Examples of Product Data Transformations

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

Example Transformation:

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.