Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns,presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties,Flats, Sandals and Shoes.