The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. In order to support organizations in planning, data mining techniques are launched due to difficult data evaluation because of large amount of data and developments of information technologies. Data mining is an important management tool, which supports original decisions based on data and increases profitability, innovation and efficiency in resource utilization by producing information from data. Today, companies gains competitive advantage from collecting past data and using for future forecastings. Future estimates are usually based on past data and information. In this paper, the research subject is selected as the data of a Turkish consumer electronics store company whose name is hidden. Two year sales amount data of a consumer electronics was used and grouped as four quarters in a year. Next years first quarter sales are forecasted by using regression equations and naive bayes classifier methods and comparised by real sales amounts. Sales forecasts results are near to the real amounts and seasonal factors are really important to some product ranges. In this context, various campaigns and marketing strategies have been proposed for the sales of company products by evaluating the forecast results.