Make the buying decision clear.
Product details, variants, identifiers and availability where the store publishes them. Missing public data is distinguished from data the endpoint does not expose.
xLabCommerce / FOR SHOPIFY MERCHANTS
Your store has the products. Does it answer the buying question?
xLabCommerce finds gaps in your Shopify store’s public product information, catalog structure and buying paths. Get evidence-backed findings and prioritized fixes. We can implement the agreed work or support your team, then retest.
For ShopifyPUBLIC STORE, CATALOG AND BUYING PATHS.
Evidence firstFINDINGS, PRIORITIES, COVERAGE AND A BASELINE.
Audit. Fix. Retest.AGREED IMPLEMENTATION AND RETESTING SCOPED SEPARATELY.
Start simplyYOUR STORE URL AND THE QUESTION IT NEEDS TO ANSWER.
THE AUDIT / A WORKING DELIVERABLE
Know what needs attention. Know why.
You receive a findings register with the supporting observation, severity, likely owner and effort for each actionable issue. A prioritized plan gives your team an order of work. Coverage and unknowns stay visible, and the retained baseline gives a later check something concrete to compare.
Give the catalog a usable structure.
Public product and collection records, navigation, links and the paths connecting a question to the relevant product.
Publish a consistent account of the store.
Structured data, crawl signals and applicable public agent surfaces, checked against the visible pages within the agreed scope.
Find friction before changing the store.
Public paths, asset weight and performance observations. A read-only audit does not sign in, add to cart or complete checkout.
ILLUSTRATIVE EXAMPLE / NOT A CLIENT RESULT
A finding becomes a piece of work.
A product page looks complete to a shopper, but its published Product structured data cannot be parsed. The audit records the issue. Investigation identifies the responsible theme or app output before a change is proposed.
Show the failure.
Record the public URL, observed structured-data parse failure, date and method. That supports a technical finding; it does not prove lost sales or predict an AI answer.
Correct the cause.
Investigate the theme or app producing the markup, then scope a correction with the responsible team. The audit alone does not establish the cause.
Check the same surface.
Rerun the affected check against the baseline. Record whether the markup now parses, whether it agrees with the visible product, and what remains unresolved.
HOW WE WORK / AUDIT · FIX · RETEST
We stay through the agreed work.
Start with the store and a consequential buying question. We agree the audit scope and deliver the evidence. You can use the findings with your own team, ask 99xlab to implement the agreed changes, or have us work alongside you. Retesting checks the affected findings; ongoing review is a separate decision.
People and machines need a clear path.
xLabCommerce applies Machine Experience to Shopify. MX also covers business websites, strategy and the broader journey from discovery to action.
UNDERSTAND MX →Measurement supports the decision.
Machine View makes a read-only record of the agreed public surfaces. 99xlab interprets the observations, separates unknowns and sets priorities with you.
BEFORE WE BEGIN
A clear scope. A useful next step.
What do we receive?
An evidence-backed findings register with severity, likely owner and effort; a prioritized order of work; a list of checked surfaces and important unknowns; and a baseline for comparison after change.
Can 99xlab implement the fixes?
Yes. We can implement agreed content, catalog, theme, performance and structured-data changes or work with your team. Implementation and retesting are separately scoped; the audit remains a useful deliverable on its own.
How does this relate to MX?
MX means Machine Experience: the broader discipline of helping people and automated readers find, understand, choose and act on what a website publishes. xLabCommerce is the Shopify service within MX. Machine View is the read-only measurement instrument that supplies the evidence.
Does the audit need Shopify admin access?
The initial outside-in audit reads agreed public surfaces without admin access, sign-in, cart actions or checkout. Any access needed for later implementation is agreed separately.
Will this increase sales or get us into AI answers?
The audit identifies supported issues and a useful order of work. It cannot guarantee sales, rankings or inclusion in an AI answer. Named answer-system observations, when useful, are separately scoped and dated.
How do we start?
Share your public store URL and the buying decision or recurring question that needs a clearer answer. We agree coverage, intended use and the deliverable before quoting. You do not need a finished brief.
YOUR STORE / ONE BUYING QUESTION / A DEFINED SCOPE
