Control Forecasting Feature

Control is a leader in mobile payment analytics and alerts for SaaS, subscription, and eCommerce businesses, enabling instant intelligence anywhere via its Android, iOS, and web-based products. We collect our customers’ payment data and provide them with their key business metrics that helps them monitor their performance. In order to improve our service to customers we are moving towards providing customers with predictive analytics, that is we want to enable our users to forecast the future of their business based on the models that will learn from their historic payment data and yield forecasts for short-term future. This will help business owners to make informed business decisions and set their strategies on insights that are driven from their data. This requires studying the data and testing forecasting techniques to measure the performance of each method in predicting the future data, which is the main objective of this project.

Faculty Supervisor:

Mary-Catherine Kropinski

Student:

Seyedsaeed Mirazimi

Partner:

Control Mobile Inc

Discipline:

Mathematics

Sector:

Information and communications technologies

University:

Program:

Accelerate

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