Retailer: Simplify your processes with the Conversion Hub

Explaining the solution: A Detailed look at Conversion Hub's components

To fully understand how Conversion Hub enhances retail data management, it’s essential to dive into the specific components and data flows that make up this innovative system. Each component plays a critical role in simplifying the data handling process, from initial mapping to final usage in internal systems. Here, we detail the steps involved in transforming raw supplier data into actionable business intelligence, ensuring retailers can maximize efficiency, compliance, and data quality throughout their operations.

1. Mapping data requirements with the Data Mapper

Retailers start by using the Data Mapper to outline their precise data needs. This can be done universally across all product types or tailored to specific product types or groups, ensuring customizability and relevance.

The Data Mapper also supports the integration of industry data standards such as GS1 and ETIM. These standards are automatically updated within the Data Mapper, ensuring compliance and up-to-date formats without manual intervention.

2. Feeding data structures to the Data Collector and Converter

Once the desired product data structure is defined, the Data Mapper automatically updates this structure across the suppliers’ data supply channels via the Data Collector and Converter. This ensures that all incoming data from suppliers conforms to the predefined structures, facilitating consistency and accuracy.

3. Supplier data input and delivery

Suppliers not integrated into the Conversion Hub platform can manually add their data to the Data Collector, which acts as a product information portal.

Suppliers who use Conversion Hub can add data directly into their systems. This data is then automatically converted to match the required structure through the Data Converter, streamlining the integration process.

4. Collecting data from multiple sources

Data from both the Data Collector and supplier’s Data Converter automatically flows into the retailer's Data Processor in the correct structure as explained above.

If necessary, data can also be imported and converted directly from product information banks such as Finnish GS1 based datapool Synkka and ETIM based datapools Sähkönumerot, LVI-Info, and Rakennustieto into the designated structure.

Retailers have also the option to automatically import suppliers' master data from Excel files or establish other for instance direct connections to ERP or other systems, enhancing data fluidity and accessibility.

5. Reviewing, editing, and working data in the Data Processor

Once in the Data Processor, all data is centralized in one accessible location. Retailers can view, edit, and process this data as needed, utilizing tools for data types, overviews, statistics, dashboards, and artificial intelligence (AI) to extract meaningful insights and ensure data integrity and quality.

6. Automatically connecting data to your internal channels

Data is formatted into the desired structure (XML, JSON, BMEcat, API, etc.) and automatically transferred directly to retailer's essential channels such as PIM system, ERP system, or CRM for instance. This automation supports real-time updates and reduces the need for manual data handling, boosting overall operational efficiency.

Benefits for the retailer

Conversion Hub centralizes data collection on a single platform, enabling customization and compliance with updated standards. This streamlines processes, enhances data quality, and reduces manual effort, freeing up retailers to focus on strategic growth.

The key benefits are:

• Centralize data collection: All supplier data is centralized and collected in a single platform, eliminating the need to juggle multiple files and formats.
• Desired data structures: Customize data structures at the product type or group level, ensuring that the data aligns with specific business needs.
• Utilize data standards: Utilize ongoing updated product data standards to ensure compliance and consistency across all product information.
• Richer and better data: Unlock richer data and enhanced data quality and broader data to improve sales.
• Constantly updating data: Constantly receive updated and standardized data automatically from suppliers without constant manual intervention.
• Better data insights: Enhanced data for better decision-making through overviews, statistics, and dashboards supported by AI technologies.
• Minimize the time and effort: Minimize spent time on manual data collection, entry and corrections, which reduces the risk of errors and improves operational efficiency.
• Focus more on strategic initiatives: Rather than working on mundane data management tasks, enhance productivity and operational efficiency.