Publication Type
PhD Dissertation
Version
publishedVersion
Publication Date
1-2022
Abstract
Real estate sales industry in China has long suffered the problem of inefficient matching of customers to projects. Inspired by the design of recommender systems, which have been widely used in the online retail industry, and are shown to facility customer-product matching and improve sales, we apply this system to the real estate sales industry using a novel approach. Instead of recommending products to customers, we suggest the best potential customers to salespeople with whom they will conduct sales with. Using city-wide sales data from the largest real estate sales company in China, we first develop a recommend system based on the predictive model where successful sales are explained by the combined characteristics of customers and real estate projects. We then conduct a field experiment to test the effectiveness of the system. We find that employing such system improves salespeople’s engagement with customers as well as customers’ willingness to visit, key contributors to successful sales.
Keywords
Recommender System, Sales Promotion, Field Experiment, Real Estate Marketing
Degree Awarded
Doctor of Business Admin
Discipline
Databases and Information Systems | Real Estate
Supervisor(s)
LIM, Yun Fong
Publisher
Singapore Management University
City or Country
Singapore
Citation
LIU, Lian.
The effects of recommender system on sales promotion of high-value products: Evidence from a field experiment in the real estate industry. (2022).
Available at: https://ink.library.smu.edu.sg/etd_coll/384
Copyright Owner and License
Author
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.