Effects of meteorological parameters on clothing retail sales in Istanbul, Ankara and Antalya

Abstract

In this study, the effect of weather conditions on sales in the retail sector was analyzed. The relationship between the parameters of precipitation, real-feel temperature, temperature, humidity and wind speed and sales data was analyzed. It was tried to be analyzed using Pearson and Sperman's rank correlation methods and graphing methods. In the study, three provinces with different sales habits and climate conditions were selected and the differences were aimed at being understood. In this study conducted for the provinces of Istanbul, Ankara and Antalya, the relationship between temperature, real-feel temperatures, precipitation, wind speed and sales data were examined, and their effects were compared. The positive or negative results of these effects were understood. Considering the regional climate conditions of the three provinces, the changes between the years 2021 and 2022 were examined. The sales data of the stores belonging to the clothing retail brand in the provinces examined were analyzed. The two-year data used was first examined with the graphing method, and the changes between the years and the internal and external factors of the changes were tried to be understood. A data set consisting of meteorological parameters and sales data was prepared and a general evaluation was aimed at being made by correlating. It was aimed to reduce the analysis to a monthly, daily and category basis by proceeding from general to specific on an annual basis. As a result of the analysis made on an annual basis, the months, days and categories that caused sales accelerations were examined by reducing them to monthly basis. The relationship between the accelerations in sales data and the weather conditions were analyzed and negative and positive effects were revealed. The results obtained by correlating the data sets were interpreted.