Kennerpim Features Data Processing

Data processing with KennerPIM

A PIM system is essential for efficient product data processing and centralised storage. It allows PIM data to be captured, structured and distributed across various channels. The central product information management database serves as a valuable repository for managing technical and marketing-related information. Using this tool improves data quality, simplifies maintenance and boosts efficiency.

The most important data processing processes include:

Data imports;
Maintenance and enrichment;
Structuring;
Localisation;
Data exports.

Data processing can be significantly improved through the use of PIM systems. Business processes can be accelerated. You no longer need to worry about the quality and consistency of PIM data.

Data processing

Why is automated data processing with KennerPIM necessary?

Using the PIM solution is essential if your online shop offers a wide range of products or if the data is complex. Publishing information across multiple sales channels is much easier with KennerPIM, as many processes are automated. This ensures that the data is always consistent. It also allows you to significantly reduce time and resources, avoid data duplication and errors, and increase business efficiency.

Process automation solves the following issues:

Collecting PIM data from various sources;
Structuring attributes and assigning them to media;
Automatically publishing product information in online shops, on marketplaces and in print catalogues;
Reducing the time spent on data optimisation and updates;
Scaling up quickly.

Data processing process: 6 phases

Product data processing in KennerPIM comprises several clearly structured phases. The information is first captured and enriched. Its quality is then checked. Only then can the data be officially released and distributed across sales channels. The automated data processing process comprises the following phases:

Data capture/import. Data is collected from various sources (ERP, CRM, inventory management and product data management systems, Excel spreadsheets, external databases). All information can be consolidated centrally in KennerPIM.

Data preparation. The product data is cleaned up in the PIM system. This allows missing information to be added, input errors to be corrected and duplicates to be removed.

Data enrichment. The content is localised for different markets. Images, videos and marketing texts are added. In KennerPIM, you can track the origin of the data. This allows you to monitor the entire product lifecycle right through to its destination and determine which source the information comes from.

Data maintenance and quality assurance. To ensure product information remains consistent, it should be regularly checked and updated. This prevents outdated images or prices appearing in the online shop.

Data release (export). Product information can be distributed via various sales channels (online shops, marketplaces, apps). Once checked, it is officially released. Authorised users are assigned roles so that they can modify and edit the information.

Monitoring and optimisation. Full control over product data guarantees the highest quality across all channels.

The benefits of well-organised data processing

The better the data is processed, the more efficiently business processes are carried out. This provides a solid foundation for efficiency, scalability and customer satisfaction.

Advantages	Explanation
High Data Quality	The information is complete and consistent. There are fewer errors and no duplicates.
Efficiency Improvement	Processes are accelerated because no time is lost on maintenance and updates. Data can be accessed quickly.
Improved Collaboration	Since employees across all departments receive consistent information, there are no misunderstandings. All workflows are transparent.
Flexibility	KennerPIM integrates perfectly with third-party systems. It can be easily scaled by adapting data for new channels and markets.
Fast Time-to-Market	PIM data is immediately available and ready to be published.
Customer Satisfaction	Data consistency builds customer trust, leading to an improved customer experience.