Citi Bike, a public bicycle sharing system that serves parts of New York City, is the largest bike-sharing program in the United States. With the existing wealth of data pertaining to Citi Bike users in New York City, it is possible to identify, segment and categorize the customer domain based on several factors such as Age, Sex and Occupation which will help the company to identify their potential customers that can be targeted and also the weak customer domain which needs to be improved. The prime objective of this project is to identify long-run customers and potential audience that can be targeted to increase the company’s customer base and drive more revenue.
Other deliverables of this project would be to identify hot-spot locations and peak-demand hours, which can be crucial information that can help the company to better, manage their business supply, which will also essentially help more customers. Identifying the hot-spots at peak hours would help the company to understand the market demand and thereby increase the bike availability at these hot-spots during peak hours will help in driving more revenue. Our design would rely largely upon existing Citi Bike trip histories data and Citi Bike Daily Ridership and Membership Data.
Check it out above MapReduce Case study in below link:
Happy Hadooping with Patrick..
No comments:
Post a Comment