Incorporating Variable Rate Pricing into an Hourly Rate for a Web Design Company
Poster Number
27
College
College of Arts and Sciences
Department
Mathematics
Faculty Mentor
Dr. Zachary Abernathy
Abstract
One of the biggest questions in web design is how to charge clients. Some companies charge an overall price per project whereas other companies charge an hourly rate. Revenflo is a web design company based in Rock Hill, SC that charges a flat hourly rate for each project. Since the cost of web design is highly variable due to the many different tasks done for each client, Revenflo would like to introduce a pricing schematic where each task is billed a different rate based on its value to the project. In this project, we analyze past data from Revenflo and their competitors’ prices to determine an acceptable range of rates to charge for each category of tasks in web design. Using the data mining technique of k-nearest neighbors, we are then able to determine the best price to charge a new client based on the rates other similar clients (categorized by size and expected budget) have been willing to pay. Our proposed technique can help Revenflo determine appropriate variable hourly rates to charge each client for specific tasks.
Course Assignment
Mathematical Modeling in Business, Industry, and Government, MATH 350, Zach Abernathy
Grant Support?
Supported by the Mathematical Association of America Preparation for Industrial Careers in Mathematical Sciences (PIC Math) Program, funded by a grant from the National Science Foundation
Start Date
22-4-2016 2:15 PM
End Date
22-4-2016 4:15 PM
Incorporating Variable Rate Pricing into an Hourly Rate for a Web Design Company
Richardson Ballroom
One of the biggest questions in web design is how to charge clients. Some companies charge an overall price per project whereas other companies charge an hourly rate. Revenflo is a web design company based in Rock Hill, SC that charges a flat hourly rate for each project. Since the cost of web design is highly variable due to the many different tasks done for each client, Revenflo would like to introduce a pricing schematic where each task is billed a different rate based on its value to the project. In this project, we analyze past data from Revenflo and their competitors’ prices to determine an acceptable range of rates to charge for each category of tasks in web design. Using the data mining technique of k-nearest neighbors, we are then able to determine the best price to charge a new client based on the rates other similar clients (categorized by size and expected budget) have been willing to pay. Our proposed technique can help Revenflo determine appropriate variable hourly rates to charge each client for specific tasks.
