- Visibility12
- Citations0
- Sentiment80
- Site quality67
- AI readiness29
AI assistants name Big Lots in 8.3% of answers, which is a little more often than the typical company in the retail sector. Its overall score is 33 out of 100, ranking 976th of 2,047 companies. The website passes 4 of 14 technical checks showing some readiness for AI tools.
We asked 15 unbranded questions about the retail market: none named Big Lots. AI assistants named it in 5 of 60 answers (8.3%). The typical retail company is named in 6.7% of answers. By how often it is named, Big Lots ranks 279 of 640 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.
640 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“Best ways to furnish a living room affordably using discount home retailers”
Great — here’s a concise, practical plan you can use to furnish a living room affordably using discount retailers, outlets, and second‑hand sources. I’ll list the tactics (what to do), where to look (retailers/types of sellers), and quick shopping tactics to get the best price.
1) Start with a plan and priorities
Decide the 3–4 anchor pieces you need (usually sofa, coffee table/media console, TV stand, main lighting). Spend most of your budget on the anchor(s); save on accessories. This keeps you from overspending on low‑impact items. (designlabs.io …
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
Not by itself. Big Lots publishes none of the purchase protocols we look for. An agent would have to click through the checkout like a person.
- UCPNot present
- ACPNot present
- AP2Not present
- x402Not present
- MPPNot present
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 · biglots.com · 2,047 companies scanned
4 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%
- PassedHTTP 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 Consumer brands.
- Best ways to furnish a living room affordably using discount home retailers
- Where can I find discounted groceries and seasonal items for families on a tight budget?
- Where can I find the biggest deals on brand-name items at US discount stores?
- What should I do if a product bought at a discount store is missing pieces or is damaged?
- Discount department stores vs. dollar stores: Which offers better deals on household essentials?
- What are some alternatives to off-price general merchandise retailers for budget shopping?
- How do prices for groceries at discount general stores compare to traditional supermarkets?
- How do off-price general merchandise retailers compare to warehouse clubs for bulk shopping savings?
- Is shopping at off-price furniture stores worth it for budget-conscious families?
- What price range should I expect for mattresses at discount furniture outlets in the US?
- Do discount department stores offer reliable quality on home goods and decor?
- How can I return or exchange an item bought from an off-price general merchandise retailer?
- Tips for shopping seasonal deals and clearance events at off-price department stores
- Are thrift stores a good alternative for finding affordable furniture and home goods?
- What are the best off-price retailers in the US for affordable home goods and furniture?
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/biglots.com"><img src="https://aeo-audit.rezolve.com/us/badges/biglots.com.svg" alt="Overall score 33 of 100, US AI Visibility Study 2026" width="280" height="64"></a>