The FMCG business faced constraints that led to ineffective marketing strategies and revenue decline.
Consumer Packaged Goods (CPG), refers to a category of products characterized by their quick turnover and frequent consumption. These goods are everyday essentials that people purchase regularly, typically with a short shelf life. FMCG items span various categories, including food and beverages, personal care products, household items, and more.
Our approach involves leveraging multiple algorithms to predict sales. Traditionally sales forecasting was a manual process, but our time series-based AI models have transformed it. By analyzing historical data and real-time parameters, we achieve accurate predictions. The SARIMAX model combines seasonal, autoregressive, and moving average components, while the LSTM neural network excels at capturing complex temporal patterns. This automated solution not only improves accuracy but also enhances decision-making.
The Result
91%
Sales Prediction Accuracy
30%
Reduced Manual Dependency
99.9%
Manual Data Error Reduced