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Data import

Data management and qualityBasic Level

Data import is the process of bringing data from an external source into a target system. In e-commerce, this often involves populating a PIM with product information from various sources like ERPs or supplier feeds.

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What is Data import?

Data import is the process of bringing information from an outside source into a software system. It fills your platform with the details needed to run your business. This allows you to manage data that was originally kept in a different place. You can import data from spreadsheets, CSV files, or XML files. You can also pull data directly from other tools like an ERP or CRM. WISEPIM uses data imports to gather product details from many suppliers into one central hub.

Why Data import matters for e-commerce

Data import is a process that moves product information from external files or systems into an e-commerce platform. It helps businesses manage large catalogs without typing every detail by hand. Most stores get their data from suppliers or internal systems like an ERP (Enterprise Resource Planning). Manual entry is slow and often leads to mistakes in descriptions or prices. Automated tools like WISEPIM make this process faster and keep product lists accurate. This helps you launch new products quickly and update prices across thousands of items instantly.

Examples of Data import

  • 1A PIM system brings in new product codes and details like names and prices from an ERP system.
  • 2A store updates its stock levels and prices every day by uploading a file from a supplier.
  • 3A business moves its whole product list from an old online store to a new PIM system.
  • 4A team adds new product descriptions and photos sent by a content agency into the system.
  • 5A user uploads a spreadsheet to add product options like sizes and colors to the database.
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How WISEPIM Helps

  • Automated connections link WISEPIM to your ERP, CRM, and supplier portals. You can schedule imports to save time and reduce manual effort.
  • Simple data mapping lets you match incoming files to your PIM fields. It works with any file format to eliminate manual data entry.
  • Data quality checks use rules to scan information as it enters the system. This ensures your product data stays accurate and consistent.
  • Change tracking records every import so you can monitor updates. You can view past versions and undo changes easily.
  • Fast processing handles large amounts of product data in seconds. The system remains stable and reliable as your product catalog grows.

Common mistakes with Data import

  • Skipping data validation before you start. This leads to broken records and mismatched information across your systems.
  • Forgetting to map data fields correctly. Mapping matches source data to the right destination. Errors put information in the wrong place.
  • Overwriting existing data without saving a backup first. Always check how new imports will change your current records to avoid data loss.
  • Failing to match formats or units from different sources. You must standardize data to avoid quality issues in your product catalog.
  • Using manual imports for daily tasks. This process is slow and increases the risk of small but costly human errors.

Tips for Data import

  • Use validation rules to check all incoming data. This stops incorrect or messy information from entering your system.
  • Create clear guides for data mapping. This shows how fields from your source file match the attributes in your PIM system.
  • Use a test environment to check new data imports. This helps you catch mistakes before they affect your live webshop.
  • Automate your imports with scheduling tools. This reduces manual work and keeps your product information consistent.
  • Set up error alerts for your imports. This helps you find and fix issues immediately during the data transfer process.

Trends around Data import

  • AI-powered data validation and cleansing tools automatically detect anomalies, suggest corrections, and standardize incoming data.
  • Increased adoption of automated data orchestration platforms for seamless, scheduled, and triggered data imports from various sources.
  • Real-time data synchronization becomes standard, especially for headless commerce architectures, minimizing latency between data sources and storefronts.
  • Enhanced data governance frameworks specifically for import processes, ensuring compliance and maintaining a clear audit trail of data origin and transformations.
  • Focus on 'sustainable data' practices, optimizing import processes to reduce data redundancy and storage, contributing to lower energy consumption.

Tools for Data import

  • WISEPIM: Centralizes product data, streamlines complex imports from various suppliers and ERPs, and ensures data quality across all sales channels.
  • Akeneo PIM: Offers advanced data import capabilities for managing diverse product information, attributes, and digital assets effectively.
  • Salsify: A Product Experience Management (PXM) platform that provides robust tools for importing, enriching, and syndicating product content.
  • Shopify: Provides built-in CSV import functionalities for products, customers, and orders, suitable for direct e-commerce management.
  • Magento (Adobe Commerce): Features powerful and flexible data import/export tools for extensive product catalogs, customer data, and order information.

