---
title: "AI citation rate by content format: what checks out"
url: https://seomadman.com/reports/ai-citation-rate-by-content-format
section: reports
published: 2026-06-16T00:00:00.000Z
modified: 2026-06-16T00:00:00.000Z
author: Adam Hafez
topics: ["AI search"]
---

# AI citation rate by content format: what checks out

## The short answer

Vendor blogs circulate exact-sounding AI citation rates by content format, but most do not trace to a real source. A real Wix study of 1,056,727 citations found listicles at 21.9%, articles at 16.7%, product pages at 13.7%. A real DeltaV Digital panel found listicles at 61% in B2B tech specifically. Three other widely repeated figures could not be verified anywhere.

## Key takeaways

- Wix's AI Search Lab analyzed 1,056,727 citations, finding listicles at 21.9%, articles at 16.7%, and product pages at 13.7% of all citations.
- DeltaV Digital tracked 25,337 citations across eight industries in 2026, finding listicles at 61% of citations in B2B tech specifically, not as a universal figure.
- A real academic paper found a 17.3% citation-rate gain from structural optimization across six engines, but an industry blog presents that finding as its own research.
- A widely repeated claim that original-data pages get a 71% citation rate, comparison pages 64%, and listicles 61% does not appear on any source it is attributed to.
- A '156% higher selection rate' figure turned up attached to three different, unrelated claims across three vendor sites, each citing a different, unfetchable source.

Five precise-sounding statistics about which content format gets cited most by AI search have been
circulating across SEO and GEO vendor blogs through 2026. Each one is quoted as if it were a single
settled fact. Checking each against the page it is supposedly published on turns up a narrower and
messier picture: two real studies with real sample sizes, one real academic paper being passed off
as proprietary industry research, and three figures that do not survive contact with their own
stated source.

## The two figures that hold up

Wix Studio's AI Search Lab published the most rigorous of the group. Researcher Tom Wells analyzed
75,000 AI answers and 1,056,727 citations retrieved from three engines, ChatGPT, Google AI Mode and
Perplexity, using deliberately non-branded prompts so the results were not skewed toward users
already naming a company. Listicles accounted for 21.9% of citations, articles for 16.7%, and
product pages for 13.7%. The methodology section discloses the model list, the prompt design choice,
and the publication date, 2026-03-23, which is enough to treat the number as a real, checkable
finding rather than a repeated slogan.

DeltaV Digital, run by VP of Operations Brandon Kidd, published a second real dataset: 21,075 AI
engine responses tracked across ChatGPT, Perplexity, Gemini, Google AI Overviews and Google AI Mode
between April 14 and July 13, 2026, yielding 25,337 citations to the 240 most-cited URLs across
eight industries. Its own page states that ranked listicles reached 61% of citations specifically
in the B2B technology services vertical, not as a figure that applies to every industry, and the
report's central argument is that citation patterns differ by industry rather than following one
universal format ranking.

A third source, cited by Search Engine Land, comes from Evertune Research: an analysis of 25,000
cited URLs drawn from the 6,000 most-cited URLs per model across six engines, spanning roughly 400
million citations. It found that 63% of the most-cited URLs pointed to listicles, and that ranked
lists made up 71% to 86% of those listicles rather than unranked lists or institutional rankings.
This is a different cut of the same underlying pattern as the Wix and DeltaV figures, format
matters and listicles lead, but it is a distinct, separately disclosed dataset, not a repeat of the
same number under a new name.

## The three figures that do not check out

**"Original-data studies get a 71% citation rate, comparison pages 64%, ranked listicles 61%."**
This exact triple circulates on multiple vendor blogs, several of which cite DeltaV Digital as the
source. DeltaV Digital's own page does not contain these three numbers as a three-way breakdown; it
contains one industry-specific figure, 61% for listicles in B2B technology services, that only
partially matches. When the pages actually publishing the 71%/64%/61% claim were checked directly,
one (MaxAEO) presented it as proprietary internal monitoring with no external dataset link, and
another (Presence AI) presented similar but not identical figures, 67% for comprehensive guides,
71% for FAQ schema, as self-published research with no linked raw data. The claim does not trace to
one real, checkable study; it traces to at least two vendors publishing similar-sounding but
non-matching numbers, neither externally verifiable.

