# A national athletic-footwear retailer. A footwear-catalog data-quality read — and where it leads. ## Scope Footwear catalog · sneakers, running, cleats, kids ## Lead finding In-stock shoes shoppers can't find ## Footwear issues surfaced 195 distinct ## Method Focused passes by footwear family · auto-profiled ## Vertical Athletic Footwear — sneakers, running, cleats, kids' ## What this is. This is a real EKOM catalog analysis, focused on the footwear side of the book, with the retailer's identity removed. The client is **a national athletic-footwear retailer** carrying sneakers, running, basketball, cleats, and kids' shoes across the major brands. Within the footwear assortment, EKOM's read surfaced **195 distinct data-quality issues** — the kind standard validation misses, because it checks whether a field is filled, not whether the value is right. Footwear has its own way of failing. A sneaker is discovered through attributes a shirt doesn't have — collar height, running surface, retro collection, cleat stud type, kids' sizing tier — and when those are blank or wrong, the shoe is in stock and simply _can't be found_. What follows leads with that: the shoes a shopper can't reach. Third-party brand and model names are kept as they appeared; only the retailer's own identity has been removed. 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 footwear-catalog health. ### What's inside - **In-stock shoes shoppers can't find** — the footwear-specific attributes that decide whether a shoe is discoverable, and where they're blank or wrong. - **Wrong shelf, wrong gender** — footwear filed or gendered so it surfaces in the wrong place, or nowhere. - **The SKU layer** — variant-level footwear issues the product view can't see: non-searchable sizes, broken parentage, price integrity. - **How EKOM reads a footwear catalog** — why per-family passes catch what a whole-catalog sweep averages away. - **What it means, and what's next** — from diagnosis to a footwear catalog that's findable and channel-ready. ## In-stock shoes shoppers can't find. The highest-impact footwear failure isn't a missing product — it's a live, buyable shoe that never surfaces where a shopper looks. Highest-impact footwear finding · Discovery Live shoes, invisible to search and filters. Every size of a purchasable **Jordan Luka 5 "Venom"** is flagged **non-searchable** — in stock, correctly priced, and invisible to on-site search. A **Jordan 4 Retro "Toro Bravo"** is tagged to the _wrong_ Jordan retro collection (jordan-retro-1 instead of jordan-retro-4), so it drops out of the collection filter shoppers actually browse. These are the shoes that exist in the catalog and disappear from the storefront. ### The footwear attributes that drive discovery — blank or wrong Shoes are found by attributes apparel doesn't have, and across the assortment these run heavily unpopulated: **collar height** (shoeHeight — low-top / mid-top / high-top / slides) blank on a large share of footwear, so shoes miss the height facet; **running type & surface** (runningType, runningShoeSurfaceType — road vs. trail) blank on most running shoes, so a trail runner never appears in a trail filter; **cleat stud type** (cleatType — molded / firm-ground / metal) blank on most cleats; and **kids' sizing tier** (kidsShoeSizing — grade-school / preschool / infant-toddler) blank on most kids' shoes, collapsing the single most important kids'-footwear filter. ### Wrong gender — invisible in navigation An **adidas F50 League Mid-Cut Men's Soccer Cleat** carries a **blank gender** — a clearly gendered men's cleat that never appears in gender-filtered navigation. A **women's shoe labeled "Men's"** despite every other field confirming the correct gender. On the variant layer, **nine Nike men's SKUs are labeled "Women's Shoe."** Gender is the first filter most footwear shoppers touch; a wrong value routes the shoe to the wrong shelf, or off the shelf entirely. ## The SKU layer — where a size is what sells. In footwear, the unit a shopper buys is a size. EKOM also ran a **variant (SKU)** analysis — one row per size a shopper can actually purchase — on a sample of the catalog. It surfaces a class of issue the product view can't see, because the product view summarizes its sizes down to a count. - **Non-searchable sizes.** Every size of a purchasable **Jordan Luka 5 "Venom"** is flagged non-searchable — the whole size run is invisible to on-site search while remaining in stock. - **Broken product grouping.** Six **Sabrina 3 "Silencer"** size variants point to the _wrong_ parent product — grouped under an unrelated shoe — while some legacy variants have no parent at all, so sizes scatter instead of gathering under one product page. - **Gender mismatch within the size run.** Nine **Nike men's SKUs labeled "Women's Shoe"** — sibling sizes disagreeing with the product's own gender. - **Price integrity.** Shoes where the **current price is higher than the "original"** (a fake sale, factually wrong) and active items priced at **$0.00** against a normal original — a free-item checkout risk. - **Barcodes / UPCs.