What are Product Data Transformations?
Product data transformation changes data from one format, structure or value to another.
Automated product data transformations are an effective method of data cleansing for eCommerce, normalizing and preparing supplier product data ready for an eCommerce website or PIM.
The graphic below outlines the most common examples of data transformations we set up here at Vesta for the on-going cleansing of supplier data for our clients.
Product Data Transformations Key Examples:
Adding = Add a word, number, space or punctuation.
Deleting = Remove a word, number, space or punctuation
Replacing = Find and replace key words
Calculating = Complete a calculation on a number (e.g. x20%)
Moving = Moving a word, phrase or number to a new location
Extracting = Extract information from one field and place it in another (e.g. HxWxD extract each to a unique field)
Sorting = Putting data in a specific order (e.g. S, M, L, XL)
Expanding = Expanding acronyms and abbreviations (eg. BLK = Black)
Replicating = Replicating the same data into 2 areas of your product catalog
Joining = Putting 2 or more attributes together (e.g. height x length)
Filtering = Filtering data for a select group (e.g. Price = $0)
Photo editing = Changing the size, resolution or cropping of images
Pull in Supplier Data ➡️ If Product Name contains "polo" then add to category Apparel/Shirts/Polo's ➡️ Update in BigCommerce Store
Interested to learn more?
Learn how data transformations are applied in eCommerce here
Read our blog ''What is product data transformation?'' here
Or book a call with one of our friendly team to talk more about how Vesta can assist you with automating your data cleansing for eCommerce.