**"Original research earns citations at 20x the rate of thin content."** Search results attribute
this figure to a synthesis of "four independent 2026 datasets," and one of the pages carrying that
framing, Digital Applied's own citation-ranking-factors report, was fetched directly. Its real
content covers a meta-analysis of several named datasets (a Zyppy 54-experiment review, an Ahrefs
75,000-brand correlation study, a BuzzStream four-million-citation analysis, and others) but does
not state a 20x multiplier anywhere in the text. Ritner Digital, another page repeating the general
claim that original research outperforms thin content, also does not state a 20x figure when
checked directly. The multiplier could not be traced to any single page that actually publishes it
with a method behind it.

**"Pages combining text, images, video and structured elements show 156% higher selection rates."**
This is the clearest case of a number being recycled. Checking three different pages that use
"156%" turned up three different, unrelated claims: one site attaches 156% to multi-modal content
selection, citing an unfetchable "AI Mode Boost 2025" report and admitting its own breakdown table
is "derived," not copied from a published figure. A second site attaches the same 156% to adding
original data or statistics to a page, citing "Authoritas 2026." A third, separately worded claim
on the same general topic instead cites SEMrush for a completely different multiplier, 1.4x, for
multi-format content. Three vendor pages, three different underlying claims, one recycled number,
and no single fetchable primary source behind any version of it.

## A real academic figure wearing an industry-research costume

One number in the original list of five does trace to something real: a 17.3% citation-rate
improvement from structural optimization, tested across six generative engines. It comes from a
genuine, fetchable paper, "Structural Feature Engineering for Generative Engine Optimization," by
Yu, Yang, Ding and Sato, posted to arXiv in March 2026. The abstract states the figure plainly and
names the six-engine test set, though it does not disclose page or trial counts in the abstract
itself.

What makes this one worth a section of its own is not the number, it is who is presenting it.
Machine Relations Research's synthesis page states outright that its 17.3% figure is drawn from
"GEO-SFE (Yu et al., University of Tokyo / University of Tsukuba / Hiroshima University / NII, arXiv
2603.29979, March 2026)," which is honest attribution. But other vendor pages in the same search
results repeat the 17.3% figure without naming Yu et al. at all, presenting it as though it were
proprietary GEO-tool research rather than an academic paper's finding. A real number, correctly
sourced in one place, is being laundered into unattributed vendor content elsewhere, which is a
different failure mode than the three figures above that were not real to begin with.

## Why we care

This specific corner of SEO content, precise percentages about which content format AI search cites
most, is currently one of the most citation-unstable areas this site has checked. Two of five
widely repeated statistics traced to real, disclosed studies. One traced to a real academic paper
being presented, in places, as if it were unattributed vendor research. Two more could not be
verified on any page that claims to originate them, despite specific search effort against several
named vendor blogs.

None of this means content format is irrelevant to AI citation. It means the specific numbers
attached to that claim are, right now, mostly unreliable. A reader who sees "71% citation rate" or
"20x more citations" quoted without a named study, a disclosed sample size, and a link that actually
contains the number, should treat the figure as unverified until proven otherwise, the same standard
this report applied to check it.

## Frequently asked questions

### Do original-data pages really get cited 71% of the time by AI search?

That specific figure, alongside comparison pages at 64% and ranked listicles at 61%, does not appear on any of the pages it circulates under. The one real, comparable figure this report could verify is DeltaV Digital's 61% listicle citation share, and that number applies only to B2B technology services, not content formats in general.

### What is the one number in this report that is both real and directly comparable across formats?

Wix Studio's AI Search Lab study, which analyzed over a million citations across ChatGPT, Google AI Mode and Perplexity and found listicles at 21.9%, articles at 16.7%, and product pages at 13.7% of citations, with a disclosed sample size and named researcher.

## Sources

1. [The content types most cited by LLMs](https://www.wix.com/studio/ai-search-lab/research/content-types-most-cited-by-llms) - Wix Studio, AI Search Lab (primary)
2. [AI search citations study: what 25,000+ citations reveal](https://www.deltavdigital.com/resources/reports/ai-citation-study/) - DeltaV Digital
3. [Structural Feature Engineering for Generative Engine Optimization: How Content Structure Shapes Citation Behavior](https://arxiv.org/abs/2603.29979) - arXiv
4. [AI search loves listicles: What 25,000 URLs reveal about citations](https://searchengineland.com/ai-search-loves-listicles-what-25000-urls-reveal-about-citations-477682) - Search Engine Land, citing Evertune Research
5. [How Content Structure Affects AI Citation Rates: The GEO-SFE Research Framework (2026)](https://machinerelations.ai/research/content-structure-ai-citation-rates-2026) - Machine Relations Research