How Can Short URLs Boost Your AI Search Visibility?

What did Local Dominator's new data actually claim?

Local Dominator, a local-SEO and AI-visibility platform, published data on July 28, 2026 arguing that short, single-segment URLs are the single most-cited URL type across major AI engines (Local Dominator, July 28, 2026).

The dataset came from the company's own AI Tracker product: 2.78 million AI-cited URLs pulled from 188,000 scans, filtered down to 1.95 million citations tied to real business sites, and tracked across ChatGPT, Gemini, Google AI Mode, Perplexity, Claude and Grok.

Inside that filtered set, short single-segment URLs captured about 29% of citations, ahead of homepages (15.79%) and blog or resource content (14.24%). Founder Eldar Cohen framed the takeaway as a clarity argument, not a technical one: 'AI engines reward clarity over complexity. The businesses winning AI citations aren't necessarily the ones with the most sophisticated site architecture. They're the ones that make their most important pages easy to find and easy to understand.' The company's stated recommendation is to keep high-intent pages near the root domain, favoring a single service-and-city slug over a deep, multi-folder path.

Does the rest of the evidence agree?

Not exactly, and the disagreement is informative. Two months before Local Dominator's release, Otterly.ai published a much larger, independent dataset that reached a different conclusion about URL length specifically (Otterly.ai, May 7, 2026).

That study tracked 1,028,959 unique URLs across 1.93 million citation instances, observed over a 24-hour window, across ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Gemini and Microsoft Copilot. It found a near-zero correlation between URL length and citation count (r = -0.025). The average cited URL ran 63 characters, and 40-character URLs were cited about as often as 120-character ones.

The same study did surface two structural signals worth noting: URLs without query strings averaged 2.1 citations versus 1.6 for URLs with query parameters, a 24% gap, and guide-type pages performed strongest overall at 2.7 average citations, 42% above baseline. Length was not the variable that moved the needle. Cleanliness and content type were.

So which study should you believe?

Both, because they are not measuring the same thing. Local Dominator grouped citations by URL type: homepage, single-segment page, deep blog path, and so on. Otterly.ai measured URL length as a continuous variable, in characters, independent of what kind of page it pointed to.

A single-segment URL like /best-plumber-austin/ is short in characters and structurally close to the root domain. It is entirely possible for AI engines to favor that page because it is well-linked, well-covered, and easy to crawl and quote, while being indifferent to the fact that its slug is 22 characters instead of 80. Local Dominator's own numbers hint at this: homepages, which are the shortest possible path (a domain and nothing else), only captured 15.79% of citations, well behind single-segment pages at 29%. If length alone drove citations, homepages should have won outright. They did not.

The more defensible reading is that proximity to the site's core structure and clarity of the content on the page are doing the work, not the string in the address bar. That distinction matters more than it sounds like it should, because it changes what you should actually do about this news.

Who does this actually affect?

Two groups are most likely to see this data cited at them this quarter. B2B SaaS and tech growth teams debating URL schemas for comparison and category pages, the pages that answer 'best [category] tool' style prompts, will hear this used as an argument to flatten navigation. Local, multi-location and service businesses building out service-plus-city pages, the exact use case Local Dominator's own recommendation targets, are the more direct audience for the claim.

A third group affects everyone reading this: agencies and consultants who will package 'shorten your URLs' as a quick AI-visibility win. It is an easy pitch. It is also, on the larger dataset, not the lever that moves citations.

How should you respond this week?

Do not start a URL migration project off a single press release. Rewriting live URLs without redirects, or without a real content reason, risks breaking existing citations and backlinks for a change the bigger dataset says is close to irrelevant on its own.

1. Audit the pages you most want AI engines to cite: are they reachable in one or two clicks from the homepage, and do they carry clear, specific content on the exact question or service someone would ask about.
2. If you are launching new pages, such as a service-and-city page or a comparison page, default to a short, single-segment slug because it is good practice for humans and internal linking, not because the string length itself moves citations.
3. Strip unnecessary query parameters and tracking clutter from canonical URLs you want indexed and cited; the 24% gap between clean and parameter-heavy URLs in the Otterly.ai data is the more actionable, better-supported signal here.
4. Do not migrate or flatten existing, already-cited URLs purely to shorten them. Redirect churn is a real risk with no confirmed upside.

What should your URL strategy actually optimize for?

Content and structure, in that order. Neither study found a shortcut. Local Dominator's own top category, single-segment URLs, is also where teams tend to concentrate their best, most specific content, because it is the format used for core service and category pages. Otterly.ai's strongest category, guide-type pages, is a content classification, not a URL pattern.

1. Put your most citable, specific content (a real stat, a comparison, a direct answer) on the page you want cited, regardless of slug length.
2. Keep the URL close to the root when the page is a primary category, service, or comparison page; that is a usability and internal-linking decision as much as an AI one.
3. Cut query strings and duplicate paths for canonical, citable pages.
4. Track citations directly, across ChatGPT, Perplexity, Gemini and AI Overviews, rather than inferring cause from a single correlation you have not tested on your own site.

Sources

Short, single-segment URLs captured about 29% of AI citations, the largest share of any URL type, in an analysis of 2.78 million AI-cited URLs from 188,000 scans across ChatGPT, Gemini, Google AI Mode, Perplexity, Claude and Grok. Local Dominator (via Submit123PR newsroom), 2026-07-28

A study of 1,028,959 unique URLs and 1.93 million AI citation instances across six AI engines found a near-zero correlation (r = -0.025) between URL length and citation count, and a 24% citation advantage for URLs without query strings. Otterly.ai, 2026-05-07