Problem Statement
A leading subsidiary of a global alcoholic beverage brand wanted to improve market share in pilot stores through more targeted and localized trade promotion planning.
The business needed better visibility into store-level sales, inventory, seasonality, regional demand, and promotion performance. However, these signals were scattered across disconnected systems, making it difficult to identify high-potential stores, allocate trade spend effectively, and align inventory with local demand.
Key Challenges
- Fragmented demand visibility across stores, SKUs, regions, and channels
- Inefficient trade spend allocation across schemes and incentives
- Disconnected inventory, incentive, and sales planning decisions
- Top-down target setting not fully grounded in outlet-level demand patterns
Solution Implemented
- Polestar Analytics deployed PromoPulse, an AI-powered trade promotion intelligence cockpit designed to help CPG teams move from broad promotion planning to store-level, insight-led execution.
- Connected store, SKU, scheme, inventory, seasonal, regional, customer, and channel data into one decision layer
- Enabled store-level brand and inventory recommendations for priority outlets
- Used uplift modeling to identify high-potential depot, channel, customer, store, and scheme combinations
- Provided promotion-level views across sales, baseline, uplift, ROI, margin, and performance drivers
- Enabled AI-backed scenario simulation across spend, geography, channel, duration, and discount depth
- Supported bottom-up target setting by aggregating store-level demand signals to regional goals
- Enabled PulseAI decision support for faster questions on ROI, lift, elasticity, discount impact, and margin outcomes.
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