Revolutionizing Marketing
with AI and Dataiku

Customer Segmentation

Dataiku can connect to virtually any data source (transaction, interaction, or external, whether structured or unstructured) from one centralized platform, which means a 360-degree view of customer data in real time. For example, DAZN’s small data team as well as its non-technical business users leverage Dataiku for advanced customer segmentation to identify user behaviors, particularly regarding content and devices on which customers use the product. 

Recommendation Engines

Building a simple recommendation engine can be quite straightforward; the real challenge is to actually build one that works and where the business sees real uplift and value from its output.

Dataiku supports clients in building their own customized recommendation engines from start to finish, because a recommendation engine that’s not in production offers no value. The platform’s robust operationalization and model monitoring features ensure that recommendation engines continue to provide value over time.

Marketing Attribution

Historically, marketing attribution has been a painstakingly manual process based on heuristic models that often turn out to be more difficult (and less effective) than necessary. Dataiku helps bring marketing teams into the age of AI with machine learning-powered marketing attribution models. For example, Trainline — an international digital rail and coach technology platform headquartered in the United Kingdom — have become 3x more efficient in using Dataiku to create their aggregated, centralized marketing acquisition dashboards.

Churn Prediction (& Prevention)

Most businesses already have some rudimentary customer churn prevention in place, but some customers are going to leave no matter what you do. Develop churn prediction models that can identify potential churners with 80%+ accuracy using Dataiku, plus turn around and use the platform to develop uplift models, making those predictions actionable and deciding which customers should be treated with — and would best react to — marketing materials.