Ahrefs answered the headline question in 2025: 43.8% of all ChatGPT citations are 'best X' listicles. That single data point opens a bigger story about which formats win in AI search.
This study layers ProCloser's TrustRank tracking on top of the 43.8% finding, drawn from 12 months across 5 client engagements. The result names the 5 reasons listicles win, the optimal length, the platform-by-platform breakdown, and the 6 criteria a listicle must meet to compete.
Cite the findings. The dataset is CC BY 4.0, with formats at the bottom.
Key findings
Six stats that summarize the entire study (May 2025 to April 2026). Each one stands on its own.
43.8% of all ChatGPT citations are 'best X' listicles per Ahrefs research, the single most cited content format on the largest AI engine.
1,800 to 3,500 words is the listicle citation sweet spot, observed across roughly 200 AI citations tracked over 12 months.
Listicles need at least 7 entries to compete, with citation rates dropping sharply for posts with fewer than 5 named entities.
The 43.8% pattern held across all 4 industries we track, including B2B SaaS, FinTech, eCommerce, and boutique M&A advisory.
Perplexity cites listicles roughly 35% of the time based on ProCloser tracking, the second-highest listicle share after ChatGPT.
Google AI Overviews cite listicles 20% to 25% of the time, the lowest share of the major engines, balanced by a more diverse source mix.
Methodology
This study combines third-party research with ProCloser's citation tracking. No client names appear in the report. Industry labels (sports tech SaaS, home services SaaS, FinTech SaaS, eCommerce, boutique M&A advisor) are used in place of brand identifiers.
- Primary source: ProCloser TrustRank citation tracking (fixed prompt set fired monthly across ChatGPT, Perplexity, Gemini, Microsoft Copilot, and Google AI Overviews) plus format classification of every cited URL.
- External validation: Ahrefs (2025) ChatGPT citation source-format research, reporting 43.8% of ChatGPT citations come from 'best X' listicles.
- Time window: 12 months, May 2025 through April 2026.
- Sample: ~200 ChatGPT, Perplexity, and AI Overviews citations observed via prompt firing across 5 client portfolios.
- Industries: sports tech SaaS, home services SaaS, FinTech SaaS, DTC eCommerce, boutique M&A advisory.
- Format tags: each cited URL tagged as listicle, ultimate guide, product page, documentation, forum, news, or other. Listicles sub-classified by length tier and entry count.
For full methodology, see the ProCloser methodology page. For broader engine context, see The State of AI Search 2026.
What this study is not: a representative sample of every listicle on the open web. It is a focused look at which format characteristics correlate with citation, validated against Ahrefs' larger third-party number. Findings are directional for similar industries and program types.
1. The 43.8% finding, and why listicles dominate
Ahrefs published the headline in 2025: 43.8% of all ChatGPT citations are 'best X' listicles. No other format comes close. Guides, product pages, documentation, forums, news, and academic papers split the remaining 56.2%.
The pattern repeats across our 5 clients. Across ~200 ChatGPT and Perplexity citations during the 12-month window, listicles dominated every industry. The sports tech SaaS client's most-cited URL was a 'best [category] tools' listicle. The boutique M&A advisor client's was a 'best [region] advisors' list. The FinTech SaaS client's two top URLs were both year-stamped 'top X' lists.
The dominance is structural. Models prefer listicles because the format fits the query. When a user asks for 'best M&A advisor for a $20M business,' the model is itself a listicle generator on the answer side. A source already in listicle shape has the lowest synthesis cost. For definitions of citation, source, and listicle in AI search, see our GEO and AEO Glossary.
2. The 5 reasons listicles win in AI search
Five structural reasons explain why the 43.8% pattern is so consistent across engines and industries.
i. Direct answer format (LLMs prefer enumerated answers)
Generative engines output answers as lists for any query involving comparison, ranking, or selection. A listicle is already in that shape. Converting a 4,000-word essay into a 5-bullet ranked list is far harder.
ii. Comparative framing (LLMs surface multiple options when asked 'best of')
Most commercial-intent queries are framed as 'best of' or 'top X'. Models surface a slate of named options, not a single recommendation. Listicles deliver the slate in one source. Any query with 'best,' 'top,' 'compare,' or 'vs' tilts toward a listicle.
iii. Citation efficiency (one listicle equals multiple brand mentions)
When a model cites a listicle, it can name 5 to 15 brands inside the answer while linking to a single URL. The model has a budget for source URLs per answer. Listicles let it name many entities within that budget.
iv. Schema-friendly (ItemList markup is a direct LLM signal)
ItemList JSON-LD is a structured list with a defined order. Models reading a page with valid ItemList markup get rank, name, and URL of every entry without parsing prose. Pages with valid ItemList get cited at higher rates than identical pages without it. For schema-layer guidance, see our LLM Seeding Strategy guide.
v. Update cycles (annual refreshes are a freshness signal models reward)
Listicles get year-stamped titles and annual refreshes. 'Best CRMs 2026' replaces 'Best CRMs 2025'. That cadence is a freshness signal, especially for live-web engines like Perplexity and ChatGPT search. A listicle updated quarterly outcites a static guide.
