In a transitory company environment, the pattern of sales predictions is critical in making strategic decisions and allocating resources. To do the analysis on discount for a particular season, the current research develops a hybrid model combining clustering techniques with ATES which helps in predicting seasonal-based sales pattern including discount and special discount as of its parameter. After ATES prediction, clustering is then proposed to find out clusters of seasonal sale based on parameter taken for target forecasting. To verify the novel combination model, large dataset has been simulated which helps in finding sales pattern and business growth that supports effective decisions in business growth. With the help of error finding techniques, model has been evaluated for accurate sales pattern prediction on seasonal and special occasional discount. Mean square has been calculated to find out the error rate of proposed model and found less error with higher accuracy. For the validation and to show the effectiveness of proposed model, a comparison analysis has been conducted. Proposed model surpasses previously existing model for predicting seasonal sales pattern.