High-quality data ensures that your products are represented correctly and effectively across all channels. Here’s our top seven tips for maintaining quality product data:
Accuracy: Data must be correct and reflect real-world attributes of the products. Errors or inaccuracies in product data can lead to customer dissatisfaction and lost sales.
Completeness: Make sure all necessary information is provided and regularly updated. Product data should be comprehensive, covering all necessary attributes (e.g., descriptions, specifications, images). Incomplete data can hinder decision-making and user experience.
Consistency: Data should be uniform across different systems and platforms. Inconsistent data can cause confusion and reduce trust in the product information.
Timeliness: Product data must be up-to-date. Outdated information can lead to issues such as incorrect stock levels or obsolete product details.
Relevancy: Ensure that the data provided is pertinent to the needs of the stakeholders, such as customers, sales teams, and supply chain partners. Establish channels for receiving feedback on data quality from users and stakeholders to identify areas for improvement.
Valid and clean: Implement validation rules to ensure that data entered meets pre-defined standards and is accurate. Regularly clean and update data to remove duplicates, correct errors, and fill in missing information.
Secure: Implement measures to protect sensitive data from unauthorized access or breaches.
Regular monitoring of defined metrics and performing audits will help you promptly identify data quality issues. There are many automated tools (data validation software or PIM systems with built-in quality management features) available that can help you ensure your product data management is at best practice - ASK THE PRODUCT DATA EXPERTS.
To develop a culture of data responsibility, you must be prepared to undertake some governance activities (see our tips for Best practice in product data governance article) including well-defined processes and utilising robust tools. And what you will achieve… is enhanced product data, and improved overall business performance.
