Resolution Layer Case Study  ·  Read & Diagnose

A licensed lifestyle brand.

A cold read of a brand-merchandise storefront — where the only asset being sold is the name on the product.

Scope
Brand merchandise storefront  ·  apparel, drinkware, home goods, accessories, collectibles
Lead finding
The brand's own name, misspelled in a live product URL
Issues surfaced
15 actionable (21 flagged)
Method
Automated multi-lens read  ·  auto-profiled, no schema supplied
Vertical
Licensed Merchandise — brand-licensed consumer goods
This pass
Read & diagnose — step one of the arc
Prepared by
EKOM
Type
Case study — client anonymized

What this is.

This is a real EKOM catalog analysis with the client's identity removed. The client is a licensed lifestyle brand — a hospitality and leisure company whose merchandise storefront sells apparel, drinkware, home goods, accessories and collectibles, all of them carrying the brand's own name. EKOM read the live public storefront cold: nothing was supplied, no access was granted, no schema was provided. The passes auto-profiled the catalog's structure, checked values against each other and against how each field was used elsewhere in the same catalog, and reconciled what surfaced into 15 actionable findings — the kind standard validation misses, because it checks whether a field is filled, not whether the value is right.

What makes this catalog worth studying is the asymmetry between what it is and how it is treated. For most retailers the catalog is a list of things they sell. For a licensing business, every product record is the brand — the name is the entire asset, and the catalog is where that name is written down the most times and proofread the least. That is not a failure of anyone's team. It is a structural property of how product data gets made: authored once, under deadline, in a field nobody presents in a review.

These are machine-surfaced findings meant as a triage signal, not a verified defect list — a small share may be intentional. Even so, the concentration and specificity of what surfaced is a strong read on catalog health.

What's inside

At a glance.

Where the 15 actionable findings concentrate, by theme. A further 6 structural observations were held back — several were artifacts of EKOM's own analysis prep rather than defects in the catalog, and are excluded from every count on this page.

15
Actionable
findings
4
Critical
14
High severity
or above
7
Issue
themes

By theme

ThemeCountWho feels it
Brand-integrity defects in live URLs & titles2Shoppers + brand owner
Platform placeholders shipped as product data4Shoppers + ops
Category taxonomy defects2Shoppers
Slug & URL artifacts2Shoppers
Tag-field contamination & contradiction3Shoppers + ops
Pricing-claim integrity1Shoppers + legal
Content completeness1Shoppers
The count isn't the point. Every one of these passes a completeness check — the field is filled, so a validator waves it through. They are wrong in ways that only surface when structure and meaning are read together, and they cluster exactly where a brand-led business can least afford them: the name, the category, and the price.

What a shopper runs into first.

Highest impact — the issues a shopper actually sees, live on the site today.

Highest-Visibility Finding  ·  Brand Integrity
The brand's own name, letters transposed — in the product title and in the live URL.
A sunglasses listing carries the brand name misspelled, with two letters swapped, in both the customer-visible title and the URL slug. For a company whose only real asset is that word, this is the single worst field in the catalog to get wrong: it is indexable, shareable and quotable, and a URL correction carries a redirect requirement, so it gets more expensive the longer it stays live. A second product, a pet bowl, carries a different transposition of a product-line phrase in its handle and title — while its own medium and large siblings spell the same phrase correctly. The catalog already held the right answer in both cases.

The platform's own scaffolding, shipped as brand data

Six live items list My Store as their vendor — the literal default a storefront platform assigns when nobody sets one, sitting in the field that drives every brand collection on the site. Five in-stock, purchasable items use Hidden as their product category: a channel-visibility concept, not a taxonomy value, which leaves those items neither hidden nor categorised. A countertop appliance's URL still ends in -copy, the trace of a duplicated product record that was never renamed — a live customer-facing address that reads, to a crawler, like a page that was never finished.

A discount that isn't one

Three items carry a comparison price identical to their actual price with no sale running. Depending on the theme, that renders either as a broken was $X, now $X badge or as an advertised saving that does not exist. Reference-price claims sit squarely inside FTC guidance on advertised savings — and this is the kind of detail that travels as a screenshot.

Categories nobody searches for, and categories that don't exist

Every jewelry item in the catalog — twenty products — is filed under Jewlery. Nothing is filed under the correct spelling, which is precisely why it survives: the category looks internally consistent, so nothing flags it. Separately, twelve items in a single sunglasses line carry a blank category while the thirteenth item in the same line is categorised correctly. Blank means invisible to category navigation, invisible to filters, and dropped from any feed that requires the field.

Where it traces back.

Most of what surfaces above traces to one root: operational language that was never separated from customer-facing language.

