Digital Readiness Scorecard · 2026
10 points above the median of 58 across 32 measured distributors
Scored against the published framework — fourteen signals, no model judgement anywhere in the scoring.
Can a machine tell what this product is and match it to the same product elsewhere?
Does the page answer what a buyer actually asks before they commit?
Can a buyer find out what it costs and whether it ships, without asking a human?
Can a crawler, a marketplace, or an AI shopping agent actually consume any of it?
schema.org Product markup present in server-rendered HTML
Valid sitemap resolved, declared in robots.txt
Product paths are crawlable under the general user-agent rules
No AI-crawler rules in robots.txt, so they are permitted by default
Every one, openable. Each was taken from the middle of a different category listing — never a featured or promoted placement — so the sample reflects the catalog rather than its best shelf.
| Product page | Attributes | Images | Page score |
|---|---|---|---|
| store.e-tplastics.com/products/blue-2069-mirror | 8 | 1 | 38/69 |
| store.e-tplastics.com/products/l-110-cherry-red-blur-acrylic | 3 | 2 | 40.5/69 |
| store.e-tplastics.com/products/glitter-ruby-gh341-601 | 3 | 1 | 34.5/69 |
| store.e-tplastics.com/products/neon-purple-p95 | 3 | 1 | 34.5/69 |
| store.e-tplastics.com/products/transparent-green-2111 | 6 | 1 | 41/69 |
Page score is out of 69 — the portion of the framework scored per page. The remaining 31 points are site-level: consistency, gating, and the four agent-readiness signals.
Derived from the score itself, largest gap first — Product Data Depth lost the most points.
Good — that is the useful conversation. The pages we sampled are listed above, so the first thing to do is open them. If the sample missed something, if a category we hit is genuinely unrepresentative, or if your catalog has changed since 2026-08-06, tell us and we re-run the measurement against your live site. Scores are never adjusted by hand — only recomputed.