Measure the quality, usability, and contribution of product data to business results.
Product data analytics doesn't just show how many product listings exist. It reveals which fields are missing, which catalogs are outdated, what features customers are searching for, and how content quality relates to sales results.
Minerva can evaluate product master data, digital assets, catalog usage, and quotation and order results together. This reveals the connections between data quality issues and business performance.
Data quality indicators
Required field completeness ratio
Invalid code, unit of measurement, and classification records.
Missing visuals, documents, translations, and technical specifications.
Conflicting product and packaging information.
Content awaiting approval or expired
Products listed in the catalog but not suitable for sale.
Duplicate or incorrectly associated product registrations
Commercial content performance
Product view, offer, and order conversion rates
Ineffective searches and missing product features
Catalog, customer and channel-based product usage.
Timeframe for new products to launch to the market and receive initial orders.
Product relationships and cross-selling results
The relationship between content richness and sales and return rates.
Manage not just the existence of product data, but its accuracy, usability, and real contribution to sales processes.