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In Episode 10 of the podcast "Navigating Data," the discussion centers on the vital practice of 'spring cleaning' product data to enhance quality and prevent shopper abandonment, as 87% of consumers leave purchases due to inconsistent product information. The episode outlines eight key criteria for effective product data management, including completeness, correctness, uniqueness, and integrity, while emphasizing the necessity of Product Information Management (PIM) systems for automating data cleaning. It also highlights global data management challenges, such as cultural and linguistic considerations, and introduces apollon's OMN PIM solution as a tool for maintaining data quality. The episode concludes with a reminder of the significant impact that data quality has on business success and encourages listeners to explore apollon's PIM and Digital Asset Management systems further.
https://hubs.li/Q02W6dXW0
By apollon GmbH+Co. KGIn Episode 10 of the podcast "Navigating Data," the discussion centers on the vital practice of 'spring cleaning' product data to enhance quality and prevent shopper abandonment, as 87% of consumers leave purchases due to inconsistent product information. The episode outlines eight key criteria for effective product data management, including completeness, correctness, uniqueness, and integrity, while emphasizing the necessity of Product Information Management (PIM) systems for automating data cleaning. It also highlights global data management challenges, such as cultural and linguistic considerations, and introduces apollon's OMN PIM solution as a tool for maintaining data quality. The episode concludes with a reminder of the significant impact that data quality has on business success and encourages listeners to explore apollon's PIM and Digital Asset Management systems further.
https://hubs.li/Q02W6dXW0