Adaptive Grid Division and Cluster Analysis of Decision Graph in Real Estate Marketing Using Data Mining

Abstract

China’s economy has been in a state of rapid development in recent years. People’s lifestyles and quality of life have also undergone earth-shaking changes. More people put forward requirements for the living environment and living environment, which promotes the rapid rise of the real estate industry. The state has promulgated several macrocontrol measures. Real estate companies analyze the needs of various customer groups, affordable housing unit prices, and family populations, and formulate real estate marketing strategies to improve real estate sales. Therefore, this paper practices data mining technology to precisely analyze and locate the target customers. The cluster analyzes the mapping of the real estate marketing bureau. The cluster further divides the adaptive network and selects the data of a real estate company in China for research. It also analyzes the relationship between the family population and the affordable housing unit price and comprehensively improves the accuracy of real estate marketing. The results show that the acceptable housing unit price for families in this area is 9800 yuan. Study its data characteristics to judge the relationship between the population of other families. The analysis and research of data mining technology in the context of real estate can formulate more accurate marketing strategies. Moreover, it can reduce the investment amount of real estate companies in marketing.