Case Study: Yog Herbal achieves under 1% stockouts and optimized sales with Ezappsolution

CPG Profit Maximization

Yog Herbal, a consumer packaged goods (CPG) customer, faced frequent out-of-stock SKUs and missed sales opportunities due to limited forecasting capabilities and highly stochastic, seasonal demand. Yog Herbal engaged Ezappsolution to predict SKU-level demand, perform scenario-based forecasting, and build an operating model to optimize sales across on-prem and cloud data sources.

Ezappsolution ingested data from AWS S3, consolidated it in DataBricks, sanitized and aggregated retail‑level data, then applied an ensemble of ML and time‑series models (XGBoost, ARIMA/SARIMAX, Prophet and deep learning) for demand sensing and sales forecasting. The solution delivered model libraries and automated forecasts that optimized replenishment and reduced stockouts to under 1%, materially cutting missed sales and improving retail performance.

Yog Herbal

Yog

Director