ECommerce Product data cleansing process involves
- Data Analysis – Identify critical product data for cleansing. Analyze the product data for missing information, duplication and gap analysis.
- Data De-duplication – Set validation rules to find the duplicates. Automated workflow systems use those validation rules to remove the duplicates.
- Standardize Data – To maintain data consistency, specified rules and parameters are set for the various components in a product data like the SKU number, price, Meta tags, product URLs, etc.
- Normalize Data – Redundant data is removed and checked for inconsistencies.
- Quality Check – Check product data again for the quality and repeat the process till will we arrive at 100% quality.