Demand Forecasting to Optimize Profitability
To resolve pricing analysis, previously reliant on costly third-party vendors, a US food manufacturing client established an in-house team for enhanced accuracy and cost-effectiveness
As a food manufacturer, strategic pricing is crucial for sustaining demand, whether during promotions or at regular times. Previously, the client relied on third-party vendors for pricing analysis, which proved costly. Recognizing the need for a more cost-effective and scalable solution, the client established an in-house team capable of conducting accurate and scalable pricing analysis.
The Mu Sigma team conducted an in-depth study of factors impacting product pricing and demand, developing price elasticity models to analyze customer responses, uncovering a strong correlation between socio-economic status and price sensitivity, and identifying diverse reactions to price adjustments among consumer segments.
Our structured approach enabled the client to implement targeted trade promotions, resulting in an 8% revenue increase, improved understanding of sales-influencing factors, and enhanced demand forecast accuracy through product-category level price sensitivity analysis.
Business Impact
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8%
Increase in sales
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More Accurate
Demand Forecasting
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Lower Expenses
Of in-house Pricing Analysis
Mu Sigma is a pure-play decision sciences company that believes the big D is Decisions, not data. Our integrated ecosystem of products, services and cross-industry best practices, Mu Sigma enables better decision-making for more than 140 Fortune 500 clients. Mu Sigma's unique interdisciplinary approach and application of AI, ML, computer vision and more drive innovation in solving high-impact business problems across sales, marketing, finance, operations, and supply chain. With over 3,800 decision scientists and experience across 12 industry verticals, Mu Sigma has been consistently validated as the preferred Decision Sciences and Analytics partner.
The firm's is derived from the statistical terms "Mu" and "Sigma," which symbolize a
probability distribution's mean and standard deviation, respectively.
