developers.fitanalytics.comFit Analytics Documentation

Feed About FitFinder integration Documentation Sections Feed 1.1 Product Feed Introduction 1.2 Product Feed Requirements 1.3 Product Feed Example 1.4 Feed Attributes Details Returns Feed 2.1 Returns Feed Introduction 2.2 Returns Feed Details 2.3 Returns Feed Example Useful Resources 3.1 Useful Resources 1.1 Product Feed Introduction 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. 1.2 Product Feed Requirements 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 & AccessoriesClothingDresses clothing & accessoriesclothingwomen’s clothingdresses 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. HomeWomenDressesMaxi 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 1.3 Product Feed Example Find a product feed example here for download. 1.4 Feed Attributes Details 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...