- Visibility24
- Citations2
- Sentiment50
- Site quality80
- AI readiness36
AI assistants name LoveSac in 13.3% of answers, which is more often than the typical company in its sector at 3.3%. Its overall score is 35 out of 100, ranking 829th of 2,047 companies. The company's website passes 3 of 14 technical checks for readiness for AI tools.
We asked 15 unbranded questions about the consumer goods market: none named LoveSac. AI assistants named it in 8 of 60 answers (13.3%). The typical consumer goods company is named in 3.3% of answers. By how often it is named, LoveSac ranks 29 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 good substitutes for bean bag chairs in a casual lounge area?”
For a casual lounge area, several comfortable and stylish alternatives to traditional bean bag chairs exist. These options offer similar relaxed vibes while sometimes providing more structure, durability, or a different aesthetic.
Here are some good substitutes:
Boneless Sofas/Memory Foam Chairs: These are essentially giant foam bags or shapeless sofas filled with dense foam instead of traditional beans. They offer cozy support, often last longer than bean bags, and can come with washable covers. They tend to fit well in modern or minimalist interiors. Lovesac's PillowSac chairs 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.
- 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 met
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 24 of 100 · 97% of checks could run · checked on October 5, 2026 · www.lovesac.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.
- 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 US-listed.
- What are good substitutes for bean bag chairs in a casual lounge area?
- Are premium bean bag chairs more comfortable than budget options?
- Best fabric choices for pet-friendly modular furniture
- Alternatives to modular sofas for flexible living room layouts
- What factors impact the price of modern bean bag chairs?
- Bean bag chairs vs floor cushions: pros and cons for home entertainment spaces
- Is investing in customizable modular furniture worth it for small urban homes?
- How do you fix a sagging modular sectional at home?
- How can customizable furniture adapt to changing family needs?
- What’s the best way to clean stains from a fabric bean bag chair?
- How much should I expect to spend on a high-quality modular sectional in the US?
- Which modern bean bag chair styles are most popular for living rooms in the US?
- What are the best modular sectionals for families with kids?
- Modular sectional sofas vs traditional sofas: which is better for apartment living?
- Best modern modular sofa setups for home movie nights
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/lovesac.com"><img src="https://aeo-audit.rezolve.com/us/badges/lovesac.com.svg" alt="Overall score 35 of 100, US AI Visibility Study 2026" width="280" height="64"></a>