Understanding User’s Adoption Path on Dreeven Platform using AI

Dreeven platform serves a diverse range of construction companies, providing training and support during their onboarding process. Client adoption varies based on their needs and interests, with some fully engaging while others become disengaged and cancel their subscription. To address this, machine learning will be used to predict key factors influencing user adoption at different stages of interaction. Analyzing user log data will identify adoption patterns, allowing for user segmentation and tailored marketing. Predicting user churn enables proactive retention strategies, while engagement prediction focuses efforts on highly engaged users. This research will inform the redesign of onboarding processes and offer incentives to users reaching adoption milestones.

Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

Dreeven Technologies Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Université de Montréal

Program: