Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators

Abstract

The value of data is gaining importance in recent years both in Turkey and globally through increase data production. As data began to gain importance, data mining began to change and evolve. With help of data mining, companies started to determine their customer management strategies based on intelligent data analysis. Literature reviews in this area show that many data analysis models studied in the field of customer management. When a more detailed literature review is made, it is observed that the number of sources where demand estimation and location analysis applied together with the machine learning algorithms is very low in all sectors and almost none in the shopping mall. Within the scope of this study, a new model has been developed by combining location analysis and demand forecasting models that will estimate the number of customers for shopping malls in order to overcome this deficiency in the literature. This model was strengthened with estimation algorithms and tested to generalize this model to all shopping malls. In this study conducted through a large-scale technology and communications services provider company, it was found that environmental factors had a significant effect on the number of customers going to shopping centers.