Our client, one of the world’s largest logistics Real Estate Investment Trust wanted to understand the factors that affect real estate prices and attain an optimal pricing point for each property.
The client wanted us to identify and quantify key pricing drivers for each individual market and create a price elasticity model to estimate the likelihood of conversion at different price points. They also wanted the model to be capable of providing recommendations on target pricing to maximize revenue.
The Pricing Optimization model showed a lift of 3% while the Revenue Maximizer model results showed a lift of 4% over the baseline data
R Shiny based web tool helped the leasing team to curate competitor comparable properties and adjust price elasticity curves accordingly
The scenario planner enabled the client to find an appropriate balance between pricing and occupancy to maximize rent & revenue. The model predicted the required changes in Optimal Rental Price to improve Win Probability after factoring in the impacts of Covid-19.