Why supplier data is becoming a bottleneck in digital value creation
Retailers with an extensive product range or a growing supplier network are familiar with the problem: every supplier delivers data differently - in terms of structure, content and form. While some send complete BMEcat catalogs, others come with simple Excel spreadsheets or unstructured media packages.
Typical consequences:
- Time-consuming manual data maintenance
- Incomplete or incorrect article master data
- Delays in online listing
- Inconsistencies in the PIM system, in the store or in marketing materials
In e-commerce in particular, such problems have a direct impact on time-to-market and conversion rates - and cause unnecessarily high process costs.
What modern supplier data onboarding needs to achieve
A modern onboarding process for supplier data fulfills four key tasks:
- Process format diversity: Support common data formats such as BMEcat, Excel, CSV, XML and JSON - ideally automated.
- Validate and enrich content: Check for completeness, mandatory fields, duplicates and semantic quality.
- Data mapping & transformation: The supplied data must be mapped to internal taxonomies, classifications (e.g. eCl@ss, ETIM) and system logics. This mapping is crucial for interpreting data correctly and integrating it into PIM, ERP or e-commerce systems in a structured manner.
- Seamless integration: transfer of the processed data to central systems - without media disruptions and without repeated manual intervention.
The better these steps are technically supported, the faster products reach the point of sale - and the fewer resources data onboarding ties up internally.
Data onboarding: technological solutions for digital retail
In practice, many retailers lack an end-to-end process for onboarding supplier data. Interfaces between external data sources and internal systems are often fragmented, media disruptions and manual intervention are the rule. Traditional PIM or ERP systems quickly reach their limits here, and self-developed solutions often do not cover all use cases.
This is where specialized platform solutions such as gateway come into play, which were designed precisely for this transition. They take over the technical management of onboarding - from validation, semantic checking and data mapping through to integration into existing IT landscapes. Increasingly, AI-supported services are also being used, for example for automated classification, text generation or semantic checking. This allows not only structured but also complete product data to be generated - with significantly reduced manual effort.
Would you like to process supplier data efficiently and optimize your onboarding processes?
Conclusion: Data onboarding as part of the digital strategy
Those who process their supplier data efficiently not only improve the quality of individual product information, but also create the basis for end-to-end digital processes. Onboarding - including structured data mapping - thus becomes a strategic component of a modern data strategy. It shortens project runtimes, increases scalability and reduces maintenance and control costs in the long term. Especially in the competition for visibility and speed at the digital point of sale, the ability to integrate new products quickly and error-free becomes a real success factor.