General Introduction

As a global sizing leader, the world's best apparel and footwear companies trust us to solve sizing and help them sell smarter. Our Fit Services have been proven to boost conversion rates and slash returns by leveraging the data that we collect about products and shopper behavior.

The importance of high data quality in maximizing the impact cannot be overstated. In particular, precise and accurate data in your product feed allows us to

• enable our services for more products, thus increasing shoppers' exposure to our services,
• correctly tailor the user experience,
• improve the accuracy of our recommendations, and
• integrate smoothly, allowing Fit Services to go live faster.

Purpose

This product feed specification provides the guidelines and rules to which the feed should conform. It is a guide to help you understand the mandatory data requirements for your product feed and it defines in detail what the format of the data should be with examples and best practices. This document is meant to be the data specifications support material from the sales deck of the Fit Finder Standard service. The product feed is the most critical part of the Fit Finder integration and requires high quality information and data structure. A high impact product feed allows Fit Analytics to import garment information to the Fit Finder database.

Good data quality ensures a smooth Fit Finder integration and leads to strong size recommendations, ensuring the best tailored experience to users.

Feed Format

The product feed should be passed to Fit Analytics either via (S)FTP or HTTP(S) dynamic link, which should be automatically updated at least once every day.

That link should direct to a CSV or XML (RSS/Atom) feed using UTF-8 encoding. There must be a separate feed entry for each size variant, and the attribute names must match the names in the "Attribute" column of the tables below.

If you already have a Facebook or Google product feed, you’ll likely only need a few adjustments, the main one being the addition of an item_subgroup_id attribute.

If you have multiple online stores or versions of your store with different sizing, product availability or languages, we require a separate product feed for each.

• Example 1: If you have French and Dutch language versions of your Belgian store, we require separate French and Dutch feeds.
• Example 2: If your European stores all share the same sizing, product availability and language (e.g. English), then it’s fine to provide a single European feed.

Feed Mandatory Data

Fit Services like Fit Finder can only be enabled if all of the following attributes are provided for the product in question. If you can’t provide the values as requested, please contact us so we can suggest how you could solve this.

Mandatory Data Table

Attribute	Short description	Examples
id	An ID that uniquely identifies a size variant of a garment.	12345-250-11 12345-BLACK-S
item_subgroup_id	An ID that uniquely identifies a color variant of a garment, grouping together all sizes for a specific combination of color, material, pattern, etc. For example, all sizes of a given red dress should have the same item subgroup ID, but the same dress in blue (or in a different material or pattern) should have a different item subgroup ID.	1234567 12345-250 12345-BLACK
item_group_id	An ID that groups together all variants of a garment. Variants are a group of similar products that only differ from one another by product details like the size, color, material or pattern.	12345
brand	The product’s brand name, manufacturer or designer, which allows us to customize recommendations by brand.	Esprit Nike Adidas Puma
gender	The Fit Finder flow differs between men’s and women’s products, e.g. recommendations for women require bra information. The [gender] also allows us to tailor size recommendations, e.g. men’s sizes typically fit differently than women’s sizes. Products should be classifed as unisex if that product can be recommended for women and men.	male female unisex
age_group	The demographic that your product is designed for. Correctly distinguishing between adults’ and kids’ products is important. A kids’ product that is mistakenly marked as for adults might lead to inaccurate size recommendations for the product in question and might pollute our machine learning data, skewing recommendations for other products.	kids adult
size	The localized size string that is displayed to shoppers on the product detail page. We recommend adding the size system in the size strings on the PDP and in the product feed, e.g. UK 10 rather than just 10, to reduce confusion for your shoppers.	32 UK 6.5 Small XXXL
size_system	The country’s sizing system that your product uses.	UK US EU
size_type	The body type for which the garment is designed.	regular petite plus tall big maternity
link	A URL pointing to the product detail page on the shop website.	http://au.exampleshop.com/TZZ12345-105-51.html
image_link	A URL pointing to the main product image.	http://au.exampleshop.com/TZZ12345-105-51.jpg
title	A brief description of the product.	Adidas trainer Long sleeve blouse
fb_product_category or google_product_category	The product category according to the Facebook product taxonomy (preferred) or the Google product taxonomy. At least one of the two must be provided, since the product category affects the Fit Finder user experience and size recommendations. For example, shoppers are asked to input bra information for tops, but not for bottoms, and a size M for a dress may fit differently than a size M for shorts. If you're only able to provide the Google product category, please additionally provide the [product_type] attribute (see "Feed Optional Data" below) so that we can better customize size recommendations for different shoe types.	2271 Apparel & Accessories > Clothing > Dresses clothing & accessories > clothing > women's clothing > dresses
availability	Whether a product is in or out of stock.	in_stock out_of_stock

Feed Optional Data

The following attributes help with detecting feed data quality issues that could affect size and style recommendations, and tuning for which products Fit Services are enabled.

