Data quality as a strategic success factor
In digital trade, significant investments are being made in new systems, interfaces and sales channels. Yet it remains challenging for many companies to efficiently scale business across multiple platforms.
A bottleneck that is often overlooked: the quality of product master data.
Many retail companies — whether in the B2B or B2C sector — work with inconsistent, outdated or incomplete product information. Data quality in e-commerce is no longer an optional issue, but the central requirement for scalable multichannel strategies, reliable automation and consistent customer experiences.
The brake in product data management
As long as processes can be compensated manually, the data problem is tolerated by many companies. But with the expansion of marketplace business, system integrations or the introduction of automated processes, it becomes clear that without clean and scalable data structures, even the most powerful technical solutions reach their limits.
In addition, the longer you wait with structural adjustment, the greater the effort — and the more serious the effects.
Typical consequences of inadequate product data management:
- High time and costs due to manual post-processing
- Delayed product releases on new sales channels
- Media breaks and redundant data storage
- Incompatibility with marketplace-specific requirements
- Inconsistent presentation of product information on different platforms
Optimizing master data means securing the future
Systematic product data management is essential to realize scalability and automation potential in e-commerce.
Three key measures form the basis for sustainable growth:
- Adjustment and standardization of product master data
Duplicates must be removed, attribute values standardized and mandatory fields must be fully maintained. Only consistent data enables reliable playback across all channels.
- Establish scalable data structures
Taxonomies, attribute sets, and category logics should be defined in such a way that they are logically structured and expandable to meet future requirements. A well-thought-out data structure is a prerequisite for efficient processes and seamless interface connections.
- Introduction of a central PIM system
A Product Information Management System (PIM) creates the central instance for all product-related information. Modern PIM systems not only enable consistent data maintenance, but also the implementation of channel-specific requirements — without redundant data sets. This creates the necessary flexibility for multichannel sales.
No marketplace success without a data strategy
Anyone who invests in marketplaces without a well-thought-out data strategy risks lost revenue and inefficient operating processes.
Companies that invest in a clean, central database at an early stage create sustainable structural advantages — technologically, organizationally and procedural.
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