Fit-aware recommendations
Fit-aware recommendations match products to a shopper's physical traits and fit preferences — proportions, rise, drape, cut — inferred from behavior and product understanding rather than size quizzes or measurements. The goal: fewer wrong-fit purchases, fewer returns, higher conversion.
In context
“Customers also bought” knows nothing about bodies. Fit-aware recommendation systems reason about both sides of the match: what the garment actually does (high rise, cropped, structured shoulder, bias cut) and what works for the person shopping. Veristyle infers these signals automatically — no quizzes, no measurement collection — from computer-vision product understanding and shopper interaction.
Fit is where fashion’s returns problem lives: a large share of returns are fit-and-expectation misses that better discovery would have prevented. That’s the thesis of fashion’s return rate is a discovery problem.
Related
Fit-aware matching is one layer of AI product discovery; see the discovery pillar for the full picture.