Proof
/ ConstructionDynamic Pricing Model for an Industrial Lighting Supplier
Business situation
A privately owned construction wholesaler with a 17% quote-to-sale conversion rate and unreliable manual pricing for wholesale products.
The challenge
Manual, inconsistent pricing processes with no predictive capability were producing low conversion rates, margin leakage, and long quoting turnarounds (average one week).
Why it matters
Quantum Rise designed and built a dynamic pricing prediction system that matches parts across quotes, focuses manual effort on outliers, and provides real-time pricing intelligence.
What Quantum Rise delivered
The QR/OS™ approach in practice
- • Dynamic pricing prediction system (part matching, recency weighting, quantity tiers) • Reduced quote turnaround from ~1 week to <1 hour • Real-time quote and PO pricing intelligence • Manual review focused on outlier products only • Model tuning capability for users
Measurable outcome
Quoted Price Accuracy: 84.4%. Validated match rate: 90.0%. Profit margin increase: 3.2%. Quote turnaround improvement: 97.5%.
Increased sales conversion. Improved pricing accuracy and profit. Real-time insights for sales teams.
What became repeatable
A dynamic pricing prediction framework for wholesale distribution: part matching + recency weighting + real-time PO integration. Reusable across any high-SKU-count industrial supplier.