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AI Search & GEO

Why 43.8% of AI Citations Are Listicles — How Local Businesses Win the “Best [Service] in [City]” Game

Ahrefs analyzed more than 1 billion data points and found that listicles are the single most-cited content format in AI chatbots, at 43.8%. For a local service business, that one number rewrites the playbook: the page that wins is a ranked “best [service] in [city]” list — and you need to be in it.

Key takeaways

  • Listicles are 43.8% of all page types cited by AI chatbots (Ahrefs, 1B+ data points) — the #1 cited format.
  • AI answers the question “what’s the best X near me?” by quoting ranked lists, not homepages.
  • Two ways to win: own a comparison-style money page, and earn spots in third-party “best in city” lists.
  • A 50-niche × 30-city test showed “Best [service] in [City] 2026” pages outcited service pages by a wide margin.
  • Review volume, recency, and rating are the strongest signals for being named in AI recommendations.

What does the 43.8% listicle stat actually mean?

It means the format you publish matters as much as the words inside it. When Ahrefs analyzed over 1 billion data points to see which pages AI chatbots cite, listicles came out on top at 43.8% — more than any other content type. Not your homepage. Not your services page. A numbered list of named options.

That tracks with how people actually use AI. Nobody asks a chatbot “tell me about ABC Plumbing.” They ask “who’s the best plumber in Sacramento?” The model’s job is to return a short, ranked, justified list — so it reaches for source pages that are already shaped like a short, ranked, justified list. The format pre-answers the prompt, which makes it cheap to quote and easy to attribute.

Why listicles beat every other format for AI citation

A language model citing a source is doing pattern-matching at scale. Listicles win on three structural properties that no service page can match.

Named entities. A “best roofers” list names specific businesses. The model can lift “Acme Roofing” and hand it back as a recommendation. A homepage describes one company in marketing language — there’s nothing comparative to extract.

Ranked structure. Position carries meaning. “#2 of 7” is a signal the model can reuse. Prose buries that judgment; a list exposes it.

One-line justifications. “Best for emergency calls,” “most affordable,” “highest-rated for tile roofs” — these slot directly into an AI answer. They are the citation, ready to copy.

Which formats get cited — and which work for local businesses?

Not every cited format suits a local service business. Here’s how the major formats stack up on both AI-citation share and practicality for someone selling HVAC, plumbing, roofing, or similar services in a defined city.

Content formatShare of AI citationsSuitability for local service
Listicles (“Best X” / “Top X”)43.8%Excellent — “best [service] in [city]” is the native query
How-to & guidesStrong secondGood — builds topical authority around your service
Comparison / vs. pagesHighExcellent — cite-ready criteria tables
Review pagesModerateGood — review volume is a ranking signal
Product / service pagesLowWeak — reads as an ad, rarely cited directly
HomepagesLowestWeak — too broad for a specific recommendation

Format shares per Ahrefs’ analysis of 1B+ data points; suitability is FlashCrafter’s assessment for local service verticals.

The pattern is clear: the two formats that win citations — listicles and comparison pages — are also the two that fit local businesses best. That’s a rare alignment. Most SEO advice asks you to choose between “what ranks” and “what sells.” Here they’re the same page.

The “Best [service] in [City] 2026” money-page test

To pressure-test this for local search, we looked at comparison-style money pages across 50 niches in 30 cities — pages titled in the pattern “Best roof repair in [City] 2026,” “Best HVAC company in [City] 2026,” and so on. The question: when a chatbot is asked for a local recommendation, which of a business’s URLs gets quoted?

The comparison pages won by a wide margin. When the page contained a ranked table, named options, and a stated set of criteria, chatbots cited it far more often than the same business’s service pages or homepage. The service page is invisible to the model because it has nothing to compare; the listicle is a buffet.

The practical takeaway: every local business should own at least one comparison-style page per core service and city — a page that names the real players (you included), states why each is a fit, and carries a current year in the title. This is your comparison hub in miniature, pointed at one city.

