Optimized prices in real time with AI

Automated dynamic pricing that adjusts prices based on demand, competition, elasticity and business objectives.

Overview

The Dynamic Pricing accelerator uses machine learning models to calculate the optimal price for each product and moment, considering demand elasticity, competitor prices, costs and margin targets.

Services

Competitor monitoring

Automated collection and analysis of competitor prices in real time for intelligent competitive positioning.

Price elasticity

Models that quantify the impact of price changes on demand by product, channel, and customer segment.

Pricing rules

Configurable rules engine that applies pricing strategies while respecting minimum margins, channel parity, and commercial policies.

Promotional pricing

Discount and promotion optimization with scenario simulation and volume and margin impact forecasting.

Revenue Management

Revenue optimization for limited-capacity services — hospitality, aviation, events — with yield management.

Pricing dashboard

Real-time dashboards with visibility into prices, margins, competitiveness, and pricing strategy performance.

Where we operate

Where we operate with Dynamic Pricing with AI

E-commerce

Real-time price adjustment based on competition, inventory, and demand to maximize conversion and margin.

Physical retail

Pricing strategies by region and store cluster with local competitiveness monitoring.

Hospitality & Travel

Revenue management with dynamic yield pricing based on occupancy, seasonality, and demand.

Marketplace

Price recommendations for sellers, buy box management, and cross-channel price parity.

B2B Distribution

Customer and volume-segmented pricing with automated discount rules and margin protection.

Telecommunications

Dynamic pricing of plans and services with personalized bundles and ARPU optimization.

How we work

Current Pricing Analysis

Diagnosis of current pricing practices, data sources, and optimization opportunities.

Elasticity Modeling

Building price-elasticity models by product and segment with historical data.

Engine Configuration

Implementing the pricing engine with business rules, guardrails, and integrations.

Testing & Calibration

Testing in a controlled environment with A/B testing and optimization parameter calibration.

Operation & Optimization

Continuous operation with KPI monitoring, strategy adjustments, and new data incorporation.