Discover how MathCo helped a global manufacturer accelerate obsolete part matching using AI. Through the Cognitive Match Engine, we custom built a data extraction framework, unified fragmented data, achieved near 100% accuracy, and reduced response times from days to seconds, boosting efficiency, revenue, and customer satisfaction.
Case Study Topic: Decision Intelligence
Powering Precision with Data-Driven Assortment Optimization
Through data-driven assortment intelligence, a leading US-based apparel retailer achieved sharper localization and improved customer satisfaction. Leveraging advanced clustering and optimization, MathCo enabled tailored product mixes across 5,000+ stores, driving a ~7% sales uplift and ~$5M revenue impact for high-priority categories while ensuring every store met the unique demands of its shoppers.
Unlocking Competitive Advantage with Predictive Market Share Intelligence
Learn how a leading US grocery and general retailer strengthened its market position through a predictive Market Share Analytics solution. By integrating 18+ data sources and embedding competitive intelligence capabilities, the retailer improved reporting accuracy, accelerated decision-making, and unlocked a ~$2.7B revenue impact, turning market insights into a sustained competitive advantage.
Streamlining Stock Transfer Orders with AI-Powered Replenishment System
A leading CPG enterprise struggled with frequent last-minute stock transfer orders due to manual, spreadsheet-based processes and the absence of a data-driven safety stock strategy. MathCo implemented an AI-powered replenishment automation system using Agentic AI and ML insights, enabling faster, more accurate fulfillment and end-to-end warehouse efficiency across multiple locations. This helped to reduce stockout incidents by 30%.
End-to-End Analytics for Sales, Marketing & Brand Performance
A global CPG leader partnered with MathCo to build a Snowflake-based analytics platform, unifying sales, brand, and consumer data. The solution enabled SKU-level insights, cut reporting time from hours to minutes, and provided a 360° view of brand and market performance across regions.
Elevating Marketing ROI Through Multi-Touch Attribution
A leading global fashion retailer transformed its marketing effectiveness with MathCo’s Multi-Touch Attribution framework. By unifying online and offline data, deploying advanced algorithmic models, and enabling touchpoint simulations, the company achieved ~1.5x higher ROI and 15% lower eCPA. The solution delivered actionable insights, powered smarter budget allocation, and strengthened resilience in a cookie-less world.
Maximizing Membership ROI Through Ideal Member Analysis
Explore how MathCo partnered with a leading general retailer to identify high-value members and build a comprehensive, data-driven segmentation framework. By leveraging behavioral insights to design targeted engagement strategies, the retailer achieved a measurable uplift in conversion rates while strengthening loyalty, maximizing member value, and unlocking long-term growth potential across its membership program.
Optimizing Manufacturing Performance with Data-Driven Centerlining
Data-Driven Centerlining revolutionizes manufacturing. Discover how a global packaging manufacturer automated analysis, optimized machine setpoints, and enabled data-driven decisions, boosting yield, quality, and efficiency.
Strengthening E-Commerce Growth Through Buyer Trust Analytics
A leading e-commerce company partnered with MathCo to create a Buyer Trust Model that turned fragmented buyer data into actionable insights. By profiling customers with trust scores and streamlining dispute reviews, the solution cut fraud losses by 35% and improved seller retention by ~5%, strengthening marketplace integrity at scale.
Transforming Workforce Planning with a Custom Intelligence-Driven Solution
Discover how MathCo helped a global manufacturer streamline workforce planning with a custom-built, intelligence-driven platform that reduced manual effort, improved accuracy, and enabled smarter decision-making.