Pricing, Revenue and Promotion Optimization
Advanced pricing and promotional analytics designed
to optimize revenue, margin, and commercial decision-making across complex product portfolios.
The Business Problem
In many CPG and retail organizations, pricing and promotion decisions are driven by fragmented reporting, historical heuristics, or retailer pressure rather than rigorous analytics. This often leads to margin erosion, inefficient trade spend, and suboptimal promotional ROI.
Commercial teams needed a structured, data-driven framework to quantify price elasticity, measure true incremental lift from promotions, and optimize gross-to-net performance across SKUs, channels, and regions.
The objective was to improve profitability while maintaining competitive positioning and volume growth.
Our Approach
AIDA Insights developed a data-driven revenue growth framework powered by advanced analytics and machine learning.
Key components included:
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SKU-level price elasticity and cross-elasticity modeling
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Promotional uplift modeling using time-series and causal methods
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Gross-to-net optimization across price, discounts, and trade spend
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Scenario simulation tools for pricing and promotion planning
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Executive dashboards integrating POS, shipment, and market data
The solution combined statistical rigor with practical usability for commercial teams.
Scale and
Complexity
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Thousands of SKUs across multiple brands and regions
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Multi-channel distribution including retail and e-commerce
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Integration of POS, shipment, promotional, and external data
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High financial sensitivity tied to every pricing decision
Small pricing shifts had material P&L impact, requiring precision and stability.
Impact Delivered
3%
Revenue improvement across products
$90M+
Annualized financial benefit
10 - 15%
Improvement in promotional ROI
Why This
Was Hard
Pricing sits at the intersection of analytics, sales, finance, and retailer negotiation.
Models had to be statistically sound yet simple enough to gain commercial trust and adoption.
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Balancing elasticity accuracy, competitive dynamics, and business usability required both technical depth and organizational alignment.