Digital Readiness Scorecard · 2026
6 points below 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?
No JSON-LD found in the HTML a crawler receives
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 |
|---|---|---|---|
| www.sun-source.com/Product/415314-0103-EATON | 18 | 2 | 28/69 |
| www.sun-source.com/Product/321174-DANFOSS | 7 | 2 | 24.5/69 |
| www.sun-source.com/Product/5MAFB10CCK1-375-Sheffer | 31 | 2 | 55/69 |
| www.sun-source.com/Product/E-43-Y-0500-Parker-Hannifin | 15 | 1 | 25.5/69 |
| www.sun-source.com/Product/G-FX55T30-B6-S1-G38M-02-PIAB | 7 | 1 | 32.5/69 |
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.