This document summarizes Company Analysis of Housing.com. It discusses the challenges in the real estate renting, buying, and reselling business such as getting authentic property information and accurate pricing. It describes Housing.com's key differentiator of an in-house data science lab that collects and analyzes property listing data. The document outlines how Housing.com uses data collection optimization, property tiles to visualize data to customers, and tools to help analyze different regions and properties. It shows how Housing.com enables businesses through features like child friendly indexes, inventory/demand graphs, listing visibility tools, and an online rental agreement facility.

1. Company Analysis of Housing.com
▪ Ayan Sengupta (09)
▪ Dundi Hitesh (15)
▪ Loveleen Kaur (21)
▪ Sanjeev Kumar (41)
▪ Sujan Kumar Biswas (49)

3. Challenges in Real Estate Rent/Buy/Resale Business
?
1.Authentic and
verified property
information from
Landlord/Brokers.
3.Accurate price
predictor platform for
landlord/broker.
4.Property I am
looking for already
Bought/Sold.
2 Platform to analyse
different aspects of
property like locality,
commuting options,
children friendly etc.

5. Technological Differentiator
Key Differentiator at Housing.com is Data Science Lab.
Housing is the first online real estate platform that actually has in house data collection team for collecting data
of every listing.
Using active learning and deep learning, to turn the massive data-stores of images into structured data as input
for various predictive models.
Amazon’s Mechanical Turk as the tool in order to generate data for variety of the products.
Overpriced Property
by Broker.
Underestimated value
of property by
Reseller.
Information hiding by
brokers/resellers
Clueless Customer

6. Data Route Collection Optimisation
Optimizing ever-expanding operations to convert scheduling and routing Data Collectors from an ad hoc system to a structured
one.
Devised a mathematical solution based on the Hungarian Algorithm allows to find the minimum cost maximum matching on the
graph and attain an optimal solution to DC collection routing.

7. Concept of Tiles for visualising Data to End Customers
The entire planet is mapped to a 2D piece of paper using map projections. One such method is Mercator Projection method for
mapping. Once entire globe is mapped to 2D it can be rendered digitally.
The real challenge occurred when user wants to view all listing(density of listing are very high and in real-time) depending on the
focus area and zoom.
Housing tiling service renders inventory of properties on transparent images based on map coordinates and can be Overlaid over
google maps in real-time. The tiling service helped in scaling maps efficiently.
Fig: Digital Maps with different number of tiles at different zoom levels. Fig: Housing Tiles.

8. How Housing.com Enabling the Business?
Fig. Child Friendly Index and Price Heat
Map for Delhi
Fig. Inventory Demand Supply Graph for
Kolkata

9. Contd...
Fig: Listing Decay and
Visibility Index.
Fig: Housing Lifestyle
Rating and Housing
Estate.

10. Online Rental Agreement Facility

11. Contd...
Create and customise your Own Agreement
Housing DC capture photo and fingerprint.
Does the registration process.
Deliver the agreement at your doorsteps and have to pay only applicable stamp duty and
Registration fee.

12. THANK YOU
Questions?