Rent Out For Lodging Portal

Case Study

Rent Out For Lodging Portal


The customer is a leading short-term rental company. They host a booking site that provides a platform for individuals and property managers to rent unoccupied living spaces and other short-term lodging to guests. The company offers affordable short-term rentals in 5,000 locations.
Typically, a short term rental is any home, apartment, boat, castle etc. that can be rented for a short amount of time. Short-term rentals are like vacation rentals but typically the host lives there until a reservation arrives.

Executive Summary

The customer has affiliated rental homes, rooms and other properties, which was to be rented to guests without the standard pricing but using more complex mathematical systems called Dynamic Pricing Systems to adjust prices every day based on supply & demand.
With our proven expertise in hospitality segment and capability in providing scalable technology to changing dynamics, we delivered an intuitive pricing model solution to the customer.


  • Scrapper -> To scrape rental site data
    • Python 2.7.9
    • Ruffus 2.6.2
    • Scrapy 0.24.5
    • AWS S3
    • AWS Redshift
    • AWS ec2
  • Frontend & Backend
    • php 5.4.16
    • Symphony / Yii 2.0
    • Jquery
    • Javascript
    • Bootstrap
    • MySql 5.6.12
    • Google maps
    • Google charts


The system developed was methodical that tracks thousands of hotel and apartment prices, booking trends and events in the area every day. Then the internal analytical engine analyzes the data with proprietary forecasting algorithms, and publishes the price recommendations directly into multiple short-term rental sites.
This engine is also integrated into these short-term rental sites so as to update prices automatically according to supply & demand changes.


  • To complete scrapping data for each city with dynamic price update and changes, before the start of next scrapping cycle.
  • Authentication verification and bot bypassing for user login credentials on all listed sites.
  • Dynamic update of the scrapped data into the analytical engine to generate competitive pricing.

Business Impacts

  • Enabled the customer in real-time price analysis, tracking and enhancement.
  • The quantifiable data scrapped helps in creating exclusive business strategies for different regions.