Why this matters
Online clothing returns run 30–40%, largely because a “Medium” means something different at every store. So shoppers bracket sizes and return the rest, a margin-killer for brands and a chore for everyone. The virtual try-on industry’s answer has been hardware scanners and semi-nude photo uploads, which is exactly why it hasn’t happened.
ThreadSense is a browser extension that acts as a personal digital tailor: it learns your fit from clothes you already love (“I’m a Medium in Nike”), cross-references brand size charts, and tells you, right on the store’s page: “Buy a Large. Relaxed at the waist, perfect at the shoulders.” Photo-based measurement, when you opt in, runs entirely on-device: only the numbers are kept, never the images.
What exists now
A seedling: a full PRFAQ working through the trust ladder (start simple, earn precision), the garment-vs-body-measurement problem and the flat-lay comparison that sidesteps it, the permissionless B2C wedge (extension first, brand deals after traction), and affiliate-first monetization.
What I’m looking for
People who’ve given up on buying certain clothes online, and anyone who’s worked in e-commerce returns or fashion sizing who can tell me where this dies first.
Open questions
- Can size-chart data alone (no photos) get recommendations good enough to build trust?
- Extension distribution is brutal. What’s the acquisition loop?
- Which single store/brand pairing proves the magic fastest?