A personalization engine connected to a customer data platform (CDP) to automatically create data-driven offers.
In a saturated market, mass promotion loses its effectiveness. The challenge was to transform our promotion engine from generic offers to real-time hyper-personalization for millions of users. The objective: increase offer relevance to maximize engagement and purchase frequency.
Internal teams (direct), general consumers (indirect)
Promo Engine Design: led a team of Data Scientists to develop a recommendation engine based on Deep Learning, analyzing historical and contextual purchasing behaviors.
Product Discovery & Data-Driven Culture: established a continuous experimentation loop, utilizing A/B testing to validate algorithm performance before national deployment.
Cross-functional Alignment: coordinated between Data, Tech, and Marketing teams to ensure algorithms served business objectives, balancing margin versus volume.
+50% Customer Engagement: massive increase in the conversion rate of personalized coupons.
+25% Purchase Frequency: direct improvement in the Lifetime Value (LTV) of mobile app users.
ROI Optimization: reduced "unnecessary generosity" by targeting only those users who required an incentive to complete a purchase.
Structure: 3 outsourced functional teams
Team size: 19 dedicated experts
Managed expertise:
Data & Science: data scientists, Big Data analystes
Engineering: back-end developers, mobile developers (iOS/Android)
CRM & Engagement: CRM and Marketing Automation experts
Mobile app, infrastructure service
Native mobile application
Microservice architecture
Customer data platform
Third-party personalization engine
Python, Kotlin, Swift
Hadoop
REST APIs