Efficient onboarding of product data

A product information management system stands and falls with the quality of the data it manages. When introducing a PIM system, the focus is often on the output channels, but the import side is at least as important. When continuously importing product data from different suppliers, it must be ensured that all information is accurate, up-to-date and consistent. However, this process is complex and poses challenges for distributors and manufacturers alike. How can product data be transferred to the PIM system as efficiently as possible? What problems frequently occur and how can they be solved?

What is onboarding in PIM systems?

Onboarding refers to the process of importing, validating and structuring product data from different sources into a PIM system. The aim is to create a consistent and high-quality database that can then be used for various sales channels. A well-executed onboarding process reduces sources of error, improves efficiency and makes it easier to manage large volumes of data.

ETL: The triad of data processing

A central component of onboarding is ETL (Extract, Transform, Load). This three-stage process ensures smooth data integration:

• Extract
  Data is collected from various sources, for example from XML and Excel files or via REST web services in JSON format.
• Transform
  The data is cleansed and converted into a standardized format. This also includes conversions into suitable units of measure and quantity.
• Load
  The prepared data is imported into the PIM system. Checking rules help to avoid incorrect or nonsensical data.

Modern PIM systems such as crossbase have integrated ETL functions that significantly reduce the effort required for data integration.

Challenges when onboarding product data

Problems often arise when importing product data, especially when suppliers use different structures and formats.

The biggest challenges include

• Inconsistent data formats
  Different names and structures for attributes such as size, weight or color make integration difficult.
• Lack of standards
  Without clear rules for data exchange, such as mandatory information, inconsistencies arise.
• Variety of variants
  Many products exist in numerous variants that differ only in details. Managing these variants is often time-consuming. A PIM can provide support here with a hierarchical structure and inheritance logic.

Solution: Mapping and standardization

Two central approaches are helpful in overcoming these challenges:

• Data mapping
  This involves transferring data fields from different sources into a standard structure. This ensures that all product information is correctly assigned and stored consistently.
• Classification systems such as ETIM or ECLASS
  These systems help to classify product data into standardized categories, which facilitates the exchange between different systems and partners.

Conclusion

Efficient onboarding of product data is essential for the success of a PIM system. ETL processes, data mapping and the use of classification standards can overcome typical challenges. Companies that apply these methods benefit from precise, up-to-date and consistent product data - an important basis for successful e-commerce and digital processes.