Grocery Products Sales Forecast
Singulariti combines enterprise class intelligence with industry specific customization to create applications that are ready to move into production and deliver value immediately.
Lack of product sales forecasting is a crucial problem which leads to piling up of unnecessary products resulting in overstock. It also results in harmful understock situation further causing revenue loss. The problem becomes more complex as retailers add new locations with new products, ever transitioning seasonal tastes when the sales are at its peak.
By knowing the demand forecast, supply can be managed more effectively to drive business. Past sales data of individual departments have been useful to forecast future sales. ML techniques are immensely beneficial to visualize seasonal decomposition to understand the seasonal trend and implement noise components of the sales. Applying ML algorithms on time series data checks for stationarity and adds constant fluctuation in order to make forecasts into the near future.