2016 - TicketMaster
Goal: How can site visits be converted to ticket sales, and how can TicketMaster identify "true fans" of an artist or band?
Data consisted of three sets. One included events from the last 12 months that tracked customer travel through the website. Another provided information about advertising campaigns on Google, and the third included data on the events themselves.
2015 - Edmunds.com
Goal: Detect insights into the process of car shopping that can help make the process easier for customers.
Data consist of visitor 'pathways' through a website that helps customers configure car features and shop for cars. Five data files were linked by a customer key, and including data about the customer, about his or her visits to the webpage, and, when applicable, about the car purchased and the dealership where the car was purchased.
2014 – GridPoint
Goal: Help understand how customers can best save money and energy
Data consisted of a random sample of customers, with five-minute aggregates over a year of energy consumption that was then aggregated across important features of the commercial properties, as well as supporting climate and location data.
2013 – eHarmony.com
Goal: Help understand what qualities people look for in prospective dates
The DataFest students worked with a large sample of prospective matches. For each customer, data were provided on his or her preferences, as well as four matches, their preferences, and information about whether parties contacted one another.
2012 – Kiva.com
Goal: Help understand what motivates people to lend money to developing-nation entrepreneurs and what factors are associated with paying these loans
Several data sets were provided, including characteristics of lenders and borrowers and loan pay-back data.
2011 – Los Angeles Police Department
Goal: Make a data-based policy proposal to reduce crime
Data consisted of arrest records for every arrest in Los Angeles from 2005-2010, including time, location, and weapons involved.