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Success Stories
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- Forecasting
- Planning
- Recommendation Systems
- Revenue Growth Management
Driving Growth for a Major FMCG Brand in India
AI-powered analytics platform optimized retail operations, inventory management, and promotional strategies, boosting recall, precision, and sales performance across India’s diverse…
80% recall, 50% precision, 85% coverage, 50% precision, 10% lines increase
Improvement
Key Results:
- Boost incremental sales by increasing the number of product lines per store.
- Ensure consistent availability of high-performing SKUs to strengthen loyalty.
- Optimize incentive schemes and payouts to reduce promotional wastage.
- Segment stores effectively across diverse Indian markets (urban vs rural, kirana vs supermarkets).
- Aggregate store-level forecasts into regional/state-level targets aligned with growth objectives.
Store Recommendation and Incentive for Large Indian Beer Brand
AI-powered store recommendation and incentive optimization to improve market share, trade promotion effectiveness, and inventory planning for a leading Indian…
8% market share gain in pilot stores
Improvement
Key Results:
- Increasing market share in pilot stores.
- Maximizing trade promotion ROI through better targeting.
- Ensuring right product availability at right time.
- Aligning sales incentives with business objectives.
Forecasting Accuracy and Impact of Pricing and Ad Spends for Popular Skincare Brand
Teresa Forecasting Engine combining e-commerce scrape (Amazon), ad-spend, competitor prices, and category rankings to stabilize forecasts and cut OOS.
25% improvement in e-commerce forecast accuracy
Improvement
Key Results:
- Highly volatile and unpredictable e-commerce sales.
- Sales heavily dependent on ad spend and competitor pricing.
- Category rankings strongly impacting visibility and sales.
- Limited integration of external data for effective forecasting.
Forecasting Improvement for Fortune 500 Consumer Appliances Company
City×Product-level forecasting and dynamic distributor norms to cut unsold inventory and rationalize product–market variants.
30% average forecasting accuracy improvement
Improvement
Key Results:
- Bad forecast accuracy at specific product levels and markets.
- Forecasting for new launches and complementary brands.
- High logistics costs for heavy products due to poor planning.
- Value loss for products not sold before next version.
- Lack of integration of color/feature variants affected by weather patterns.
40% Forecasting Accuracy for US Car Wash Company using Weather-based Seasonal Patterns
Feature Engineering Engine incorporating 14 weather datasets to boost 90-day demand forecast accuracy and unlock working capital.
40% improvement in 90-day forecasting accuracy
Improvement
Key Results:
- No integration with critical weather datasets.
- Demand swings from dynamic weather conditions.
- Inefficient inventory/planning due to inaccurate predictions.
- Working capital tied up in excess or under-utilized resources.
Tea Price Forecasting and Procurement Insights
Ensemble machine learning–based tea price forecasting with external weather signals to improve procurement timing and pricing strategy.
≥90% price forecast accuracy
Improvement
Key Results:
- Price Volatility due to climatic conditions and supply–demand changes.
- Procurement Timing: identifying optimal bulk-buy windows.
- Pricing Strategy: aligning with market conditions to protect competitiveness and profitability.
- Demand Impact: understanding brand-level demand shifts from tea price changes.
Trade Promotion Scheme Design for Large Adhesive Brand
Designed a data-driven trade promotion scheme for a large adhesive brand, optimizing incentive slabs and improving budget efficiency across 500,000+…
3% sales uplift
Improvement
Key Results:
- Promotion Effectiveness: Difficulty in understanding uplift elasticity patterns across different promo slabs, retailers, and schemes.
- Saturation Levels: Identifying points of diminishing returns to avoid overspending on promotions.
- Budget Constraints: Maintaining budgets while ensuring meaningful sales growth across diverse store types and channels.
- Scheme Optimization: Lack of data-driven insights to design slabs and targets aligned with retailer performance and market dynamics.
Price Inflexion Point Study for Large FMCG Brand
A non-linear Marketing Mix Modelling (MMM) engine was used to identify optimal price adjustments, minimize market share erosion, and enhance…
5% price increase implemented
Improvement
Key Results:
- Determining optimal price adjustments while minimizing market share loss.
- Benchmarking against competitors to maintain relative positioning.
- Protecting volume and revenue amidst rising input costs.
- Safeguarding brand market share during inflationary pressures.
Store Recommendation System for Lubricant Brand
AI-powered analytics platform integrating diverse data sources and advanced models to drive store-level inventory recommendations, upselling, cross-selling, and incentive optimization.
50,000 outlets optimized
Improvement
Key Results:
- Boosting incremental sales and market share across diverse store formats.
- Ensuring lubricant availability at the right time and location.
- Aligning trade incentives with sales performance goals.
- Factoring seasonal, regional, and behavioural trends into demand forecasting.
Lever 1 to 5 – Large Dairy and Tuna Brands in SEAA
Lever analysis for large dairy and tuna brands in Southeast Asia.
$10M unlocked in revenue growth.
Improvement
Key Results:
- Diverse market conditions.
- Multiple product categories.
Impact of Pricing and Same Page RPI for Popular Skincare Brand
Evaluating pricing strategies and RPI impact for a popular skincare brand.
Increased revenue and market share
Improvement
Key Results:
- Complex pricing environment.
- Rapidly changing market trends.
B2B Demand Forecasting, Sales Alerts and Profitability Management System
AI-powered analytics platform leveraging machine learning to optimize inventory, forecast revenue, identify sales gaps, and improve margins through SKU-level forecasting…
100% improvement in forecasting accuracy
Improvement
Key Results:
- Optimizing inventory levels and unlocking working capital.
- Providing actionable insights to sales teams for timely order tracking and gap closure.
- Forecasting revenue for upcoming quarters.
- Tracking drop in high-margin sales and alerting sales teams by optimizing bidding strategies and proactive interventions.
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