Instantly identify missing product data before publishing
Preparing product information for GS1, ETIM or retailer-specific requirements often starts with one important question: What information is still missing?
Finding the answer manually can take days. Teams compare spreadsheets, product specifications and documentation against complex data models, only to discover missing attributes late in the publication process.
Qmica automates this process through an intelligent Product Data Gap Analysis. After importing your existing product data, Qmica immediately analyses every product against the applicable data model and identifies missing attributes, incomplete information and retailer-specific requirements.
Instead of manually searching for gaps, your team receives a clear overview of what is missing, which products are affected and which actions should be prioritised. This allows you to improve Product Data Quality, reduce delays and accelerate the path towards successful publication.
Key Capabilities
Identify missing product data instantly
Upload your existing product information and receive an immediate overview of missing mandatory and optional attributes.
Qmica compares your available data against the selected product data model and highlights exactly which information is still required.
Examples include:
- Missing dimensions
- Missing packaging information
- Missing logistics data
- Missing marketing content
- Missing classifications
No manual comparisons. No guesswork.
This dramatically reduces manual mapping while ensuring consistent product information across every publication channel.
Analyse GS1 and retailer requirements
Every publication channel has different expectations.
Qmica analyses your product information against the latest GS1 Requirements, ETIM standards and retailer-specific product data models.
Instead of working with generic checklists, users immediately see which requirements apply to their specific products and target channels.
This enables organisations to prepare product information correctly before validation and publication.
Improve product data quality
High-quality product data starts with complete product data.
Gap Analysis not only identifies missing attributes but also highlights inconsistencies, conflicting values and incomplete information that may reduce overall Product Data Quality.
By resolving these issues early, organisations reduce validation errors, minimise publication delays and improve the customer experience.
Prioritise the work that matters most
Not every product requires the same level of attention.
Qmica helps teams focus on the products with the highest business impact by providing clear insights into:
- Completion percentages
- Missing mandatory attributes
- Retailer-specific requirements
- Product readiness
- Publication status
This allows organisations to prioritise their efforts and significantly reduce the time needed to prepare large product assortments.
Why this matters
Complete product data leads to faster publication
Incomplete product information is one of the main reasons for delays, rejected publications and unnecessary manual work.
By performing a Product Data Gap Analysis before validation, organisations gain full visibility into missing information and retailer-specific requirements at an early stage.
This enables teams to improve Product Data Completeness, increase data quality and publish products faster with greater confidence.
Benefits:
Instantly identify missing product data
Analyse GS1 and retailer requirements
Improve product data quality
Increase product data completeness
Prioritise missing information
Reduce manual analysis
Accelerate product onboarding
Prepare products for successful publication
FAQ's
A Product Data Gap Analysis compares your existing product information with GS1, ETIM or retailer-specific requirements and identifies which mandatory or recommended attributes are still missing.
Qmica supports GS1, ETIM and retailer-specific product data models. Additional customer-specific data models can also be supported.
Immediately after importing your product data and mapped your source data to the standard, Qmica analyses every product and provides a clear overview of missing information and data quality issues.
Yes. By identifying missing attributes and inconsistencies before validation, organisations can significantly improve overall Product Data Quality and reduce publication errors.
Yes. Qmica analyses product information regardless of whether it originates from ERP systems, PIM platforms, Excel files or other connected data sources.
Gap Analysis focuses on completeness and readiness, while validation checks whether the available data complies with business rules. Performing Gap Analysis first reduces the number of validation errors and speeds up the entire publication process.
Ready to discover what's missing?
See how Qmica identifies missing product data and helps you prepare products for successful publication.