Price Optimization Engine

Define Pricing Rules

• Based on product attributes (cost, quality, brand value, etc.)
• For each market segment (region, customer segment, channel, etc.)
• Considering competitor prices

Pricing Algorithms

• Rule-based pricing algorithms
• Accept product attributes and market segments as parameters
• Determine priority when multiple rules are applicable

Price Adjustments and Constraints

• Set minimum and maximum price thresholds
• Set minimum and target margin thresholds
• Options for price rounding (up, down, nearest)

Simulation and What-if Analysis

• Simulate different pricing scenarios
• Forecast impact on revenue, profit, market share, etc.
• Compare and analyze simulation results

Price Application and Updates

• Apply optimized prices to product catalogs/e-commerce platforms
• Schedule and batch process price changes
• Track price change history and audit trail

External Data Integration

• Interfaces to import competitor price data
• Interfaces to import market trend and demand forecast data
• Incorporate external data into pricing logic

Performance and Scalability

• Optimize for large product catalogs
• Parallelize price calculations and data processing
• Scalable architecture for future expansion

Evaluation and Improvement

• Compare actual sales data with predicted values
• Regularly review and refine pricing logic
• A/B testing to evaluate pricing strategies

Future Enhancements

Introduce machine learning and optimization algorithms for advanced pricing.

Combine accurate data, domain knowledge-based rules, and performance metrics for maximum profitability.