Optional Data Table

Attribute	Short description	Examples
product_type	The product type according to your own product categorization system.	Home > Women > Dresses > Maxi Dresses
gtin	The Global Trade Item Number (GTIN), also known as the EAN or UPC, that uniquely identifies a size variant of a garment in a globally standard way.	3234567890126
color	The product’s color.	Green
material	The main fabric or material that your product is made of.	Cotton
pattern	The pattern or graphic print on your product.	striped

Find a product feed example here for download.

Color variant ID [item_subgroup_id]

Use the color variant ID [item_subgroup_id] attribute to group together all sizes for a specific combination of color, material, pattern, etc. For example, all sizes of a given red T-shirt should have the same item subgroup ID, but the same T-shirt in blue (or in a different material or pattern) should have a different item subgroup ID.

• Required for each product
• Format: String (Unicode characters. Recommended: ASCII only); 1–70 characters
• Examples: 1234567, 12345-250, 12345-BLACK
• Matching item subgroup IDs must be available on product detail pages (PDPs) and order confirmation pages (OCPs) on your website and mobile apps.
• The item subgroup ID must not be reused later for a different garment. It must be unique in the history of your shop.
• The item subgroup ID must be locale-independent. For example, if 12345-BLACK appears in the product feed for your US store, then it must also appear as 12345-BLACK (not e.g. 12345-NOIR) in your French store.
• Avoid changing item subgroup IDs. Doing so may lead to an interruption of Fit Services if for example the IDs on PDPs are updated before a product feed with the new IDs has been ingested into the Fit Analytics database. It may also lead to a gap in training data for our size recommendation models if we aren’t able to link Fit Finder inputs, purchases and returns due to mismatched IDs.

To benefit from the complete Fit Finder experience and the machine learning process of the recommendation engine, Fit Analytics requires a returns feed. That feed allows us to import returns data to our database and matches the return to the purchases for your shop. When sharing the file, it’s important to pay attention not only to the attributes and format but also to the data quality:

• Good data quality leads to a quicker, smoother import of data into the database.
• Good data quality leads to better size recommendations, ensuring a good user experience.

Fit Analytics requires an HTTP(S) or (S)FTP URL pointing to a CSV feed using UTF-8 encoding. If your shop is live in multiple countries, we require returns for all locales where Fit Finder is live. Important details regarding the format, frequency and availability of the feed:

• Returns should ideally be exported on a daily basis. Weekly or monthly exports are also supported, but there will be more of a delay until the returns are reflected in reports and in size recommendations.
• The filename must include the export date in the format YYYYMMDD.
• The files should only include new returns that came in since the previous export.
• Files should remain available for some time (ideally at least a month), so that Fit Analytics can re-ingest them in case of an error.

Returns Feed Details Table

Attribute	Short description	Examples
return_id	An ID that uniquely identifies the return event.	82934601982
timestamp	The date and time of the return event.	2024-01-01T10:00:00Z
order_id	An ID that identifies the original purchase order that included the item now being returned. The order ID in the return feed must match the order ID reported from the order confirmation page when the item was originally bought.	1234567
item_id	An ID that uniquely identifies a size variant of a garment.	12345-250-11
quantity	The quantity of items being returned.	2
return_reason	The reason why an item was returned. Used for improving the recommendation system and for reporting. Only required if a shop collects return reasons and if the purchase was not canceled.	big small fit style other
is_canceled	Whether or not the purchase was canceled, as opposed to having been received and then returned. Only required if the user has the option to cancel a purchase on your website.	true false

Find a return feed example here for download.

• Product feed example download
• Returns feed example download
• Data Object Documentation