A Data Mining Framework for Automatic Online Customer Lead Generation
Customer lead generation is a crucial and challenging task for online real estate service providers. The business model of online real estate service differs from typical B2B or B2C e-commerce because it acts like a broker between the real estate companies and the potential home buyers. Currently, there is no suitable automatic customer lead generation system available for online real estate service providers. This thesis aims at developing a systematic solution framework of automatic customer lead generation for online real estate service providers. This framework includes data modeling, data integration from multiple online web data streams, as well as data mining and system evaluation for lead pattern discovery and lead prediction. Extensive experiments were conducted based on a case study. The results demonstrate that the proposed approach is able to empower online real estate service providers for lead data analysis and automatically generate targeting customer leads.