Price Optimization Application for Self Storage Business

Project Description

THE SCOPE OF THIS PROJECT HAS CHANGED AFTER ROADMAPPING. PLEASE REVIEW REQUIRMENTS AND EDIT ACCORDINGLY. 

Objective:

Seeking data scientist with strong programming capabilities to build a price optimization application that will predictively change pricing on self storage units ahead of seasonal demand periods based on historic sales data. The goal is to adjust prices to maximize revenue and maintain property-level occupancy through peak and trough demand seasons. To achieve our goal the candidate will need to build a prototype application that we can enhance as we learn and as additional data inputs are available.

Requirements:

·         Automate current data processing: Establish API data feeds to read/publish data with two or more external vendor systems, process this data and store in a database for use by price application.

·         Price optimization application: Automate existing excel-based pricing model and manual processes into a custom application that can be run weekly or daily to make price changes on self storage units.

·         Reporting: The application will need to integrate with an existing or new reporting system to track and measure success of the pricing application.

The data I collected:

·         Monthly unit-level sales activity and price points from 2011 – 2015.

·         Monthly unit-level competitor prices for past year.

Technology & Vendor APIs:

·         Majority of pricing work is currently performed in excel, but the intent is to move beyond this.

·         We have a local SQL database and IBM Cognos TM1 reporting infrastructure, but neither are currently utilized in pricing or reporting processes. We are open to technology stack recommendations.  

·         Vendor APIs are available, but need to be developed on our end with the following vendors (https://slc.centershift.com/store40/SWS.asmx), (http://www.stortrack.com/index.php/solutions/datastream).