3. Listicle length analysis: where the citations live
Format alone is not enough. Length matters too. Across the 200 citations observed, the citation rate by length tier was distinctly non-linear.
| Length tier | Citation rate | Why |
|---|---|---|
| Under 1,000 words | Rarely cited | Models flag thin lists. Entries lack the supporting context the model needs to summarize fairly. |
| 1,000 to 1,800 words | Occasionally cited | Mid-range. Cites land on stronger entries with detailed descriptions, get skipped on shallow ones. |
| 1,800 to 3,500 words | Highest citation rate (sweet spot) | Each entry has 2 to 4 paragraphs of supporting context, pricing, pros and cons, best-for. Models can cite confidently. |
| 3,500+ words | Diminishing returns | Models tend to extract only the top 3 to 5 entries. The rest of the post does not earn citations even though it is on the page. |
The takeaway: aim for 1,800 to 3,500 words total, each entry receiving 200 to 350 words. Below, the post reads thin. Above, the model has moved on.
Entry depth beats total word count. A 2,400-word listicle with 10 well-described entries gets cited more often than a 4,000-word post with 3 deep entries and 7 thin ones.
4. By industry: observed citation patterns
The 43.8% pattern holds across every industry we track, but the anchor query patterns differ. Each industry has its own dominant 'best X' phrasing, which dictates the kind of listicle that earns citations.
SaaS and B2B tech
'Best [category] tools' and 'best [category] software' listicles dominate. Both SaaS clients ranked their top-cited content under URLs of this shape. The model is structurally biased toward 'tools' and 'software' framing for B2B tech queries.
Financial services and M&A
'Best [region] advisors' and 'best [size-bracket] firms' listicles dominate. The M&A advisor client's top-cited URLs were 'best M&A advisors for [size]' and 'top [region] firms 2026'. Geographic and size-bracket qualifiers matter more here than any industry we track.
DTC eCommerce
'Best [product] for [use case]' listicles dominate. Use-case-framed listicles beat category-framed by a wide margin, because the model uses the qualifier to narrow the answer.
FinTech SaaS
'Best [tool] for [business size]' listicles dominate. The FinTech SaaS client's two highest-citing pages were 'best [tool] for small businesses' lists. The model rewards listicles that match the size and use-case framing buyers use.
The cross-industry pattern: qualifiers matter. A generic 'best CRM' listicle competes against thousands of identical pages. 'Best CRM for solo financial advisors' competes against far fewer.
5. Platform-by-platform listicle citation breakdown
The 43.8% number is ChatGPT-specific. Every other AI engine cites listicles too, but at different rates.
| Engine | Listicle share of citations | Why this rate |
|---|---|---|
| ChatGPT | 43.8% (Ahrefs research) | Largest engine, most listicle-heavy. The headline number that anchors this study. |
| Microsoft Copilot | ~42% (ProCloser tracking) | Tracks ChatGPT closely because both pull from the Bing index. Listicle share is nearly identical. |
| Perplexity | ~35% (ProCloser tracking) | Cites listicles plus Reddit threads at roughly equal rates. Listicles still the largest single category. |
| Gemini | ~24% (ProCloser tracking) | Source mix mirrors AI Overviews. More diverse than ChatGPT, but listicles still over-indexed vs broader web. |
| Google AI Overviews | 20% to 25% (ProCloser tracking) | Most diverse mix. Pulls from documentation, forums, news, and YouTube, but listicles still meaningful share. |
The pattern: Bing-index engines (ChatGPT, Copilot) cite listicles at the highest rates. Google-index engines (Gemini, AI Overviews) pull from a more diverse mix. Perplexity sits between, with strong listicle citations balanced by Reddit and news. Our State of AI Search 2026 report covers the broader engine mix.
Strategic implication: if your priority is ChatGPT and Copilot, listicles are the highest-leverage format by a wide margin. If your priority is AI Overviews and Gemini, listicles still help but you also need documentation, forum participation, and structured guides.
6. The 6 criteria for a citation-worthy listicle
Not every listicle gets cited. Across the 200 citations observed, six criteria appeared consistently in cited listicles and were missing from those that were not.
- Specific entity names, not generic descriptions. Cited listicles name brands directly. Listicles that describe option categories without naming them get skipped. Models cite to extract names.
- At least 7 entries. Listicles with fewer than 5 are flagged as thin. The 7 to 12 range gets cited the most. Above 15, the model extracts only the top tier and the long tail does not earn citations.
- Clear ranking criteria stated up front. Cited listicles open with how entries were chosen ('ranked by [metric]', 'selected based on [criteria]'). This answers the implicit user question: why these and not others?
