Final colloquium Dimphy Jansen

Data-Driven Control Approaches for Enhancing Through-Partner Social Engagement in IT Channel Marketing

Supervisor: Dr. Peyman Mohajerin Esfahani

Abstract:
The rise of social media has significantly influenced the world of digital marketing, especially within the IT Channel Industry. Channext, as a key player in automating channel marketing, faces the challenge of achieving optimal through-partner social engagement. This includes maximizing shares, impressions, clicks, likes, and comments on social media posts. However, the current approach is hindered by content overload, leading to scheduling conflicts and reduced engagement.

To handle this issue, this project introduces an advanced model for the vendor-partner network. This model, driven by carefully selected data and machine learning techniques, aims to enhance the framework for through-partner social engagement. By empowering IT partners to actively participate in vendor-led social media campaigns while avoiding overpublishing, we seek to optimize engagement strategies.

Furthermore, the integration a learning system transforms this project into a learning system capable of autonomously adapting to the evolving dynamics of the vendor-partner network. This research will redefine the architecture of through-partner social engagement, pioneering a new standard for intelligent and adaptive strategies in the IT Channel Industry. Moving beyond traditional marketing automation challenges, the project envisions a finely tuned and responsive system, aiming for sustained impact in the ever-evolving digital landscape.