How to build your own listicle money page

You can write a page that lists your own business and still get cited — as long as it’s genuinely useful. The bar is honesty, not self-denial. Here’s the structure that earns citations:

  • Title it like the query. “Best [service] in [City] ([year])”. Match the words people actually type and speak.
  • Name real options. List 5–8 actual local providers, including yourself. A list of one is an ad; a list of seven is a resource.
  • State your criteria up front. Response time, pricing transparency, warranty, review rating, licensing. Criteria are what AI lifts.
  • Give each entry a one-line verdict. “Best for emergency calls,” “best value,” “best for commercial jobs.”
  • Add a comparison table. Models lift tables verbatim — make the data clean and current.
  • Keep it current. Re-date and refresh annually. AI heavily favors recent pages for “best of [year]” queries.

If you want a working template, study how vertical comparison pages are built — for example, best CRM for roofers and best website builders for plumbers both use named options, criteria, and tables — the exact structure AI rewards.

How to earn spots in third-party listicles

Your own page is half the game. The other half is being named in lists you don’t control — local newspaper “best of” roundups, niche directories, “top 10 plumbers” blog posts, and review-platform rankings. These carry independent authority, so AI weights them heavily.

To get into them, work the signals those publishers and platforms use:

  • Reviews, relentlessly. Recent, detailed, high-volume Google reviews are the number-one input to who gets named. Make review generation a standing process, not a once-a-year push.
  • A complete Google Business Profile. Categories, hours, photos, services, and Q&A all feed the data layer that listicle authors and AI both read.
  • Local citations and consistency. Same name, address, and phone everywhere builds the entity confidence models need before they’ll recommend you.
  • Pitch the roundups directly. Local journalists and bloggers publish “best of” lists every year. A short, specific pitch with proof (ratings, job count, specialty) gets you considered.

Where this fits in a broader AI-search strategy

Listicles are the highest-leverage format, but they live inside a wider shift toward generative engine optimization. The fundamentals — being a well-defined entity with strong reviews, consistent citations, and content structured for extraction — apply across AI Overviews, ChatGPT, Perplexity, and Gemini alike. For the full picture, see our guide to GEO for local service businesses and the data behind the shift in our State of Local Search 2026 report.

The strategic point is simple. The query AI is answering — “who’s the best near me?” — is the exact query you’ve always wanted to win. The format has changed from ten blue links to one spoken recommendation, but the prize is the same, and listicles are how you claim it.

Want to be the business AI recommends?

FlashCrafter builds the comparison-ready money pages, local SEO, and review engine that put you in the “best [service] in [city]” lists AI quotes.

Frequently asked questions

What percentage of AI citations are listicles?

Per Ahrefs’ analysis of more than 1 billion data points, listicles make up 43.8% of all page types cited by AI chatbots — the single most-cited content format. Guides, comparisons, and review pages follow, but no other format comes close.

Why do AI chatbots prefer listicles?

Listicles map directly onto the question people ask AI: “what are the best options for X?” A ranked list of named entities with one-line justifications is structurally easy for a language model to lift, attribute, and recombine. The format pre-answers the query.

How does a local service business get into a “best [service] in [city]” list?

Two paths: build your own comparison-style money page that ranks for “best [service] in [city]”, and earn placement in third-party lists from local media, directories, and review sites. Both create citable entries an AI can quote when asked for recommendations.

Can I write a listicle that recommends my own business?

Yes — a transparent comparison page that lists you alongside real competitors, with honest criteria, gets cited because it reads like a useful resource rather than an ad. The key is genuine comparison data, not a thinly disguised sales page.

Do AI chatbots use the same lists Google ranks?

Largely yes. AI Overviews and chatbots draw heavily from pages that already rank on page one, plus the local pack and review platforms. Ranking your comparison page in classic search remains the most reliable on-ramp to AI citation.

What did the “Best [service] in [city] 2026” money-page test show?

Across 50 niches in 30 cities, comparison-style pages titled “Best [service] in [City] 2026” were cited far more often by chatbots than service or homepage URLs. Pages with a ranked table, named options, and clear criteria were the ones AI quoted.

Do reviews matter for AI listicle inclusion?

Heavily. AI models lean on review volume, recency, and rating when deciding which businesses to name. A steady stream of recent, detailed Google reviews is one of the strongest signals for being included in “best in city” recommendations.

How does FlashCrafter help local businesses get cited by AI?

FlashCrafter builds your site with comparison-ready money pages, keeps your Google Business Profile and local SEO tuned, captures leads with a CRM, and runs review generation — the exact signals AI models use to decide who belongs in “best [service] in [city]” lists.

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