GoalsConrad Electronic is a European retailer of electronic products based in Germany. With 36 retail stores nationwide, the company wants to move towards innovation and digitalization, especially by improving its website offer. To successfully represent these core values, Conrad wants to improve its customer’s digital experience. It is critical to detect when its customers are churning and to understand the causes by analyzing relevant data.
ChallengeConrad was exploring why their customers churn. