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CONCEPT

Stack

PythonRayPostgreSQLRedisReactKubernetes

Pricing Optimization System

Dynamic pricing engine that maximizes margin while maintaining competitiveness.

Overview

Designing a system that continuously optimizes prices based on demand signals, competitor pricing, inventory levels, and margin targets....

The Problem

A marketplace was leaving money on the table with static pricing. No visibility into price elasticity. Competitors were more agile. Margin pressure was increasing.

The Solution

Designing a system that continuously optimizes prices based on demand signals, competitor pricing, inventory levels, and margin targets.

Architecture

1
Real-time competitor price monitoring
2
Demand elasticity modeling
3
Multi-objective optimization engine
4
A/B testing framework for price experiments
5
Guardrails for brand and margin protection
6
Executive dashboard and alerting
  • Real-time competitor price monitoring
  • Demand elasticity modeling
  • Multi-objective optimization engine
  • A/B testing framework for price experiments
  • Guardrails for brand and margin protection
  • Executive dashboard and alerting

Business Impact

  • Target: 8-12% margin improvement
  • Target: Reduced time to respond to market changes
  • Target: Better inventory turnover
  • Target: Competitive positioning intelligence

Lessons Learned

  • Pricing is sensitive - start with controlled experiments
  • Stakeholder buy-in is critical
  • Guardrails prevent costly mistakes
  • Simple rules often outperform complex models initially

Want this built for your company?

Every system starts with understanding your specific problem. Let us talk about what is possible.