Most brands have no idea how their products look to AI shoppers. The ChatGPT, Perplexity, and Claude searches that increasingly decide what buyers see — Lumio just looked at this one the way those agents do, and scored how ready it is.

AI Readiness report

Example Homewares

Linen Throw

example-homewares.com/products/linen-throw

BigCommerce

Falling behind

82% of premium homewares on BigCommerce score higher.

Your Product schema only appears after JavaScript runs, so ChatGPT, Claude, and Perplexity can't see it. Fixing server-side schema is the single highest-leverage change here.

Scored by Lumio's AI-readiness algorithm · v2.2

Where this product stands

Lumio benchmarks this score against a live research set — real product pages from the top brands in each category and platform, all scored on the same 16 signals. Your standing is exactly where this product lands in that field. It's the same field ChatGPT, Perplexity, and Claude pull from, so the ranking is the one that actually matters.

At 30 out of 100, 82% of premium homewares on BigCommerce score higher. The typical product there scores around 61 — real ground to make up.

premium homewares on BigCommerce41 products scored
Middle 50%Typical score 6182% score higher

Cohort widened to clear the minimum sample — platform filter dropped.

Fix these first

  1. llms.txt file Missing

    Publish an llms.txt file at your site root pointing AI agents to your most important pages.

  2. AI crawler visibility Critical

    Server-render your product's structured data so it's in the page's initial HTML, not added by JavaScript after load.

  3. Q&A and use-case content Critical

    Add Q&A pairs, usage scenarios, and compatibility notes an agent can quote back to a shopper.

  4. Description depth Critical

    Write attribute-rich descriptions that answer real buying questions instead of marketing fluff.

  5. Product identifiers Critical

    Provide valid product identifiers: GTIN, MPN, brand, and model number.

  6. Structured data validity Critical

    Fix the errors in your structured data — missing required fields, wrong value types, or details that contradict the page.

  7. Structured data completeness Critical

    Fill in the recommended fields: GTIN, MPN, ratings, price validity, and return and shipping policy.

  8. Site-wide structured data Critical

    Add organization, site-search, breadcrumb, and FAQ structured data across the site — not only on the product page.

  9. Availability detail Critical

    Give exact stock levels, handling time, and restock dates rather than a bare in-stock / out-of-stock flag.

  10. Internal linking Critical

    Link the product to its category, related products, and brand pages so agents can navigate your catalog.

  11. Title quality Weak

    Write structured titles: brand, product type, a key attribute, and the variant — not just the product name.

  12. Content visible after load Weak

    Surface key product copy in the loaded page instead of hiding it behind tabs or accordions.

  13. Image readiness Weak

    Add descriptive alt text, image structured data, and responsive image sizes so agents can use your product photos.

  14. Page and data agree Weak

    Make the price, availability, brand, and title in your structured data match what's on the visible page exactly.

GPTBot, ClaudeBot are disallowed in robots.txt. Those are AI crawlers — blocking them keeps this catalog out of their answers.

The 16 dimensions

The full scorecard. Lumio measures structured-data and crawlability signals deterministically, then grades content quality with an AI pass. Expand any dimension to see what it measures and how to improve it.

Structured data & crawlability

  • AI crawler visibility 10

    Whether your product's structured data is in the page's initial HTML or only appears after JavaScript runs. ChatGPT, Claude, and Perplexity read the initial HTML — anything that needs JavaScript is invisible to them.

  • Structured data validity 35

    Whether your structured data is valid: it parses cleanly, required fields are present, values are the right type, and nothing contradicts the visible page.

  • Structured data completeness 20

    How complete your structured data is beyond the basics — product ID (GTIN), manufacturer part number (MPN), ratings, price validity, and return and shipping policy.

  • Site-wide structured data 15

    Structured data across the rest of the site, not just the product page — your organization details, site search, breadcrumbs, and FAQ markup.

  • Content visible after load 48

    How much real product text remains once JavaScript has run. Copy hidden inside tabs or accordions can be invisible to AI agents.

  • Page and data agree 40

    Whether the page a shopper sees and your structured data agree on price, availability, brand, and title. Mismatches read as a trust problem to an agent.

  • Image readiness 45

    How usable your product images are to AI: enough images, descriptive alt text, image structured data, and responsive sizes. Agents increasingly read images, not just text.

  • Freshness 50 Informational

    Signals about how recently the page was updated. Informational for now (not scored) until a reliable signal lands.

  • Internal linking 30

    Whether the product page links out to its category, related products, and brand pages — the trail an agent follows to understand your catalog.

  • llms.txt file 0

    Whether the site publishes an llms.txt file — an emerging convention for pointing AI agents to your key pages. Low weight while adoption is early.

  • agents.md file Not detected Informational

    Whether the site publishes an /agents.md file — an emerging convention, alongside llms.txt, for pointing AI agents to a site's real agent endpoint. Informational for now while the standard is nascent.

  • MCP endpoint Detected Informational

    Whether the storefront exposes a reachable Model Context Protocol (MCP) endpoint — the emerging way for AI agents to query a catalog and act on it directly. Informational for now while the standard is nascent.

Content quality (AI-graded)

  • Title quality 52

    Whether product titles are structured and descriptive — brand, product type, a key attribute, and the variant — rather than a bare product name.

  • Description depth 38

    Whether descriptions are rich with real attributes and answer the questions a shopper actually asks, rather than marketing fluff.

  • Q&A and use-case content 12

    Whether the page has the question-and-answer pairs, usage scenarios, and compatibility notes an AI agent can quote back to a shopper.

  • Product identifiers 25

    Whether the core product identifiers — GTIN, MPN, brand, and model number — are present and actually valid.

  • Availability detail 30

    Whether availability is specific — exact stock, handling time, and restock dates — rather than a bare in-stock / out-of-stock flag.

Fix it with Lumio

Lumio just analyzed one of your products.
Now let it analyze and fix your entire catalog.

Every gap above becomes an automatic fix — richer structured data, sharper titles and descriptions, complete identifiers — across all your products. Then Lumio keeps watching, so you stay ahead as AI shopping shifts.

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