Leveraging Big Data Technologies in Marketing Automation

Abstract

Selligent Marketing Cloud offers end-to-end marketing solutions for businesses. The platform captures tons of user-interaction data on a daily basis and aims to expose the data to provide insightful reporting and analysis. While Selligent has been able to successfully provide such reporting functionalities, the company is longing for a future proof solution that provides increased scalability. Moreover, the reporting functionalities are limited in the sense that they focus on a single reporting dimension. In reality, however, the interaction data can be used to deliver insights in multiple dimensions.

This work describes how recent advancements in the field of large-scale, distributed processing are leveraged to create a scalable end-to-end reporting application. This application delivers near real-time results and allows for multiple dimensions of the interaction data to be addressed. The activities carried out within the framework of this thesis already contribute directly to production innovations at Selligent.