Insights & Resources

Migrating to a new Product Information Management (PIM) system or implementing one from scratch is a complex task. One of the biggest challenges companies face during this process is dealing with bad quality product data. Poor data quality can slow down the migration, increase costs, and even cause the new system to fail in delivering its expected benefits. Understanding how bad product data affects PIM projects helps businesses prepare better and avoid costly mistakes. Incon

In ecommerce, customers rely heavily on filters to narrow down product choices quickly and efficiently. When filters work well, shoppers find exactly what they want without frustration. But inconsistent or non-standardized data can cause filters to fail, showing irrelevant or duplicate results. This problem often arises when product attributes are recorded in different formats or use synonyms that confuse the system. For example, a filter might treat "1" and "1.0" as two sepa

Online shopping has become a daily routine for millions, yet many customers still face frustration when product information is unclear or incomplete. Quality product data plays a crucial role in shaping the ecommerce experience, directly influencing customer satisfaction and loyalty. This post explores how accurate, detailed, and well-organized product data improves the shopping journey and benefits both customers and retailers. Detailed product specifications displayed on an

Online shoppers expect clear, accurate information when browsing products. When product details are incomplete or misleading, customers often receive items that don’t meet their expectations. This mismatch leads to frustration and a higher chance of returns. Understanding how product data quality affects return rates can help online retailers reduce costs and improve customer satisfaction. Detailed product page with clear specifications and images Why Product Data Quality Mat