Data Quality

Definition

Data quality refers to the overall utility and reliability of data for its intended purpose. In the context of PIM, it involves ensuring product information is accurate (correct values), complete (no missing fields), consistent (uniform format across products and channels), timely (up-to-date), and valid (conforms to defined rules).

Why It's Important for E-commerce

High data quality builds customer trust, improves conversion rates (accurate details lead to purchases), reduces returns (fewer surprises for customers), enhances SEO (complete data ranks better), and enables effective personalization and analytics. Poor data quality leads to lost sales, operational inefficiencies, and brand damage.

Examples

• Ensuring all product weights and dimensions are accurate.
• Making sure brand names are spelled consistently across all products.
• Validating that EAN codes follow the correct format.
• Checking that all mandatory fields for a specific channel are filled before export.
• Regularly updating pricing and stock information.

How WISEPIM Helps

• **Validation Rules:** Define rules to automatically check data completeness and correctness upon import or entry.
• **Completeness Scores:** Visualize the completeness of product data across different attributes or channels.
• **Bulk Editing:** Quickly fix inconsistencies or update information across multiple products.
• **Data Profiling:** Identify patterns and anomalies in your product data to pinpoint quality issues.
• **Controlled Workflow:** Implement approval processes to ensure data is reviewed before going live.

Related Terms

Also Known As