Rendered Fits · Guides
This glossary explains the words fashion ecommerce teams meet when they work on sizing, fit, returns, outfit merchandising, virtual try-on and AI shopping. Each entry gives a short definition you can quote, and where it helps, a note on why it matters for an online store. Terms are grouped by topic, and the A to Z index below lets you jump straight to one. Definitions of technical terms link to their primary source. Where a term has no formal standard, we say so.
By the Rendered Fits team · Reviewed 29 September 2026
A table that maps a brand's size labels (such as S, M, L or UK 10) to measurements, usually in centimetres or inches. Shoppers use it to compare their own measurements with the sizes on sale.
Why it matters online: Show it on the product page, name the measured points and use one unit set. If the chart and the garment disagree, shoppers pick the wrong size. Our size chart audit checks a chart for gaps.
The wider sizing help around a product: the size chart plus instructions on how to measure, fit advice and conversions between regional size systems. A size chart is one part of a size guide.
Why it matters online: Put how-to-measure steps beside the chart. For UK, US and EU conversions, see our clothing size converter.
Body measurements describe the person, such as chest, waist and hips. Garment measurements describe the finished item, usually laid flat or measured on a form. The two differ by the ease built into the design.
Why it matters online: Say which type each chart uses. Shoppers who compare their body with garment measurements, or the reverse, will misjudge the size.
The difference between a garment's measurements and the body it is designed for. Wearing ease allows movement; design ease is added on purpose for a style, such as an oversized cut.
Why it matters online: Two garments with the same size label can carry different ease. A fit note about the intended cut helps shoppers read the numbers.
The process of scaling a base pattern up and down to produce the other sizes in a range, following rules for how each measurement changes from one size to the next.
Why it matters online: Grading choices explain why one brand's sizes can fit differently at each end of the range. Ask suppliers for grade rules alongside the chart.
The planned split of units across sizes in a buy or production run, based on expected demand. For example, more units in middle sizes than in the smallest and largest. Also called a size distribution or size ratio.
Why it matters online: If a popular size sells out early, shoppers may choose a neighbouring size, which is one route to a poor fit. Compare the planned curve with what sells.
The set of sizes a style is offered in, such as XS to XXL or UK 6 to 20. In production, the term can also mean one batch made across those sizes.
Why it matters online: Say clearly which sizes are in the run and which are sold out. A gap in the run changes the choice a shopper has.
Ranges cut for particular proportions rather than simply scaled from the standard range. Petite generally covers shorter heights, tall longer heights and plus larger sizes. Each brand sets its own cut-offs, as there is no single standard.
Why it matters online: State the height or size range each line is cut for, and give inseam and length measurements for each.
The measurement along the inside of the leg, from the crotch seam to the hem. It sets trouser length and is often offered as short, regular and long.
Why it matters online: Give the inseam in your size chart for every trouser size and length option, in the same unit as the rest of the chart.
The distance from the crotch seam to the top of the waistband, measured at the front (front rise) or the back (back rise). It affects where trousers sit on the body, commonly described as low, mid or high.
Why it matters online: Rise changes how the same waist size sits and feels. List it as a measurement, not only as a word such as 'high-rise'.
The difference between the chest size of a suit jacket and the waist size of its trousers. In UK and US sizing, a size 40 jacket with size 34 trousers has a drop of 6.
Why it matters online: Tailoring shoppers often need different jacket and trouser sizes. Make sure separates can be bought in different sizes.
The practice of labelling a garment with a smaller size number than its measurements would have carried in the past or at other brands. Size labels therefore differ between brands and over time.
Why it matters online: Encourage shoppers to compare measurements, not labels, and to use a brand's own chart.
Short statements on a product page that describe how a garment is cut, such as 'relaxed through the body' or 'model is 175 cm and wears a size 8'. They give context that a size chart cannot.
Why it matters online: Include the model's height and size worn, the intended fit and any fabric stretch. Use consistent wording across products so people and software read them the same way.
A description of a garment whose label matches the size a shopper would expect, so they can order their usual size. It is a judgement, not a measured standard, and depends on which brand and fit the shopper compares it with.
Why it matters online: Avoid using the phrase without a measurement behind it. 'True to size' means different things to different shoppers.
