Driving Trade Promotion Effectiveness with Azure AI

Situation

Our client’s Strategic Revenue Management (SRM) team relied on a legacy tool to forecast demand and plan promotions. The tool depended heavily on heuristics and manual judgment, offered no clear view of promotional ROI, and lacked statistical rigor. With the legacy tool being decommissioned, the SRM team needed a modern, scalable alternative that could support data-driven forecasting, promotion evaluation, and faster decision-making for Key Account Managers and Sales Volume Planners.

Problem

• No ROI visibility or explainability for promotional investments
• Manual, heuristic-based forecasting with limited statistical rigor
• Forecasts not aligned to real consumption, reducing decision confidence
• Fragmented data across ERP, TPM, and sell-through systems
• Limited visualization slowing trade and pricing decisions
• Ongoing reconciliation issues between SRM and Demand teams

Solution

Mu Sigma designed and deployed an AI-driven Forecasting and Promotion ROI platform on Microsoft Azure, with Azure Machine Learning as the core intelligence layer.

• Azure Data Lake served as the centralized foundation for shipment, promotion, and consumption data, creating a unified view across enterprise systems
• Azure Machine Learning trained, selected, and deployed the most appropriate time-series and regression models at SKU–account level, enabling consumption-based forecasts
• Automated baseline estimation adapted to market maturity—from limited promo history to advanced promotional mechanics
• Azure Web Apps delivered interactive dashboards for Key Account Managers and planners to assess forecasts, promotional lift, and ROI in near real time
• Azure DevOps enabled CI/CD for data pipelines and ML models, ensuring faster iteration and reliable scaling

The result was a scalable, SaaS-style planning platform that replaced intuition with statistically grounded, explainable decision-making.

Impact

• 66% improvement in forecast accuracy, enabling more reliable trade planning
• 80% reduction in manual effort for forecast creation and adjustments
• Deployed across 4 major markets with rapid adoption
• Scaled to 200+ customers and 2,000+ products
• Standardized planning workflows across Key Account Managers
• Reduced reconciliation effort with Demand teams through statistically sound baselines