Case Study: Yog Herbal cuts stockouts to under 1% and boosts CPG sales with EzappSolution

CPG Profit Maximization

Yog Herbal, a consumer packaged goods (CPG) company, faced frequent out-of-stock issues and missed sales because it lacked robust forecasting for highly stochastic SKU demand. To close those gaps and build an operating model for sales optimization, Yog Herbal engaged EzappSolution to provide demand-sensing and SKU-level forecasting services using time-series and machine learning approaches.

EzappSolution ingested on-prem and cloud data from AWS S3 into Databricks, sanitized and aggregated retail-level data, and scaled features for modeling. Their team deployed an ensemble of forecasting techniques—XGBoost, ARIMA/SARIMAX, Prophet and deep learning models—to predict demand under multiple scenarios and account for seasonality and supplier refill variance. EzappSolution’s implementation drove measurable improvements, reducing stock-outs to under 1% and enabling more accurate demand sensing and optimized sales.

Yog Herbal

Yog

Director