- Visibility39
- Citations1
- Sentiment76
- Site quality93
- AI readiness36
AI assistants name Starbucks in 41.7% of answers, which is almost twice as often as the typical company in its sector. Its overall score is 47 out of 100, ranking 53rd of 2,047 companies and 3rd in its sector. The Starbucks website passes 3 out of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the travel market: none named Starbucks. AI assistants named it in 25 of 60 answers (41.7%). The typical travel company is named in 21.7% of answers. By how often it is named, Starbucks ranks 11 of 75 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.
75 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“How do drive-thru coffee chains compare to sit-down coffeehouses?”
Drive-Thru Coffee Chains vs. Sit-Down Coffeehouses
These two coffee retail models serve different purposes and appeal to different customers:
Convenience & Speed
Drive-thru coffee chains prioritize speed and convenience—perfect for people on the go. Customers can order and receive their drinks without leaving their vehicle, making it ideal for commuters and busy individuals. Sit-down coffeehouses, by contrast, emphasize a more leisurely experience where customers can linger over their drinks.
Atmosphere & Social Experience
Sit-down coffeehouses typically offer a dedicated sp …
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.
- 0
- 1
- 2
- 3
- 4
- 5
Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.
- Content Signals
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%SitemapPassed
An XML sitemap listing the pages, ideally referenced from robots.txt.
- study: 0.3%Link headersNot met
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 negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtNot met
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 AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
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 ResourceNot met
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%auth.mdNot met
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 CardNot met
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsNot met
Publish a skills index with the main tasks agents can do.
- study: 33.7%WebMCPCould not check
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 25 of 100 · 97% of checks could run · checked on October 5, 2026 · www.starbucks.com · 2,047 companies scanned
3 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%
- PassedXML 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.
- GPTBotallowed
- ClaudeBotallowed
- Anthropic-AIallowed
- Google-Extendedallowed
- Applebot-Extendedallowed
- Meta-ExternalAgentallowed
- FacebookBotallowed
- Bytespiderallowed
- CCBotallowed
- Diffbotallowed
- Omgilibotallowed
- OAI-SearchBotallowed
- Claude-SearchBotallowed
- PerplexityBotallowed
- Applebotallowed
- Amazonbotallowed
- YouBotallowed
- ChatGPT-Userallowed
- Claude-Userallowed
- Perplexity-Userallowed
- DuckAssistBotallowed
- MistralAI-Userallowed
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 menu prices at specialty coffee chains justified by the quality and convenience?
- How do drive-thru coffee chains compare to sit-down coffeehouses?
- What are some community-based options with mobile ordering features for coffee lovers?
- How do loyalty rewards affect overall spending at coffeehouse chains?
- Why might my mobile coffee order not be ready when I arrive?
- Alternatives to large coffeehouse chains for on-the-go coffee in the U.S.?
- Common issues with using gift cards at specialty coffee chains and how to resolve them?
- Which coffeehouse chains offer the widest variety of pastries and snacks in addition to drinks?
- What are popular fall-inspired drinks typically offered by coffeehouse chains?
- How do specialty coffeehouse chains cater to customers with nondairy preferences?
- Where can I find cafes with mobile ordering and rewards programs?
- What are the best specialty coffeehouse chains for handcrafted drinks in the U.S.?
- Specialty coffeehouse chain vs independent local café—what’s the experience difference?
- What is the average price range for handcrafted espresso drinks at major U.S. coffee chains?
- Is joining a coffeehouse rewards program worth it for frequent customers?
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/starbucks.com"><img src="https://aeo-audit.rezolve.com/us/badges/starbucks.com.svg" alt="Overall score 47 of 100, US AI Visibility Study 2026" width="280" height="64"></a>