Product data quality refers to the accuracy, completeness, consistency, and relevancy of the information associated with a product. It encompasses the various attributes, specifications, descriptions, and other details that describe a product's characteristics, features, and functionality.
Critical business processes and global operations depend on the collaborative exchange of high-quality product information. Ensure that your enterprise has immediate access to the information it needs.
Accurate product data ensures that the information provided is correct and reliable. It means that the data reflects the actual attributes and properties of the product, enabling customers to make informed decisions. For example, if the dimensions or weight of a product are incorrectly listed, it can lead to customer dissatisfaction and potential returns.
Completeness refers to the presence of all necessary information about a product. It includes details such as product name, brand, model number, specifications, images, pricing, availability, and other relevant attributes. Incomplete data can confuse customers and hinder their ability to evaluate and compare products effectively.
Consistency implies that the product data is uniform and follows predefined standards across different platforms or channels. Consistent data ensures that customers receive the same information regardless of where they encounter the product, reducing confusion and enhancing trust.
Relevancy refers to the appropriateness and usefulness of the product data for customers. It means that the information provided is tailored to the target audience and aligns with their needs and expectations. Irrelevant or outdated data can lead to customer frustration and loss of credibility.
Overall, ensuring high product data quality is crucial for e-commerce businesses and retailers. It enhances customer experience, boosts trust and confidence, reduces returns and complaints, and ultimately contributes to the success of the product and the brand.
At Masterdata, we propose a data quality solution that allows you to understand, correct, and govern product and materials data and implement processes that adapt and extend to support the specific needs of your organization and drive measurable business results.
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Do you have challenges with inconsistent standards and poorly structured product and inventory data?
Do your management reports look something like this?
Imagine the impact this data is having on your supply chain
Is it possible you are ordering stock that you already have - lost in a warehouse somewhere?
Can your delivery team find the closest available stock or are they travelling to the wrong warehouse?
Trillium Software can solve your problem
Key | Material Long Name | UOM |
1 | H/BRAND FRZN PEAS 500G | EA |
2 | FROZEN PEAS (H/B) | 0.5KG |
3 | HOUSE BRAND PEAS, FROZEN | 500G |
- Facilitate procurement classification
- Create consistency across multiple suppliers
- Consolidate inventory
- Identify variances across sites (plants, warehouses, manufacturing lines, subcontractors, suppliers)
- Maintain “Item Masters” across multiple sites
- Build a complete product view
Take the guesswork out of materials classification
Apply the data - Leverage trusted, complete product views for
- Populating new applications and systems
- Global data synchronization
- Spend and inventory analysis
- Consistent reporting across all applications
- Compliance in product recall management, material maintenance, lot management and tracking
Key | Class | Type | Brand | UOM | Match key | Category |
1 | PEA | FROZEN | HOUSE | 500g | 00000001 | VEG |
2 | PEA | FROZEN | HOUSE | 500g | 00000001 | VEG |
3 | PEA | FROZEN | HOUSE | 500g | 00000001 |
VEG |
Trends in manufacturing have enabled companies to offer highly complex configured products.
This article provides a how-to guide on SKU management for digital channels.
Link to your Suppliers, Customers and Sales team!
Of course, quality product data exists within an ecosystem of suppliers, customers and employees.
Who is the biggest supplier of your core consumables?
Who is your most successful salesperson, and with what product?
Which customers are generating the most sales for product X?
Data Quality management must go beyond Product Data to create consistent, accurate client data as well.
Choose a solution that is proven to do both!
Preparing for PIM (Product Information Management)?
Read the Precisely eBook and learn five steps to get your organization ready for a PIM software or product information management initiative.
Get a free FRI template for PIM here