The standard · v1.0
The Shelfgrade Score
One number, 0–100, for how ready a store's catalog is to be read by AI shopping surfaces — ChatGPT, Perplexity and Google/Gemini. Deterministic, fully documented below, with every point traceable to a finding that cites the vendor doc it derives from. Free to measure, free to quote.
Three pillars, weighted
robots.txt evaluated per RFC 9309 against each surface-gating bot (OAI-SearchBot, PerplexityBot, Googlebot), plus live bot-UA probes
the product feed validated under OpenAI's documented parser rules — native schema first, Google-compatible profile fallback, GS1 GTIN checksums
Product/Offer JSON-LD on product pages checked against Google's merchant-listing spec, diffed against the feed for price/availability drift
The free scan measures access + structured data (weights renormalized) — and on Shopify stores it auto-measures the feed pillar from the store's public catalog. The full audit reads your uploaded feed directly and ships the corrected files.
The point model
Each pillar starts at 100 and deducts per finding by severity. A pillar containing any blocker is hard-capped at 25 — a store that blocks the shopping crawler cannot score well no matter how clean its markup is. The total is the weighted average, rounded.
| Severity | Deduction | Meaning |
|---|---|---|
| Blocker | −40 | kills a surface — e.g. robots.txt disallows the crawler that feeds it |
| Major | −15 | breaks parsing or a documented requirement — e.g. invalid price format |
| Minor | −5 | a documented field the surface reads is missing — e.g. no gtin in markup |
| Info | −0 | recorded for transparency, never scored — e.g. training-only bot blocked |
What it deliberately does not measure
Rankings, traffic, or revenue — no one can honestly score those, and we don't pretend to. The Score measures machine readability against published vendor requirements: the part of AI visibility a merchant fully controls. Whether a surface actually cites you is measured separately (citation monitoring), never folded into the Score.
Why the number can be trusted
- Deterministic: the same store state always produces the same score — no models, no judgment calls, no black box.
- Sourced: every finding links the vendor document it derives from.
- Re-verified weekly: an automated pipeline re-checks every underlying rule against the live primary sources; changes are published in Spec Watch and versioned here (current: v1.0).
The Shelfgrade Index
A fixed panel of 50 well-known DTC stores, re-scored every week — the public baseline the ecosystem can be measured against.
Median score
94/100
week 2026-W36
Grades
A:38 · B:3 · C:9 · D:0 · F:0
Blocking a surface
Perplexity 18% · Google 18% · ChatGPT 0%
Methodology and findings: the DTC AI-readiness study.
Using the Score
Quote it freely — in client reports, audits, internal dashboards — with attribution (“Shelfgrade Score”). Agencies get it natively in white-label reports. Any store can measure itself in 30 seconds: