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Ray Iyer
Ray Iyer
Co-founder & CEO, Anglera

The five questions safety & ppe buyers ask that your product page must answer

Safety and PPE buyers ask five specific questions before they click buy. See what happens to returns and support tickets when your product pages don't answer them.

The five questions safety & ppe buyers ask that your product page must answer

A buyer looking for a cut-resistant glove for a metal stamping line doesn't want marketing copy. They want to know if the glove will stop a specific blade, fit a specific hand, and survive a specific coolant. When your product page can't answer that in ten seconds, one of two things happens: they buy the wrong SKU, or they call support before they buy anything. Both cost you. Here are the five questions Safety & PPE buyers actually ask, and what it takes to answer them on the page instead of on the phone.

The five questions

1. What's the actual protection level, and against which standard? "Cut resistant" is not a spec. Buyers need the rating and the standard it came from — ANSI/ISEA 105 (now on a 9-level A1-A9 scale after the 2016 revision) or EN 388, tested against ISO 13997 using a tomodynamometer. The two scales aren't a straight conversion, so a page that lists one without the other forces a buyer to go find a cross-reference chart, per Ergodyne's breakdown of the two standards.

2. Will it actually fit? Glove sizing isn't universal across brands, and cuff style (knit wrist, gauntlet, safety cuff) determines whether it works with the sleeve or coverall the buyer already has. A single "size: L" field with no chart is a guess, not an answer.

3. What's it made of, and what's the coating? Shell material (HPPE, steel-core, Kevlar, glass fiber blend) and palm coating (nitrile, polyurethane, latex, sandy nitrile) drive grip, dexterity, and chemical exposure — three things that trade off against each other. A buyer handling oily sheet metal needs a different coating than one doing dry assembly work.

4. Is it rated for my specific hazard, not just "safety" in general? Cut resistance, abrasion, puncture, and chemical permeation are tested and scored separately. A glove can be excellent on cut and mediocre on puncture. Buyers sourcing for a specific task — deburring, glass handling, chemical dilution — need the full hazard breakdown, not a single headline rating.

5. What's the pack size, and what's the direct replacement if this exact SKU is out of stock or discontinued? Distribution buyers order in case quantities and reorder on a cycle. If the page doesn't state units per case, case pack pricing, and a cross-reference to an equivalent SKU, they either call to ask or order the wrong quantity.

A concrete example: the cut-resistant glove

Here's what a typical raw supplier feed looks like when it lands in a distributor's catalog, next to what a buyer actually needs to see.

Raw feed description: "HPPE Cut Resistant Glove, Grey, Nitrile Coated, Size L"

Enriched attribute table:

AttributeValue
Cut level (ANSI/ISEA 105-2024)A4
Cut level (EN 388 / ISO 13997)4X42D
Shell materialHPPE / steel-core / spandex blend
Palm coatingFoam nitrile, 3/4 dip
Cuff style10-inch knit wrist
Size runXS – XXL
Touchscreen compatibleNo
Chemical resistanceNot rated for liquid chemical exposure
Case pack12 pairs / case
Direct replacement if discontinuedEquivalent SKU with matching A4 rating and coating

The raw version tells a buyer almost nothing they can act on. The enriched version answers all five questions in one scan, and it's the difference between a buyer confidently adding it to a cart and a buyer opening a support chat to ask "will this stop a box cutter or just cardboard edges?"

Ask an answer engine

More sourcing now starts outside your search bar. A buyer might ask an answer engine: "what glove do I need for handling sheet metal with light oil, cut level A4 or higher, that still keeps grip." An AI answer engine can only surface your product if the cut level, coating, and hazard context exist as structured, machine-readable attributes on the page. A product titled "Grey Cut Resistant Glove" with no rating field is invisible to that query, no matter how good the actual glove is.

Why the gaps show up as returns and tickets, not just lost sales

When a product page is missing rating, sizing, or hazard-specific detail, buyers fill the gap with a guess. Guesses on safety gear are expensive in a specific way: an under-rated glove sent back after a near-miss is a return with a compliance conversation attached, not just a refund. Return volume tied to product description problems is well documented at the industry level — NRF's 2025 Retail Returns Landscape puts total US retail returns near $850 billion for the year, and distribution categories with technical specs carry their own version of that cost in wrong-SKU reorders and support load, not just consumer refunds.

The checklist

Before a safety/PPE product page ships, it should answer:

  • Cut, puncture, abrasion, and chemical ratings, each against a named standard (ANSI/ISEA 105, EN 388, or both)
  • A sizing chart, not just a size label
  • Shell material and coating, stated separately
  • The specific hazard(s) the item is rated for, not a generic "safety" claim
  • Case pack quantity and a named alternate/replacement SKU

Where Anglera fits

Your PIM or catalog system stores this data; Anglera is the layer that finds where it's missing, gap-fills it against supplier and source documentation, and quality-scores the result so a buyer — or an answer engine acting on their behalf — gets a straight answer instead of a guess. It plugs into whatever system already holds the catalog, works from a flat file if there's no PIM in place yet, and is built to close exactly the kind of attribute gaps that turn into returns and support tickets long before they turn into lost revenue.

Ray Iyer

About the author

Ray IyerCo-founder & CEO, Anglera

Ray is the co-founder and CEO of Anglera, building the product-data infrastructure for agentic commerce — turning messy catalogs into structured, AI-readable data that buyers and answer engines can find. Previously product at Uber; Stanford CS.

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