Data quality and product matching are the foundation. If the platform matches the wrong SKU, every dashboard and repricing signal becomes risky. Ask each vendor how products are matched across retailers, whether matching uses EAN, UPC, MPN, ASIN, title similarity, image data, or manual validation, and how exceptions are handled.
Update frequency should match category volatility. Real-time monitoring matters for Amazon, Walmart, electronics, beauty, and marketplace-heavy categories. Daily updates may be sufficient for B2B, industrial, or slower-moving niche retailers. Real-time updates often separate enterprise-grade workflows from lighter SMB trackers.
Scalability must be tested against the real catalog. A tool that performs well on 100 SKUs may struggle at 50,000 SKUs when product matching, variants, stock status, promotions, and multiple geographies enter the workflow. Ask for a pilot using real products, not sample data.
Integrations and workflow fit decide adoption. API access, CSV exports, ERP connectors, PIM workflows, and BI integrations matter because price intelligence loses value when it stays trapped in a dashboard. If pricing, merchandising, and category teams cannot act on the data, the software becomes reporting rather than intelligence.