Buying Guides and AI Visibility: 63% of Top Citations

Buying guides take most of the citations to highly cited media pages. In a 5W study of the 50 most-cited earned-media pages in each of five industries, 63% of 39,739 citations went to best-of lists, reviews, comparisons or shopping sections, and 79.4% in beauty. For communications teams, product coverage now reaches shoppers and AI engines at once.

What did the study find about AI and buying guides?

The study found that buying guides take most of what AI engines cite from highly cited media pages. 5W analyzed citation data for financial services, beauty, tools and home improvement retail, smart home and supplements between January 1 and November 7, 2026. The data is 5W's analysis using Profound's tools. In each industry we took the 50 pages with the most earned-media citations, 250 pages in all.

Of the 39,739 citations to those pages, 63.0% went to recommendation-style pages. They were 51.6% of the pages, which means the average buying guide drew about 194 citations while the average editorial or explainer page drew about 122. The 63% describes this group of highly cited pages, not every AI citation, and the full results are in 5W's buying guides study.

Source: 5W's analysis using Profound's tools, citations tagged earned media, January 1 to November 7, 2026.

How much of beauty's AI citations go to buying guides?

Beauty has the highest share, with 79.4% of citations to its 50 most-cited pages going to buying guides. Of those 50 pages, 36 are buying guides. NBC Select had five pages with 1,530 citations, Elle had six pages with 1,080, and the single most-cited beauty page was NBC Select's best under-eye patches guide with 795 citations. Health.com's best lip balms page followed with 579, and Vogue Scandinavia's best under-eye patches page had 523.

In my view this is encouraging for beauty PR, because beauty teams already work with the editors who write these guides. The study suggests those editors' pages are among the most visible pages in AI answers for the category.

What does WSJ Buy Side tell PR teams?

WSJ Buy Side shows that one outlet can hold two different kinds of placement. In financial services, all 18 Wall Street Journal pages in the top 50 sat under wsj.com/buyside, drew 2,539 citations and held 37.8% of the top-50 finance total. That is at least 72.6% of WSJ's 3,495 earned-media citations in the category across all engines.

Axios reported at Buy Side's 2022 launch that it would have its own writers and editors, a team completely separate from the newsroom, and affiliate partners including Skimlinks, Red Ventures and Amazon. The study did not re-verify that structure today, so I read it as a description of how Buy Side began. The practical lesson is that a brand in a Buy Side guide has a placement AI engines cite often, and it is a different placement from a newsroom story.

Do buying guides earn more citations than other pages?

On average, buying guides earned more citations than other pages in the study. They were 51.6% of pages and 63.0% of citations, and the gap was positive in every industry. It was largest in smart home, at 11.7 percentage points, where a few very high pages such as security.org's best smart home guide, with 2,655 citations, drive it. In tools and retail the two shares were nearly equal.

Ten of the 15 most-cited pages in the study are buying guides. In my view, that is a clear signal that guides deserve their own line in a communications plan.

Which outlets are cited for explainers instead?

Some outlets earn their citations with explainers, and that is an opportunity too. Wired had three pages in the smart home top 50 with 1,228 citations, and none were buying guides: how to choose a smart home ecosystem (471), how to set up a smart home (457) and what Matter is (300). Kiplinger had 28% recommendation-style pages across six finance pages, and SmartAsset's three top pages had none.

For these outlets, expert commentary and original data are a better fit than a product pitch. The study suggests brands can work in both lanes if they match the pitch to the page type.

How do buying guides change consumer PR budgets?

Buying guides suggest that product PR and AI visibility are converging, because pages written for shoppers are among the pages AI engines cite most. Consumer campaigns have often kept product reviews, shopping guides, brand features and reputation coverage in separate lines. This data gives shopping-oriented placements a stronger case for their own line in a plan aimed at AI visibility.

• Send products to qualified reviewers and testing publications.
• Build relationships with the editors who write buying guides and comparison pages.
• Keep product specifications, availability and pricing accurate and easy to find.
• Map which publications AI engines cite for specific buying questions in your category.
• Track the exact URLs that appear in AI answers, not only publication names.

The earlier EPR analysis of PR versus SEO and AI citations and the beauty brand GEO framework cover related ground for teams planning this work.

What should communications teams do next?

Communications teams can act on this quickly, because every step builds on work PR teams already do well.

1. List the buying guides for your category by running the prompts buyers use in each AI engine and recording the exact URLs cited.
2. Pitch the guide's editors, not only the news desk, with product access, test data, specifications and a clear disclosure of any relationship.
3. Check which section of each outlet is being cited, since a commerce section and a newsroom can have different editors and rules.
4. For explainer-led outlets, offer expert commentary and original data.
5. Repeat the URL check on a schedule, because a guide is one page that can change or drop out of citations.

These are strategic implications, not demonstrated causal effects. The study does not show that earning a buying-guide placement will cause an AI engine to recommend a brand. Teams that want help running the check can start with 5W's AI visibility agency practice.

How does this study build on earlier 5W research?

This study looks one level below 5W's AI Engine Citation Gap research, which ranked outlets by engine and industry and found that ChatGPT, Perplexity and Google AI Overviews cite different outlets. That study also found that at least 78% of WSJ's ChatGPT citations in financial services sat under Buy Side. The buying guide study asks which pages are cited and what kind of page each one is, and it covers every industry and engine combined.

The Trade Press AI Index 2026 on EPR looks at which trade publications the engines cite, and EPR's summary of Muck Rack's earned media findings covers the broader share of AI citations that comes from earned media.

What are the study's limits?

The study is a first page-level read, and I want to be direct about its limits. It covers only the 50 most-cited pages per industry, drawn from five categories 5W already monitors, with one category per industry. Gemini returned no citation data. Supplements is a small sample, and five off-topic pages in the smart home list were left in.

Pages were classified from their URL paths. The path rule gives 63.0%, and a manual review of all 250 URLs that adds 18 likely roundups raises it to 70.7%. Neither method opened the pages themselves.