The Time Has Come for a Product Data Interchange Standard
It’s a billion dollar problem
Dakota estimates that every month, terabytes of product data are transmitted between manufacturers, distributors, and retailers to enable on-line and in-store sales. Most product data is exchanged as spreadsheets and CSV files, with supporting digital assets in a variety of formats, mostly images and PDF documents. None of this data conforms to a standard. Why? Because there is no standard for product data interchange.
Because of the lack of a data interchange standard, distributors and retailers spend an inordinate amount of time, effort, and money to “cleanse” and “enhance” the product data they get from manufacturers. Why? They do this to gain an advantage in the marketplace. Better data and richer product information increase traffic, sell more products, increase customer loyalty, and contributes to “brand” value.
Depending upon product margins and volumes, a channel player may spend between $1 and $20 per SKU enhancing product data. This can include:
- Classifying the products to the their own merchandising taxonomy
- Normalizing attribute values and units of measurement to assure that faceted search works correctly in their online catalog
- Filling attribute values that the manufacturer did not provide (which include technical specs as well as their own merchandising attributes such as “application”)
- Improving product imagery (including generating their own video and 360° photography)
- Writing “romance” copy
If the B2B manufacturer community alone produces 1M new products each month (>10M new products each year), retailers and distributors can easily spend $1B annually on enhancing product data just for newly released products.
The time has come for a product data interchange standard. A minimum viable product interchange data standard would provide these foundational methods for transmitting taxonomies and item data:
- Taxonomy & attribute definitions
- Defining a product taxonomy (consisting of the hierarchy, terminal categories, and the category attributes)
- Attribute definitions (written for merchandisers, not end users)
- Typing of attribute values (e.g. numeric, text, Boolean, enumerated lists, etc.)
- Standard units of measurement (UOMs)
- Primary and secondary measurement systems (e.g. metric and imperial)
- Product item data definitions
- Classification of items/SKUs to categories
- Attribute name-value pairs for each SKU
- Separation of attribute values from UOMs
- Discrete high and low values for ranges
- Multiple UOMs per attribute
With such a minimum data interchange standard, even in the absence of shared taxonomies, distributors and retailers would be able to quickly cross-map attribute labels and categories to their own, and would have well-formed product data from the manufacturers.
Ideally, manufacturers and distributors in the industry would share segment-specific product taxonomies and would reach consensus on attribute labels and definitions. Agreement on a product data interchange standard is a necessary first step. Once industries agree on the data interchange standard, they would use it as a framework for defining shared taxonomies.
Dakota is committed to furthering the cause for a product data interchange standard. Over the coming year we will coordinate with major manufacturers and distributors in key B2B industry segments to begin the hard work of defining the standard. Stay tuned here, in social media, and in the major B2B digital press for more news on this exciting project.