Problem Statement
The client is the GCC of a leading global confectionery company, responsible for pricing and commercial strategy across global retail markets. Rising inflation, increasing cost of goods sold (COGS), and fragmented pricing decisions were impacting profitability, retailer alignment, and pricing agility.
To address these challenges, Polestar Analytics implemented an AI-powered Revenue Growth Management (RGM) framework that enabled rapid pricing and Price Pack Architecture (PPA) scenario simulation, demand impact analysis, and data-driven commercial decision-making.
Key Challenges
- Inflation-driven price fluctuations impacting pricing strategies
- Rising COGS putting pressure on profitability and margins
- Fragmented pricing and PPA decision-making across teams
- Inability to simulate multiple pricing scenarios in parallel
- Limited visibility into shopper and competitor response dynamics
- Risk of retailer dissatisfaction and loss of shelf space
- Outdated methodologies slowing commercial decision cycles
- Lack of a unified framework to identify profitable “Triple Win” outcomes
Solution Implemented
- Deployed an AI-powered Revenue Growth Management (RGM) framework
- Enabled rapid simulation of pricing and Price Pack Architecture (PPA) scenarios
- Implemented demand elasticity and competitive impact modeling
- Assessed shopper and retailer response dynamics across pricing strategies
- Simulated multiple price, pack, and size combinations before go-live
- Identified optimal “Triple Win” recommendations balancing manufacturer, retailer, and shopper value
- Accelerated data-driven commercial decision-making through integrated analytics
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