Related Terms

Access Control (PIM)Attribute Dependency ManagementAttribute InheritanceAttribute ManagementAttribute mappingAttribute Scoping

Also Known As

Data ingestionData uploadData migrationData synchronization (one-way)

Frequently Asked Questions

In PIM for e-commerce, data import is the process of loading product-related information, such as SKUs, attributes, descriptions, prices, and media assets, from various external sources into the PIM system. This centralizes product data, making it ready for enrichment, validation, and distribution to sales channels.

Efficient data import saves time and reduces manual errors associated with product data entry and updates. It ensures that product information is consistent and accurate across all channels, accelerates time-to-market for new products, and supports scalability for growing product catalogs, directly impacting customer experience and operational efficiency.

A PIM system can import a wide array of product data, including core product attributes (names, descriptions, SKUs), technical specifications, marketing content, digital assets (images, videos, documents), pricing information, stock levels, product relationships (e.g., cross-sells, up-sells), and category assignments. This data typically comes from ERP, DAM, or supplier systems.

WISEPIM handles complex data import scenarios through flexible data mapping tools that allow users to match fields from diverse source formats to PIM attributes. It includes robust data validation rules to maintain data quality and supports automated import schedules, API integrations, and version control for tracking and managing changes effectively, even for large and varied datasets.

E-commerce businesses can ensure data quality during import by implementing robust validation rules, data cleansing processes, and thorough mapping configurations within their PIM system. Regularly reviewing imported data for discrepancies, standardizing formats before import, and utilizing data governance policies also help maintain accuracy and consistency.

PIM users should prioritize automated data import to significantly reduce manual effort, minimize human error, and accelerate time-to-market for new products. Automation ensures that product information across all sales channels is consistently up-to-date, improving operational efficiency and providing a better customer experience.

E-commerce managers should consider factors such as supported file formats, integration capabilities with existing systems (ERP, CRM), scalability for future growth, and the level of data validation and transformation features offered. Usability of the import interface, error handling mechanisms, and reporting functionalities are also crucial for efficient data management.

A full data import is advisable when initially setting up a PIM system, migrating from an old system, or when significant structural changes have occurred that affect a large portion of the product catalog. Incremental updates, on the other hand, are ideal for routine tasks like updating stock levels, price changes, or adding new product attributes, as they are faster and less resource-intensive.

One frequent error is failing to map source columns to the correct target attributes, leading to scrambled product descriptions or incorrect pricing. Another mistake is ignoring data formatting requirements, such as date structures or currency symbols, which causes the import to fail. Many teams also forget to back up their current database before a major import, making it difficult to revert changes if the new data contains widespread errors or duplicates.

In smaller companies, an e-commerce manager or catalog specialist usually handles imports. As businesses scale, this role often shifts to a Data Steward or PIM Manager who oversees data integrity. They work closely with IT teams to set up technical connections and with procurement or category managers to ensure the incoming supplier data is accurate. For complex technical setups, a data engineer might be involved to manage API integrations.

Connecting an ERP to a PIM typically involves using an API (Application Programming Interface) or a middleware connector. The ERP acts as the source of truth for inventory and base pricing, pushing this data to the PIM at scheduled intervals. Alternatively, some systems use a hot folder method where the ERP drops CSV or XML files onto a secure server, and the PIM automatically picks up and processes those files as soon as they appear.

Start by auditing your source files for consistency; ensure every product has a unique identifier like a SKU or EAN. Clean up your data by removing duplicate entries and fixing spelling errors. Next, define your attribute mapping—decide exactly which column in your spreadsheet corresponds to which field in your software. Finally, perform a test import with a small batch of ten items to verify that images and categories appear correctly before processing the entire catalog.

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