** Blank or 0 UPCs on live shoes (nothing scannable for point-of-sale or EDI), and UPCs that **fail GS1 UPC-A validation** in vendor routing. - **Shipping-breaking dimensions.** The primary variant of **nearly every product** has height and width set to **0.0**, which breaks shipping-rate calculation and carrier-manifest validation. ### Missing fields and quiet contradictions. Less visible than a wrong shelf, but they break fit guidance, routing, and vendor identity. #### The fields fit and fulfillment depend on **Missing sizeChartId** on many shoes means the size-chart widget never renders — and in footwear, a missing size chart is one of the surest drivers of a return. Several **Jordan / Nike products carry a blank vendorName and vendorNumber** even though every other field confirms the brand — a gap that quietly breaks vendor routing and reporting. manufacturer is blank on items with a known vendor, and vendorPartNumber formatting is inconsistent across the assortment. ### Status / availability contradiction Shoes whose status and availability disagree. Several items are **failing quality guardrails yet remain searchable and purchasable**; one carries a bypassGuardrails flag set **True** with no documented reason. Others are marked **offline for "no image" while online with several images**, and one is **offline but still flagged in-stock and purchasable.** The status layer and the availability layer contradict each other on the same shoe. ### Why a completeness check misses all of this Every issue above passes a standard validation gate: the field is filled, the record is complete, the shoe is live. What a completeness check can't see is that the value is _wrong_ — a cleat with no gender, a retro tagged to the wrong collection, a size run pointing at the wrong parent. Those only surface when structure and meaning are read together, footwear family by footwear family. ## How EKOM reads a footwear catalog. Why family-specific footwear problems surface here rather than averaging away in a whole-catalog scan. 1. **Profile the catalog** EKOM profiled the catalog with no schema supplied — inferring the vertical and every field's role, fill rate, and quality signals, and detecting that footwear attributes cluster by family (running, basketball, cleats, kids'). 2. **Partition & pass** It ran focused passes — partitioning footwear by family and, within each, by sub-type or brand — so sparse-but-family-defining attributes like cleat type, running surface, and collar height are read in the context where they matter. 3. **De-duplicate & group** Findings are de-duplicated across passes, then grouped by theme and impact — which is why a blank cleat-type or a wrong Jordan-collection tag comes through cleanly instead of washing out. ## What this means — and what's next. More than one in four organizations facing data-quality challenges report losing over $5 million annually as a result — and in footwear that cost concentrates in discovery and returns, where every size filter, collar-height facet, running-surface tag, and size chart relies on clean structured data to function. A shoe that can't be filtered, or a size chart that won't load, doesn't announce itself; it disappears into a search with no results and a return that didn't need to happen. None of these are content problems. A cleat with a blank gender is invisible to gender navigation no matter how good the photography. A retro tagged to the wrong collection drops out of the filter shoppers browse. A size run pointing at the wrong parent scatters the sizes a shopper needs to convert. A missing size chart silently ends a session and seeds a return. These accumulate because standard validation checks for presence, not correctness — and footwear's most important attributes are exactly the sparse, family-specific ones a generic check never looks at. **This pass read and diagnosed.** The same structural understanding powers the work that follows — turning a diagnosed footwear catalog into one that's findable on every filter and channel-ready everywhere it sells. 1. **Apply the confirmed corrections** Fix the wrong-collection tags, the blank and mislabeled genders, the broken variant parentage and non-searchable size runs, and the price/status contradictions — resolved systematically, not one shoe at a time. 2. **Enrich the footwear-specific attributes** Complete the fields that make a shoe discoverable — collar height, running type and surface, cleat stud type, kids' sizing tier, retro collection — plus sizeChartId so fit guidance renders, so every shoe shows up on the filter a buyer actually uses. 3. **Go to the SKU layer, and hold the line** Run the full variant-level pass (price integrity, UPCs, per-size searchability, shipping dimensions) as the natural next depth — and keep ongoing intelligence at intake so the footwear catalog stays findable as new drops and colorways arrive. This is how EKOM moves a footwear catalog from insight to impact — and keeps every shoe findable as the assortment grows.