Data Analytics Models for FreshBooks’ Customers’ Engagement

An organization that can effectively understand its specific customers’ needs will be able to follow the best communication approach and accurately measure engagements. A data-driven framework based on the customer’s digital behavior, historical data, will be developed to identify specific customer segmentation and used to find optimal next best action to enhance customer experience by improved personalized and quantifiable marketing strategies. A deep understanding of user segmentation and corresponding support strategies to enhance customer engagement (based on their providing service/product) is critical for our partner organization. In this project, we
proposed to develop a framework (combined with unsupervised and supervised models) for segmenting customers based on their invoice line-item (i.e., provided product or services). Furthermore, to enhance engagement, we also propose to design an advanced Machine Learning and optimization framework for recommending the next best
action for supporting specific customers on our partner organization’s platform.

Faculty Supervisor:

Elkafi Hassini

Student:

Partner:

FreshBooks Cloud Accounting

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

McMaster University

Program: