I sell apparel, and for a long time my size guide was a single table copied from a supplier. Customers still returned items with the note "runs small" or "not what I expected." Each return cost me shipping both ways plus restocking, and I never connected it to the chart until I looked at the return reasons together.
The chart was technically present, practically useless
A size chart with only bare measurements fails the person who doesn't know their measurements in your units, or who is between sizes. What actually reduces returns is fit context: "if you are between sizes, size up," "this cut runs narrow at the shoulder," that kind of note. I didn't have those, and writing them per size across a range is tedious enough that I skipped it.
The second leak was the unit. I listed centimeters; half my buyers read inches. The confusion produced returns from people who ordered the "right" size in the wrong unit, which is pure waste on both sides.
Generating from measurements
I now build the chart from the garment numbers I already have. SizeGuide turns garment measurements into a clear size chart with fit notes per size and a care/return line, and a cm/in toggle. The per-size fit notes are the part that addresses my return problem directly — they tell the buyer the thing my supplier table never did.
The cm/in toggle matters more than it sounds: it removed a whole class of unit-confusion returns. You can preview the chart format on the SizeGuide page before you feed in your own measurements.
What it can't do
The fit notes are only as good as the measurements you enter. If my garment data is wrong, the chart is confidently wrong, and returns go up, not down. I had to fix my measurement source first, which meant actually measuring samples instead of trusting the supplier PDF.
It also won't judge your sizing philosophy — whether you want a relaxed or tailored fit is your call. The tool documents the garment; you set the intent, and the fit notes should reflect that intent honestly.
A related fix was standardizing how I measure. Different people on my team used different points on the garment, so the chart disagreed with itself between products. Cleaning that up before generating made the fit notes trustworthy across the whole catalog, not just one listing, which is what actually moved the return rate down.
Fit notes beat a bigger table
I tried the obvious fix first: a more detailed measurement table. It didn't move returns. The fit notes did, because buyers read a sentence faster than they cross-reference numbers, and the sentence tells them what to do when they're between sizes. The table is the evidence; the note is the instruction. Both matter, but only one changes behavior at the moment of purchase.
I also started putting the care and return line right under the chart, not on a separate policy page nobody clicks. A buyer deciding whether to risk the order reads the return line next to the size they're about to pick; burying it elsewhere loses the reassurance at the exact moment it's needed. The tool putting that line in the chart output made it trivial to keep them together.
FAQ
What do I need to provide?
Your garment measurements. The tool builds the chart and fit notes from those numbers.
Does it handle both metric and imperial?
Yes, there is a cm/in toggle so buyers see the unit they expect.
Will fit notes really cut returns?
They address the most common return reason — size confusion. They won't fix a product people don't like, but they remove a known leak.
Is the care and return line included?
Yes, a care/return line is part of the output, so the chart doubles as a policy reminder.
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