something like /pages/press or /pages/reviewers, and include:

• Brand facts in one paragraph: who you are, where you're based, how long you've made this product, where you ship from and where returns go.
• A product line table: model, price, three key specs, who it's for.
• One honest difference per product against the products already on the lists you're targeting.
• Downloadable high-resolution photos and spec sheets.
• Warranty, returns and shipping by country.
• Affiliate program details and a sign-up link.
• A sample or loaner request form and a named person with email and phone.

The same facts should live as text on each product page, with Product structured data carrying price, availability, brand and GTIN, so machines read what editors read.

Step 5: Pitch the people who update the lists#

Most "best of" lists are updated on a schedule, and many show an "updated" date and an author. Commerce teams plan seasonal guides well ahead: holiday gift guides, Black Friday roundups, spring grilling and outdoor season. Pitch before the update, not after.

A pitch that gets read is short and points at a gap in their list:

Subject: [Product] for your best [category] list, test unit available

Hi [Name],

I read your [list title] (updated [month]). You cover [two or three
products] but nothing for [the gap: a price band, a use case, a size].

We make [product], a [one-line difference] at $[price].
Spec sheet, photos and warranty terms: [link to reviewer page]

If it's useful, we can ship a test unit. No obligation to cover it,
and you can keep or return it. We also run an affiliate program on
[network] if you use one.

[Name], [role], [phone]

A few rules we hold to:

• One pitch and one follow-up per person, a week or two apart.
• Lead with their reader's gap, not your feature list.
• Never offer product or money in exchange for a link or a placement. Google's spam policies name "sending someone a product in exchange for them writing about it and including a link" as link spam, unless the link is marked rel="sponsored" or rel="nofollow".
• Take a no gracefully and ask when they next update the list.

Step 6: Run an affiliate program editors can use#

Much commerce content is paid for by affiliate commissions. An editor choosing between two similar products may lean toward the one that pays, and some independent review sites only cover products with a program. An affiliate program doesn't buy a placement. It removes a reason to leave you out.

• Use the networks your targets already use. Hover over the links on the lists in your sheet; the redirect domains show which networks they work with.
• Set a commission that's normal for your category. Editors compare.
• Match the cookie window to your buying cycle. A $3,000 sauna is researched for weeks, so a one-day window pays nobody.
• Pay on net sales, after returns, and say so up front.
• Test tracking end to end through Shopify checkout before you announce it.

Affiliates must disclose the relationship to their readers. That's their obligation, but don't ask anyone to hide it.

Step 7: Samples and loaners for high-ticket products#

Reviewers can't test a pool table from a spec sheet. For expensive, heavy products, a structured sample or loaner program is usually what separates brands that get tested from brands that get listed from press releases, or not at all.

• Decide who qualifies. Lists in your citation log, sites that test in-house, and YouTube reviewers with a history in your category.
• Write down the terms. Test period, who pays return freight, whether they can keep the unit, and that coverage is not guaranteed and must be honest.
• Plan freight. Freight and white-glove delivery for saunas, greenhouses and pool tables costs real money; ship from a warehouse in the reviewer's country.
• Use open-box or refurbished stock for loaners where the reviewer agrees.
• Do the math. If one placement on a list cited for your top prompts drives even a handful of sales a year, one sample unit at landed cost pays for itself.

The FTC's Endorsement Guides FAQ says reviewers who receive free products should disclose it where it could affect how readers weigh the review. Build that into your terms. Our work with high-ticket brands leans heavily on this step, because long research cycles make third-party reviews decisive.

Paid placements: what's allowed and what's worth it#

Once you start outreach, you'll get offers: pay a few hundred dollars and join our "best X" list. Some are legitimate sponsored content, many are pay-to-play lists that include anyone who pays. Before you pay, check four things:

1. Does the page rank on Google's first page for the list's main query today?
2. Does it appear in your citation log? If no assistant cites it, it won't move AI answers.
3. Is the placement disclosed as sponsored, and are links marked rel="sponsored"? Undisclosed paid placements are an FTC problem, and paid links without the attribute break Google's link spam policy.
4. Does the list show real testing? A list of 40 products with identical blurbs is weak evidence for a human or a model.

Also know Google's site reputation abuse policy: third-party content published on a host site mainly to exploit that host's ranking signals can be demoted. Paid "best of" pages on big domains are exactly the kind of content that policy targets.

And ChatGPT itself: OpenAI began testing ads in 2026 and says ads are kept separate from answers and don't influence them. You can buy an ad. You can't buy a recommendation.

Chinese brands: clear the trust bar first#

Editors are cautious with brands they don't know, and more cautious with Chinese brands they can't verify. Their questions are practical: will returns work, will the warranty be honoured, will the company exist in two years?

Answer those before you pitch. A warehouse and returns address in the market, English support during the customer's working day, one brand name used identically on Amazon, Shopify, packaging and social profiles, and an About page that shows the factory and the people. Zack has worked with Amazon-first brands from Shenzhen for more than eight years, and the ones that get onto Western lists fastest look like any other well-run brand to a busy editor. Our brand trust work for Chinese brands covers the setup, from Organization schema to the About page.

When a list mentions you badly#

Sometimes your citation log shows you're already on a list, as the product not to buy, or with wrong facts. Treat the cases differently.

• Wrong facts (old price, discontinued model, wrong warranty): email the author with the correction and a link to the page on your site that confirms it. Editors fix errors because errors hurt them too.
• A fair negative verdict: don't argue with it. Check whether the problem is real. If you've since fixed it with a new model, a better warranty or faster shipping, tell the author before the next update and offer a unit to retest.
• A verdict based on one bad experience: offer to resolve that experience, then ask for a retest. Don't ask for removal.

AI assistants repeat these pages, so one outdated verdict on a well-cited list can follow you into a great many answers. Correcting it is often worth more than a new placement.

Measure whether it's working#

• Rerun the prompt set monthly. Track the share of prompts where you're named and which sources the assistants cite.
• Count placements on your target lists, and note which ones AI assistants start citing.
• Track referral traffic from AI assistants and list sites. Our guide to tracking ChatGPT traffic in GA4 and Shopify has the exact setup.
• Watch branded search. People often read a recommendation, then Google your brand. Search Console's branded queries filter shows the trend.

Expect months, not weeks. Lists update on their own schedule, and AI answers follow the sources. Our AI visibility audit gives you the baseline to measure against, and the wider playbook is in how to rank in ChatGPT.