Runs small means a garment fits tighter than its size label suggests; runs large means it fits looser. The phrases compare a garment with an expected fit, often through reviews, rather than measuring it.
Why it matters online: If reviews keep saying an item runs small, put that in a fit note near the size selector and check the listed measurements are right.
A suggested size for a particular shopper and product, worked out from information such as the shopper's height, weight or measurements and the product's size data. It is a suggestion, not a guarantee of fit.
Why it matters online: It depends on usable size charts and fit notes for each product. See how this works in our size recommendation app for Shopify.
A tool that estimates how a particular garment is likely to fit a particular shopper. It overlaps with a size recommendation; a fit predictor may return a size, a tighter-to-looser rating, or both.
Why it matters online: Ask what data a tool uses and how it treats products with missing measurements.
A short questionnaire that asks a shopper about height, weight, usual sizes or preferred fit, used to produce a size recommendation. The answers are self-reported, so results depend on what the shopper enters.
Why it matters online: Keep it short and let shoppers skip questions, so it does not add friction to buying.
Ordering the same item in two or more sizes with the intention of keeping one and returning the rest. Also called bracketing.
Why it matters online: It raises return volumes and stock in transit and makes fit-related returns harder to read. Clear size guidance and per-item fit notes give shoppers less reason to hedge. See our guide to reducing fashion returns.
Buying an item, wearing it, often for a single occasion, and returning it for a refund. It is different from returning something that does not fit or is faulty.
Why it matters online: Keep it out of your fit data. A clear return policy, and reason codes that separate it from sizing issues, make returns data easier to trust.
The share of orders, or of units sold, that are returned in a given period. Orders, units and revenue give different figures, so a return rate is only comparable when the denominator and period are stated.
Why it matters online: Record how you calculate it and compare like with like. Returns arrive after the sale, so recent periods look lower until they mature.
Returns where the reason is size or fit, such as too small, too large, too tight at the shoulder or too long. Merchants usually infer them from returns reason codes, which record only what the shopper chose to select.
Why it matters online: This is the group that sizing content and a size recommendation are meant to influence, so track it separately from other reasons.
The fixed list of reasons a shopper selects, or staff record, when a return is started. For example 'too small', 'too large', 'not as pictured' and 'changed my mind'. How consistently they are used determines how useful the returns data is.
Why it matters online: Split size into 'too small' and 'too large' rather than one 'wrong size' code. Add the size the shopper kept or exchanged for where you can.
The share of returns that end in an exchange for a different size, colour or item instead of a refund.
Why it matters online: Report it beside the refund rate. Returns that become exchanges keep the sale, and the size someone exchanges into is useful sizing feedback.
A product-page feature that suggests other items to make up an outfit around the product being viewed, often with a way to add several pieces to the cart. The name is used generically, and retailers and apps label it in different ways. Rendered Fits offers a Complete the Look app for Shopify.
Why it matters online: Outfit pieces often need different sizes, so each item should keep its own size choice. See how it differs from Shop the Look in our comparison.
A format that shows an image, often editorial or on-model, and links the products worn in it. The starting point is the image, whereas in Complete the Look it is the product being viewed. Retailers use the two names loosely.
Why it matters online: Check that every tagged item is in stock and shows a size selector, so shoppers can buy from the image.
A recommendation module that shows items purchased with the viewed product, usually based on order history, and often offered as a bundle. It reflects buying patterns, not whether the items make an outfit.
Why it matters online: Purchase-based pairings can suit accessories and basics. Fashion merchants often add stylist or rules-based outfits alongside.
The share of orders (or product views) containing a main item that also include a recommended or add-on item. Define the numerator and denominator before comparing figures.
Why it matters online: Track attach rate for each recommendation type separately, and note how many orders sit behind each figure.
The average number of items in each transaction, calculated as total units sold divided by the number of transactions. Also called items per order.
Why it matters online: Read it with average order value. Outfit and add-on features can move UPT, but so can discounts and shipping thresholds.
Total revenue divided by the number of orders in a period. State whether revenue is before or after discounts, tax, shipping and returns.
Why it matters online: AOV changes with discounts, free-shipping thresholds and product mix, so compare similar periods and journeys before drawing conclusions. Our measurement guide explains how.
