Case Study: Bechtle achieves real-time personalized recommendations and website optimization with Neo4j

Neo4j Drives Recommendations & Website Optimization

Bechtle AG, a leading European IT products and services provider with ecommerce operations in 14 countries and over 40,000 products, needed to improve its website and online store experience. The company had to process hundreds of thousands of user actions per day and move beyond traditional analytics to understand the structure of user journeys and deliver timely, relevant recommendations.

To solve this, Bechtle implemented the Neo4j graph database to model anonymized interaction data and power both reporting and the Ginni real-time recommendation system. By capturing a rich graph of interactions (100M nodes, 400M relationships, 40K+ products) and applying graph algorithms, Bechtle now delivers targeted product and content recommendations, optimizes search and navigation, and gains deeper context for AI/ML-driven insights into user journeys.

Bechtle

Zoltan Kovacs

Project Manager