SyntropyData · AI-Commerce Readiness Audit

Your store has a second storefront. It’s the one machines read.

AI shopping systems don’t browse your site — they read your product data. We audit which buyer questions that data can answer, show you the evidence, and give you a prioritized plan to close the gaps.

• Read-only • No installs or admin access • Prepared by a human analyst
[ PRODUCT SHOT ]

Halden 3-Seat Sofa

€2,190

A low, deep-seated sofa in Belgian linen over a kiln-dried oak frame. Feather-wrapped cushions, hand-finished seams. Made to order.

Belgian linen Kiln-dried oak Ships in 3–4 weeks

A growing share of product discovery is now machine-mediated — and it doesn’t browse your store the way a person does.

Assistants

Shoppers ask AI assistants before they ever reach a product page.

Agents

Shopping agents query stores through structured feeds and commerce APIs.

The gap

When your data can’t answer, the failure never shows up in your analytics.

The unit that matters

Buyers ask questions. Machines answer them with your data — or don’t.

Not rankings. Not keywords. The real test is whether a buyer’s question can be answered from what machines can read — across every vertical.

“Will this sectional fit a 3.2 m wall?”

Furniture·Fit & size
On page, not machine-readable

“What’s the inseam on the 32R?”

Apparel·Fit & size
Answerable

“Is this serum fragrance-free?”

Beauty·Ingredients
Not found

“Does this case fit the 2026 iPad Air?”

Accessories·Compatibility
On page, not machine-readable

“Is the protein powder vegan?”

Supplements·Composition
Answerable

“Does it ship assembled?”

Outdoor·Purchase-safety
Not found

“What’s the battery life on these earbuds?”

Electronics·Specs
On page, not machine-readable

“Can I return it after 30 days?”

Home·Purchase-safety
Answerable

Illustrative example · demonstration store

“Will the Halden sofa fit through a 78 cm doorway?”

A real buyer question. The answer is on the product page — in the dimensions table a person can read. Here is what the machine layer returns.

OBSERVED MACHINE RESPONSE

product matched✓ Halden 3-Seat Sofa
width exposed— on page, not machine-readable
answer possibleNo — can’t confirm fit

The fact exists. It just never reached the layer a machine reads. That’s an exposure gap, not a missing spec.

The good news

Most missing answers aren’t missing facts. They’re facts machines can’t see.

You’ve already done the work — it’s on your product pages. Every gap falls into one of three states. Most sit in the middle: cheap to fix.

Answered

In the machine-readable layer

The fact is structured and exposed. A machine can use it to answer a buyer.

On page, invisible to machines

Written for human eyes only

The answer is right there on the page — but never made it into the structured layer. Very common. Cheap to fix.

Genuinely missing

The fact exists nowhere yet

A real content gap. We flag it plainly — and never invent a value to fill it.

material: Belgian linen on your product page not yet in the machine layer One field. One fix. That’s the shape of most of the list.

What you receive

An audit you can hand to your team — or your boss.

Every finding is evidence-backed and source-linked. No opinions, no guesses — a document, and a plan.

AI-COMMERCE READINESS REPORT v1.3

Sample · demonstration store

62% of buyer questions answerable from machine-readable data
■ 62% answerable ■ 24% on page only ■ 14% not found

Directional figures on a fictional demonstration catalogue. Not a grade.

IN EVERY REPORT

Buyer-question coverage, family by family — what your catalogue can answer today.

The evidence behind every finding, down to the product and the field.

A fix worksheet ordered by impact and effort, mapped to public standards.

A 30-minute readout to decide what’s actually worth doing.

FIX WORKSHEET · SAMPLE ROWS

Expose sofa dimensions in structured data On page, not machine-readable schema.org · width / depth / height · effort: Low
Add material to the machine-readable layer On page, not machine-readable schema.org · material · effort: Low
Publish return window as structured policy Not found merchant returns policy · effort: Medium
Map variant availability per option On page, not machine-readable schema.org · Offer / availability · effort: Medium

COVERAGE BY BUYER-QUESTION FAMILY · DEMONSTRATION STORE

answerable / on page only / not found

Fit & size
51%
Material & composition
41%
Colour & finish
64%
Category & type
83%
Variant selection
62%
Price & availability
91%

Purchase-safety questions · tested through the policy / FAQ surface where available

Shipping, returns, warranty, care, lead time and assembly are checked separately from catalogue coverage — against your own policy and FAQ pages where they’re exposed.

How it works

Read-only. Nothing changes on your store.

01

Send us your store URL

That’s all we need. No app installs, no admin access, no credentials.

02

We audit your machine-facing surfaces

Evidence-backed checks against your public feed, structured data, and agent endpoint where available — measured the same way each time, read-only.

03

You get the report, the evidence, and a plan

Prepared and reviewed by a human analyst, then walked through on a readout call.

READ-ONLY HUMAN-REVIEWED EVIDENCE-LINKED

What we test

Six buyer-question families, plus a purchase-safety battery.

Tested against three surfaces: your public structured feed, product-page structured data, and your live agent endpoint where the platform exposes one.

Tested against public specifications — schema.org Product / Offer, Google Merchant Center product data, OpenAI product feed fields. Not a certification. Verified July 2026.

“Will it fit my space, or my body?” — dimensions, weight, capacity, size charts.

Surfaces: feed · product structured data

What we don’t claim

In a category full of guarantees, here’s what we won’t promise you.

✗ NO RANKINGS OR RECOMMENDATIONS

We don’t promise placement or recommendations in any AI assistant — no one can honestly promise that.

✗ NO ‘LOST REVENUE’ MATH

We don’t estimate lost sales. We show which buyer questions your data can and cannot answer — that’s measurable.

✗ NO PLATFORM AFFILIATION

We’re not affiliated with or certified by any platform. We test against their published specifications.

✗ NO INVENTED DATA

We never invent product data. Every suggested value is extracted from your own store, with its source.

Where to start

Start with a free snapshot. Go further only if it’s worth it.

01 · Readiness snapshot

Free

A human-prepared one-pager: your headline coverage stat and the strongest buyer questions your machine layer can’t fully answer.

Request a snapshot

02 · Readiness audit

€299

Report + 30-minute readout

The full report — coverage, evidence, and a prioritized fix worksheet — walked through on a readout call.

Ask about the audit

03 · Catalogue fix sprint

From €990

Scoped after the audit

Review-ready data you approve, verified with a before/after re-run of the same questions. The audit fee is credited toward the sprint.

Discuss a sprint

Shopify storefronts today · other platforms on request · the audit fee is credited toward a sprint.

Request a snapshot

See your second storefront this week.

A human-prepared snapshot of how AI shopping systems read your store. Free, read-only, no obligation.

Prepared and reviewed by a human analyst — typically within 2 business days.

Read-only. We never install anything or touch your store.

Shopify storefronts first. Other platforms on request.

No obligation · No store access required · Each snapshot is prepared and reviewed by a human analyst.

Questions

The honest answers.

No — and be cautious of anyone who says yes. No one can honestly promise placement in any AI assistant. What we can measure is whether your product data can answer the questions buyers ask, with the evidence and a plan to close the gaps.