- Year-stamped title. 'Best X 2026' beats 'Best X' for citation rate, especially on live-web engines. The year stamp signals freshness, the single biggest variable for inclusion in current answers.
- ItemList JSON-LD schema present. Pages with valid ItemList get cited more often than identical pages without it. The schema gives the model rank, name, and URL of every entry without parsing prose.
- Methodology disclosure. A short paragraph explaining how entries were ranked. Both a trust signal and a citation hook. Models cite the methodology paragraph as supporting evidence for the ranking.
Hit all six and your listicle competes for citation share. Miss two or more and the listicle reads thin to the model regardless of how good it is for humans.
How to cite this study
Dataset published under CC BY 4.0. Attribution required, derivatives allowed.
Kozar, T. (2026). The listicle citation study: Why 43.8% of ChatGPT citations are 'best X' posts. ProCloser.ai. https://procloser.ai/blog/listicle-citation-study/
@techreport{kozar2026listiclestudy,
title = {The Listicle Citation Study: Why 43.8\% of ChatGPT Citations Are 'Best X' Posts (2026)},
author = {Kozar, Tania},
year = {2026},
month = {May},
institution = {ProCloser.ai},
url = {https://procloser.ai/blog/listicle-citation-study/},
note = {Meta-analysis combining Ahrefs (2025) ChatGPT citation research with ProCloser TrustRank tracking, May 2025 to April 2026}
}
<blockquote> 43.8% of all ChatGPT citations are 'best X' listicles per Ahrefs research, and ProCloser.ai tracking across 5 client engagements confirms the pattern holds across Perplexity, Microsoft Copilot, Gemini, and Google AI Overviews. Listicles in the 1,800 to 3,500 word range with at least 7 named entries get cited the most. <cite>Kozar, T. (2026). <a href="https://procloser.ai/blog/listicle-citation-study/">The Listicle Citation Study</a>. ProCloser.ai.</cite> </blockquote>
"43.8% of all ChatGPT citations are 'best X' listicles. The format wins because models prefer enumerated, comparative, citation-efficient sources, and a single listicle delivers what the model needs in one URL. The criteria for a citation-worthy listicle are tighter than most teams realize." Tania Kozar, Director of Partnerships, ProCloser.ai. The Listicle Citation Study 2026.
About this analysis
ProCloser.ai is a GEO agency for B2B SaaS, FinTech, eCommerce, and professional services brands. The TrustRank methodology combines fixed-prompt citation tracking, GA4 referral attribution, and on-site GEO work. Read the full methodology or visit Tania Kozar's profile.
This study draws on 5 anonymized client engagements plus the publicly cited Ahrefs (2025) research. Findings are directional. Methodology questions: contact ProCloser.ai.
Frequently asked questions
Why do AI engines prefer listicles?
AI engines prefer listicles because the format aligns with how models structure answers: enumerated, comparative, and citation-efficient. One listicle delivers multiple named entities in a single source, which lets the model satisfy a 'best of' query without stitching together five separate pages.
What's the ideal listicle length for AI citation?
Listicles in the 1,800 to 3,500 word range get cited most often in our tracking. Below 1,000 words, posts are flagged as thin. Above 3,500, models tend to extract only the top entries and skip the rest. Aim for depth on each entry, not raw word count.
Does this only apply to ChatGPT or all AI engines?
All five major AI engines cite listicles disproportionately, but the rate varies. ChatGPT sits at 43.8% per Ahrefs. Perplexity runs around 35%. Google AI Overviews trends 20% to 25%. Microsoft Copilot tracks ChatGPT closely because of the shared Bing index. Gemini patterns mirror AI Overviews.
Can a non-listicle page get cited at the same rate?
Rarely. Definitive guides and original research can match listicle citation rates for very specific query intents, but for any 'best of', 'top X', or 'compare options' query, listicles win the citation share by a wide margin. For commercial-intent queries, the listicle format is structurally favored.
How long does it take for a new listicle to start getting cited?
Live-web engines (Perplexity, ChatGPT search) can pick up a new listicle within 2 to 4 weeks if the page is indexed and earns at least one quality citation. Base-model citations tied to training updates take 3 to 9 months. Across our portfolio, meaningful listicle citation gains land 60 to 120 days after publication.
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ProCloser.ai runs free GEO audits for qualified B2B SaaS, FinTech, eCommerce, and professional services brands. We measure your current AI citation rate across ChatGPT, Perplexity, Copilot, Gemini, and AI Overviews, then build a roadmap to lift it (including which listicles to publish or get included in).
Book Your Free GEO AuditLast updated: May 4, 2026. Author: Tania Kozar, Director of Partnerships at ProCloser.ai. Tania leads partnerships and editorial across ProCloser's GEO programs for M&A advisory, FinTech, and B2B SaaS clients. The findings in this study come from her work managing client engagements alongside the ProCloser analytics team.