A third of what you ship comes back. Half of it for one reason.
Not quality. Not price. Not delivery. Size. The one variable your product page never actually measures, and the one your margin pays for, twice, on every order that goes back.
Return rate, online apparel
Online clothing returns in India run at roughly double the global e-commerce average, and climb further through festive peaks.
None of this is new information. Which raises the harder question: why has every attempt to fix it failed?
Your fit leak
Move the slider to your annual online revenue.
Merchandise returned
at a 35% return rate
Returned over size & fit
at least half of apparel returns
Based on the 12–15% of profit the category loses to returns handling.
Figures are industry averages, not a projection of 1:1’s impact. Return rates from 2026 India e-commerce reporting; the size-and-fit share of apparel returns from Coresight Research. Your own numbers will differ, a Fit Audit measures them.
You have already
tried to fix this.
Three fixes, and every serious brand has shipped at least two of them. They all improve the information around the garment.
Not one of them measures the body that has to wear it.
Better photos and 360° views
Helps conversion, doesn't fix fit.
Generic size charts
Built for averages. Your customer isn't average.
"Size guide" pop-ups
1 out of 100 read them. You know this.
Most try-on tools dress a mannequin.
1:1|one:one dresses your customer.
Both put a picture on the product page. Only one of them measured the person looking at it.
Measuring the shopper is the half you can see. The half that pays for itself is what it hands back to you.
Built for brands that take
their margins seriously.
Return Reason Mapping
When returns do happen, we tell you exactly why. Size too small, wrong fit feel, unexpected drape. Your team stops guessing and starts fixing the right things.
Every return, classified
Mapped per SKU and per body segment, so the pattern is actionable rather than anecdotal.
Body-Type Analytics
Know what your customers actually look like. Plan inventory, design fits, and set quantities against real body data , not last season's sell-through reports.
First-Party Fit Profiles
Every shopper builds a profile. That profile belongs to your brand , a high-intent data layer of real bodies, preferences, and behaviour.
We are taking on three founding partners to prove it on real catalogues.