Cross-selling suggests complementary items, such as a belt with trousers. Upselling suggests a higher-priced or upgraded version of the item being considered.
Why it matters online: Fashion cross-sells work best when colour, category and size availability make sense together.
A curated set of images showing pieces from a season or collection styled together, published as a page, gallery or PDF. Shoppable versions link each image to its products.
Why it matters online: A lookbook is a natural source for Shop the Look modules. List the size worn in each image.
Technology that shows a garment on an image or avatar of a shopper or model so they can preview its appearance. Methods include AR overlays, 3D avatars and AI image generation. A visual try-on preview shows appearance and does not establish physical fit.
Why it matters online: Pair any preview with a size chart and size recommendation. Read more on our virtual try-on for Shopify page.
AR (augmented reality) try-on overlays an item on a live camera view and tracks the body or face as it moves. AI (generative) try-on uses an image model to produce a new still image of a person wearing the garment. Both are visual previews and neither measures physical fit.
Why it matters online: AR is common for accessories and eyewear; generative try-on works from product photos. We compare them in AI vs AR virtual try-on.
An online experience in which a shopper provides details or a photo, sees garments on a representation of themselves and often receives size advice. The term overlaps with virtual try-on and its scope varies between vendors.
Why it matters online: Check whether a product gives size guidance, an appearance preview or both. See our virtual fitting room for Shopify page.
Photographs of garments worn by a model, as opposed to flat-lay or ghost-mannequin images. Shoppers use them to judge cut, length and drape.
Why it matters online: Give the model's height and the size worn. Showing a range of body types helps more shoppers relate the image to themselves.
Shopping in which an AI agent acts for the shopper, researching, comparing and, with permission, completing purchases. For merchants it means product, stock, price and policy information needs to be readable by software as well as people.
Why it matters online: See our guidance for AI agents and agentic commerce in fashion retail.
A conversational or search-style assistant that answers product questions and recommends items, either inside one store or on a third-party platform. Its answers depend on the product data it can read.
Why it matters online: If your size charts and fit notes are only images or PDFs, an assistant may not be able to use them. Use our AI shopper-ready checklist.
Product information held in consistent, labelled fields, such as size, colour, material, price and availability, rather than only in free text or images, so that software can read it reliably.
Why it matters online: Put size and fit facts in fields and on the page as text. Metafields and schema.org markup are two ways to do this.
Schema.org is a shared vocabulary for marking up web pages. Its size property describes a product's standardised size as text (for example 'XL'), a QuantitativeValue, a DefinedTerm or a SizeSpecification. A SizeSpecification can carry a size name, sizeGroup, sizeSystem and hasMeasurement, for example the inseam of trousers.
Why it matters online: Whether a search engine or AI agent uses the markup is up to that system. Keep the markup consistent with the visible size chart.
A proposed convention, introduced by Jeremy Howard in September 2024, for a Markdown file at a site's root (/llms.txt) that gives AI systems a short, curated summary of the site with links to key pages. It is described by its authors as a proposal and is not a formal standard.
Why it matters online: Whether a given AI system reads the file is that system's choice. Keep any file you publish accurate and dated.
An open-source standard for connecting AI applications to external systems, such as data sources, tools and workflows. A store or app can run an MCP server so compatible AI applications can look up data or take actions.
Why it matters online: It matters when you want an AI assistant to read live catalogue or stock data, rather than a copy that goes stale.
Custom fields that let you add extra data to Shopify resources such as products. A metafield has a namespace and key, a type and a value, and starts from a metafield definition.
Why it matters online: Metafields suit data that Shopify does not hold as standard, such as garment measurements or fit notes. Use one naming pattern across the catalogue.
In Shopify, each combination of a product's option values, such as size M in navy, can be a variant. The Shopify Help Centre currently states up to 2,048 variants and three options per product.
Why it matters online: Set size up as a real product option, not typed into the title, so size data and stock can attach to each size. Shopify's limits can change, so check the current page.
Technical definitions were checked against these primary sources on 29 September 2026. The plain-English definitions for fit, sizing, returns and merchandising terms are editorial and use no external statistics. Shopify limits can change, so check the linked page.
Start with your own size chart and fit notes, then decide what shoppers and AI systems can read from each product page.