- Visibility15
- Citations0
- Sentiment75
- Site quality80
- AI readiness14
AI assistants name Ralph Lauren in 6.7% of answers, about twice as often as the typical company in its sector. Its overall score is 34 out of 100, ranking 923rd of 2,047 companies. The website passes 2 out of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the consumer goods market: none named Ralph Lauren. AI assistants named it in 4 of 60 answers (6.7%). The typical consumer goods company is named in 3.3% of answers. By how often it is named, Ralph Lauren ranks 41 of 118 in its sector.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
118 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“What are the hallmarks of luxury American fashion brands for men and women?”
Luxury American fashion brands for men and women share several hallmarks that distinguish them in the global market. These characteristics often blend classic American aesthetics with high-quality craftsmanship and a distinct brand identity.
Key hallmarks include:
1. Quality and Craftsmanship:
Exceptional Materials: Luxury brands prioritize the use of premium fabrics, leathers, and other materials. Coach, for example, is known for its exquisite craftsmanship in leather goods.
Attention to Detail: Meticulous construction and finishing are crucial. Brands like Zac Posen are …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
This website turned most of our scan away, so it has no level. Only 42% of the checks could run. That reflects the website’s rules for automated visitors, and an AI agent arriving by itself meets the same rules.
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapCould not check
Serve an XML sitemap and reference it from robots.txt.
- study: 0.3%Link headersCould not check
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- study: 1.9%Markdown negotiationCould not check
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtCould not check
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthCould not check
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogCould not check
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryNot met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceCould not check
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%auth.mdCould not check
Publish an auth.md describing how agents sign in.
- study: 0.2%MCP Server CardNot met
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardCould not check
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsCould not check
Publish a skills index with the main tasks agents can do.
- study: 33.7%WebMCPNot met
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestCould not check
Publish an ai-catalog.json listing every agent interface.
Score 37 of 100 · 42% of checks could run · checked on October 4, 2026 · www.ralphlauren.com · 2,047 companies scanned
2 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.
These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.
Show the 14 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- Not metXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Not metllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- Not metExplicit AI bot rulesstudy: 13.0%
- Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
- Not metOAuth Authorization Server discoverystudy: 10.1%
- Not metOAuth Protected Resource discoverystudy: 9.3%
- Not metMCP Server Cardstudy: 0.0%
- Not metA2A Agent Cardstudy: 0.0%
- Not metWebMCP toolsstudy: 4.2%
- Not metAgent Skills declaredstudy: 0.0%
This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- ChatGPT-Userpartly
- Claude-Userpartly
- Perplexity-Userpartly
- DuckAssistBotpartly
- MistralAI-Userpartly
Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.
How many times each website was listed as a source in these answers
In the study as S&P 500.
- Are high-end accessories a good investment for everyday wear?
- How do luxury bedding prices compare to mid-tier options in the US?
- What are the hallmarks of luxury American fashion brands for men and women?
- Best classic style outfits for an upscale family gathering
- What should I do if tailored garments lose their shape after washing?
- Best upscale outerwear options for business travel
- Alternatives to classic preppy style for a timeless wardrobe
- What are some options for luxury-inspired living on a budget?
- High-end home decor trends popular in the United States
- Luxury lifestyle brands vs department store private label apparel
- How to care for fine materials like cashmere and silk at home
- Traditional American fashion vs European designer style differences
- Is premium pricing on classic clothing worth it for the quality?
- What factors impact the cost of premium wardrobe essentials?
- What makes high-quality home textiles suitable for families with kids?
Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.
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<a href="https://aeo-audit.rezolve.com/us/ralphlauren.com"><img src="https://aeo-audit.rezolve.com/us/badges/ralphlauren.com.svg" alt="Overall score 34 of 100, US AI Visibility Study 2026" width="280" height="64"></a>