Management software

planningcontrolfor airline

Overview
Cargospot neo Revenue Management is an ML-based dynamic pricing solution for airline cargo teams. Turn cargo data into faster, more profitable pricing decisions with AI-driven recommendations, real-time capacity intelligence and transparent human-in-the-loop control. Natively built on the CHAMP neo Platform.

Key capabilities

• AI-driven pricing and capacity recommendations directly within operational workflows
• Clearer demand and capacity visibility
• Faster decision-making for commercial teams
• Explainable recommendations that keep revenue managers firmly in control

Functionality & features
Cargospot neo Revenue Management combines machine learning, live operational data and market signals to support pricing and capacity decisions directly in Cargospot neo. It is designed to integrate with existing Cargospot data and CHAMP MarketAnalytics, and to be extensible via APIs to third-party cargo management systems.

What it delivers

• Updated daily: ML-based flight-level capacity forecasting (weight and volume) so sales teams work with the latest view
• ML-based demand forecasting using historical booking patterns plus real-time operational and market signals to anticipate booking trends
• ML-driven pricing recommendations that use demand forecasts, pricing rules and live market/capacity signals
• Dynamic pricing support that continually adjusts rates using live demand, capacity and market signals
• Market-rate intelligence incorporated into revenue and pricing decisions
• Native integration across the CHAMP ecosystem (supports TACT, contract, spot, market and hurdle rates with approval hierarchies)
• Human oversight with explainable AI: approve, adjust or override recommendations with transparent reasoning
• Rich input data model incorporating passenger and baggage weight, fuel and aircraft configuration for more accurate forecasts

Business benefits

• Revenue uplift potential: early evidence of 3–5% revenue gains from dynamic pricing
• Faster response: enable sales teams to quote more quickly and competitively while protecting yield
• Better forecasts: potential capacity forecast accuracy improvements (example: reducing error baseline from ~70% to ~15% MAPE; cited improvement ~55 percentage points)
• Improved competitiveness and trusted control via transparent ML-based recommendations
• Fast time-to-value due to native CHAMP neo Platform and Cargospot integration, simplifying adoption and reducing integration effort

Product position & data foundations
Built on machine learning models trained on multiple years (at least three years) of operational data, the solution accounts for seasonality, public holidays and passenger/baggage behaviour to generate more accurate capacity forecasts than static industry assumptions.

Technical specifications

• Solution type: ML-based dynamic pricing & revenue management for air cargo
• Native platform: CHAMP neo Platform; deep integration with Cargospot and CHAMP MarketAnalytics
• Forecasting cadence: daily flight-level capacity forecasts (weight and volume)
• Demand model inputs: historical bookings, real-time operational data, market signals, seasonality and booking behaviour
• Pricing models: ML-driven recommendations using demand forecasts, pricing rules, live booking and market signals
• Integration: flexible API support for third-party cargo management systems
• Controls: approval hierarchies, human-in-the-loop adjustments, explainability of recommendations
• Data model: includes passenger & baggage weight, fuel, aircraft configuration
• Typical business outcomes: 3–5% revenue uplift potential; marked improvement in capacity forecasting accuracy