Safety ratings meet real-world shopping
Find helmets that tested well — and buy them from sellers worth trusting.
TestedHelmets is building a guide that brings independent safety evidence, seller-trust rules, and clear caveats into one place. This first release is a static prototype, not a live catalogue.
- Independent safety evidence
- Trusted-seller filters
- Recall-aware policy
- Clear disclosure
- Freshness requirements
Why this exists
Helmet shopping is fragmented.
Lab ratings live in one place, retailers in another, and marketplace listings can hide unknown sellers, stale information, used helmets, or possible counterfeit risk. TestedHelmets is designed to connect the pieces and preserve the caveats.
Start here
Bike helmet recommendations
The MVP includes one sample page to demonstrate the future recommendation structure without presenting any real catalog data.
How rankings work
Useful evidence, in the order a shopper needs it.
Gather evidence
Preserve independent rating sources and raw snapshots.
Normalize models
Keep canonical helmet records separate from source rows and listings.
Review matches
Never silently promote a product match into a public recommendation.
Filter offers
Hide unknown sellers, used condition, and unreviewed offers by default.
Seller trust matters
A helmet deal is only useful if the product and seller are trustworthy.
The planned system tracks seller identity and fulfillment separately from a retailer listing. It defaults to hiding unknown marketplace sellers, used helmets, and offers that need review.
- Seller context will be stored beside every offer.
- Used and unknown marketplace listings will not be default recommendations.
- Caveats stay visible when data is stale or incomplete.
Affiliate transparency
Future revenue will be disclosed plainly.
TestedHelmets may earn a commission from future qualifying links. Any such relationship will not change independent safety evidence, seller-trust rules, recall checks, or ranking criteria. This prototype contains no affiliate links.