Case Study: Dentsu Aegis Network achieves 4x faster, more accurate customer segmentation with Dataiku

Improving the Data Department’s Agility and Speed Through Reproducible Workflows

Dentsu Aegis Network, a multinational media and digital marketing company, faced a bottleneck: its data team could not quickly deliver repeatable customer-segmentation recommendations to the sales force. Although they had a data lake, analysts had to write new Python/Spark/SQL code for each project and could not easily reproduce past work, slowing the sales cycle. To solve this, they selected Dataiku, adopting Dataiku Data Science Studio (DSS) as an all-in-one platform.

Using Dataiku, Dentsu Aegis Network industrialized reproducible workflows and prototyping—reusing models, running pipelines on Scala/Spark, and applying predictive machine learning to uncover weak signals for more granular audiences. The result: segmentation recommendations are delivered four times faster, enabling better, more targeted campaigns and allowing the sales team to close more business while the data team focuses on strategic modeling rather than repetitive data prep.

Dentsu Aegis Network