The Off-Site GEO Playbook: Getting Recommended by Pages You Do Not Own

You can fix every product page in your store, publish flawless structured data, and still not get recommended.

That is the awkward finding underneath most of the AI visibility research published this year. When a shopper asks an assistant which product to buy, the answer is usually assembled from pages you do not control.

What the studies agree on

Siege Media ran about 1,000 bottom-of-funnel prompts, the pricing, comparison, "best X for Y" and alternatives queries, across ChatGPT, Perplexity, Gemini and Google AI Overviews between January 29 and February 4, 2026. 57,095 citations. Third-party sources accounted for roughly 80 to 95% of them. Reddit appeared in 62% of responses. YouTube in about a quarter. Product pages and homepages showed up at single-digit rates.

Omniscient Digital analysed 23,387 unique sources across 240 branded prompts on ChatGPT, Perplexity, Gemini, AI Mode and AI Overviews, published January 8, 2026. Overall split: 48% earned media, 30% commercial third-party content, 23% owned. Within the earned bucket, editorial 16%, forums and social 11%, review sites 11%, directories 10%.

The Omniscient study also does the most useful thing in this whole literature, which is break the numbers out by what the shopper asked. When people ask what customers think of a brand, 82% of citations come from earned media. When they ask a factual question about how a product works or what it is compatible with, owned content is about half the citations.

That is your operating rule. Specs are yours to win. Opinions are not.

Where the studies disagree, and why it matters

Yext published research on October 9, 2025 covering 6.8 million citations from 1.6 million queries per model across ChatGPT, Gemini and Perplexity, collected in July and August 2025. Its headline was the opposite: 86% of citations came from brand-controlled sources, split 44% websites and 42% listings, with Reddit at 2%.

Two studies, same broad question, near-inverse answers.

They are not measuring the same thing. Yext's query set is shaped by the problem Yext solves, which is local and listings visibility, and "brand-controlled" counts your Google Business Profile and directory entries as yours. Siege's set is explicitly purchase-decision prompts. The windows differ by six months in a fast-moving area. And Yext sells listings management, which does not make the data wrong but does explain the framing.

We are not going to pick a winner, because the honest answer is that source mix depends almost entirely on the question being asked, and both datasets support that.

The practical consequence: segment your prompt set by question type and check the cited domains for each segment separately. A blended average across your whole prompt set will tell you something that is true of no individual query.

Roundups and "best of" lists

Still the highest-leverage placement for a product brand, and getting less reliable.

Seer Interactive tracked more than 2 million citations on a consistent prompt set from November 2025 through February 2026. Between December and January, ChatGPT's citations to "best" and "top" URLs fell about 30%, from roughly 160,000 to 111,000, with listicle share of all citations sliding from 17.2% to 15.5%. Thirteen of sixteen industries declined. Google AI Overviews moved the other way on identical prompts, holding flat or rising.

So this is platform-specific and volatile, not a format collapse.

Seer found the surviving listicles shared four traits: recent dates on the page, ten to twenty options rather than five to eight, external validation like third-party ratings or a disclosed methodology, and consistent structure across entries. If you are pitching to be included in someone's roundup, those are the pages worth targeting.

Realistic timeline: two to four months from first outreach to being cited in an answer, assuming the publication actually updates the piece and the model re-crawls it. There is a market for paid listicle placements at a couple of hundred dollars a slot with two-week turnaround. Treat those the way you would treat a paid link, because that is what they are, and the pages selling them tend to have none of the four traits above.

Review platforms, which are mostly a matter of asking

Trustpilot, Reddit's product subreddits, category-specific review sites, and for anything sold to businesses, G2 and Capterra. Omniscient put review sites at 11% of citations overall, and they concentrate on exactly the opinion-shaped queries where your own site is worth nothing.

This is slow and mostly a matter of asking. A post-purchase email sequence that requests a review on one specific platform, consistently, for a year, will do more for your AI visibility than most content projects.

Communities, and the one way to ruin this

Reddit's weight in AI answers is not an accident of ranking. Google signed a licensing deal reported at $60 million a year in February 2024, and OpenAI signed its own that May. That content is in the pipeline by contract.

Two warnings. First, Reddit's share is unstable. Seer measured it roughly tripling over the same four-month window in which listicles were falling, which is not the behaviour of a settled system. Do not build a strategy around one platform's current weight. Second, and more important: do not astroturf. Reddit's moderators are extremely good at spotting it, and the failure mode is not that the campaign does not work. It is a permanent, indexed, well-upvoted thread about your brand being caught, which the models will happily cite for years.

What works instead is boring. Answer questions in your category as the brand, with the account clearly labelled, and be useful when your product is not the answer.

Video

Ahrefs found YouTube accounts for 5.6% of all Google AI Overview citations, up 34% over six months, and 18.2% of citations from pages ranking outside the top 100. For visual and demonstrable products, a comparison or unboxing video from someone credible can enter an answer through a door that has nothing to do with your site.

Digital PR

Editorial coverage was 16% of citations in the Omniscient data, the single largest earned category. This is the slowest and least controllable channel, and the one where results are hardest to attribute. Six to nine months before it shows up in your tracking, if it does.

The entity layer, which nobody enjoys

Underneath all of this sits something duller than any tactic.

Models build a representation of your brand from every source at once. If your product is a "trail runner" on your site, a "running shoe" on a retailer's page, and an "approach shoe" in a review, the model has three weakly connected facts instead of one strong one.

Pick your names and use them everywhere. Product names, category names, the specs and their units, your company name and its spelling. The same drop height in millimetres, the same material name, the same weight in the same unit. Do it across your site, your marketplace listings, your press materials and anything you send to a reviewer.

It is unglamorous and it compounds. It also happens to be the same work that makes generative engine optimisation function at all.

What this costs

Off-site GEO is a public relations programme wearing an SEO hat, and it runs on PR timelines. Three to nine months before the tracking moves. No dashboard will show you an ROI curve, because the mechanism runs through third parties who publish on their own schedule.

If you need results this quarter, this is not the lever. Fix your product data and your structured data first, since that work you control end to end and it moves faster.

Start off-site work anyway, in parallel, at a low intensity you can sustain for a year. The stores that show up in category answers in 2027 are the ones getting mentioned on other people's pages now.

The cheapest first step is finding out which domains the assistants already cite when they answer questions in your category, and Seokai's AI Visibility tracker will hand you that list.