The tag field is doing two jobs at once

Tags drive storefront filtering and flow into shopping feeds — and this catalog's tag field is also being used as an internal work queue. Live products carry NEED_CAD_DRAWING, NEEDS_COLOR, NEED_COUNTRY_OF_ORIGIN, NEED_HS_CODE, BFCM_DISCOUNT_2024, FLASH_SALE_OCT_2025, REMOVED_META_GOOGLE, SYNC_PRICE and YBlocklist — a merchandising to-do list and two expired promotions, sitting in the field that decides what a shopper can filter by.

Two fields telling a customer opposite things

Ten items are tagged DISCONTINUED while remaining in stock and purchasable. If that tag drives an exclusion rule somewhere, sellable inventory is being suppressed; if it doesn't, the tag is telling a customer something untrue. Either way the catalog is holding two contradictory positions on the same product, and no validator will ever raise it — both fields are populated, and both are individually valid.

The same idea, written four ways

Gender appears as Men | Mens | women | Womens — sometimes several variants on the same garment. Any collection rule filtering on one form silently misses everything using another. A vendor name has a fulfillment status welded onto it, splitting one supplier's collection into a real one and a phantom one that nobody browses. And a handful of live items ship with no description copy at all; one hat's description reads, in full, Adjustable hat.

The URL that says nothing

One beach towel's slug is the generic placeholder exclusive-gift — while every other handle in the catalog is a descriptive product slug. It costs the page its search relevance and makes the link meaningless the moment somebody shares it.

How EKOM reads this catalog.

Why an auto-profiled, cross-referencing pass catches what a field-by-field check misses.

1
Read the live storefront
Took the whole public catalog cold — no file handed over, no credentials, no schema. One link in, complete coverage out.
Full public-catalog coverage, nothing supplied.
2
Profile it without being told what it is
The first pass classified the catalog's vertical on its own and mapped every field's shape and usage — which is what makes "this value is wrong for this field, in this catalog" a question the system can even ask.
Vertical and field semantics inferred, not configured.
3
Read records against each other
Checked each value against its own siblings and against the field's use catalog-wide, then reconciled findings into typed results with a severity, an intended fix, and a confidence score on each.
15 findings, de-duplicated, scored and grouped.

A field-by-field completeness check would have passed almost all of this. Every field above is populated. The misspelled brand name is a valid string; Hidden is a valid category value; a comparison price equal to the price is a valid number. What makes them findings is context — a sibling product spelling the same word correctly, a category used nowhere else, a discount with nothing to discount. Reading records against each other is what turns "populated" into "correct," and it is what makes the next step precise rather than exploratory.

What this means — and what's next.

think less75%
75% of consumers now form a negative opinion of a brand when they encounter incomplete or inaccurate product information online — up from 62% in 2023 and 73% in 2024. The trend line matters more than the number: tolerance is going down, not up, and it is going down fastest for brands whose whole proposition is how they make someone feel.
Syndigo, "2025 State of Product Experience" — survey of 8,500+ consumers across six markets
A licensing business sells one thing: a name, and the permission to put it on something. Merchandise is where that premise gets tested most often and defended least, because a product record doesn't look like brand work — it looks like data entry. But a misspelled brand name in a live URL is not a data-entry problem. It is the brand, misspelled, in public, on a page the company published itself. And in a licensing structure, name integrity is not an aesthetic standard; it is typically what the agreements exist to protect — which makes a transposed name and a platform placeholder shipping as vendor of record control questions rather than content ones. The rest is quieter and compounds faster: a jewelry range filed under a word nobody searches for does not appear in its own category, and a sunglasses line with no category falls out of navigation entirely. Neither raises an error anywhere — there is no alert for a filter that quietly returns a shorter list.

This pass read and diagnosed. The same structural understanding powers the work that follows — turning a diagnosed catalog into one that reads right everywhere it's seen.

1  ·  Apply the corrections the catalog already answers
Nine of the fifteen findings carry a ready correction derived from the catalog itself — the correct spelling sitting on a sibling product, the real vendor legible from the product line, the category value one item in the range already uses. These resolve systematically, not one listing at a time.
2  ·  Separate the operational language from the customer-facing language
Move the work-queue flags and expired promotions out of the tag field, settle one canonical form per gender, and reconcile the discontinued-but-in-stock contradiction — surfaced with the context to decide quickly.
3  ·  Hold the line at intake
Keep continuous intelligence on new products and vendor updates, so the next placeholder or transposition never reaches a live URL in the first place.
This is how EKOM moves a catalog from insight to impact —
and keeps the name right everywhere it appears.
EKOM
The Resolution Layer
ekom.ai
About this analysis

EKOM's first read of this client's catalog, taken from the live public storefront with nothing supplied. Six further structural observations were excluded from every count here — several were artifacts of EKOM's own analysis prep, not defects in the catalog. Two findings were over-called on the first pass and are recorded as such. Client identity removed; the findings are real.

Case Study  —  Client anonymized  ·  The Resolution Layer
EKOM