In March 2020, Manav Kamboj, CTO of PropertyGuru, an online property platform, wondered what it would take for his firm to become a one-stop solution-shop for property seekers in the home buying process. His company had just launched a new application – PropertyGuru Finance which could enable seekers to search for a home loan entirely online. The solution had taken Kamboj and his team one step closer to achieving the organisation’s vision – enabling completely online property transactions by 2025.
PropertyGuru had implemented several AI-based solutions to transform its platform from a property-search to a property-trust platform. The goal was to become the customer’s trusted friend, philosopher and guide in the home buying process. The transformation had seen the implementation of several useful analytics tools and AI applications that had helped property seekers, sellers and agents make informed decisions in buying and selling properties. It had also propelled the company to become Asia’s leading online property platform providing users a choice of over 2.7 million homes and the preferred destination of more than 24 million property seekers per month.
To attain its vision of enabling fully digital property transactions, however, the company would need to think outside the box and rely on its old friend – technology, to design new solutions to enable online property transactions.
How could PropertyGuru become an end-to-end property solution platform? What emerging trends in real estate could the company explore? Would it need to bundle all its proposed applications, or could it offer the additional offerings as standalone services? Could AI open more doors for the company?
This case describes the dilemmas faced by a technology firm in the online property market. The case can be used to discuss the use of Data Analytics and AI to drive growth strategy. Students will learn about how companies incorporate data-driven decision making for growth and the evolution of Data Analytics life cycle from basic reporting to advanced AI. Students will also learn about the nuances of Recommendation models and AI-driven use cases for a property platform.
Inspection copies and teaching notes are available for university faculty. To receive an inspection copy and teaching note, please email cmpshop [at] smu.edu.sg with your registered faculty email ID and a link to your contact information on the faculty directory at your university as verification. An inspection copy and teaching note will then be sent to your faculty email account.
Download Information
SMU Faculty/Staff can download the case & teaching note on iNet with your SMU login ID & Password via the following links:
· Teaching Note (SMU-20-0019TN)
· Supplementary Material (SMU-20-0019S)
For purchase of the case and supplementary materials via The Case Centre, please access the following links:
· Teaching Note (SMU-20-0019TN)
· Supplementary Material (SMU-20-0019S)
For purchase of the case and supplementary materials via Harvard Business Publishing, please access the following links:
SMU Faculty/Staff can download the case & teaching note on iNet with your SMU login ID & Password via the following links:
· Teaching Note (SMU-20-0019TN)
· Supplementary Material (SMU-20-0019S)
For purchase of the case and supplementary materials via The Case Centre, please access the following links:
· Teaching Note (SMU-20-0019TN)
· Supplementary Material (SMU-20-0019S)
For purchase of the case and supplementary materials via Harvard Business Publishing, please access the following links:
(Please note you are purchasing the case only.)
Looking for something?
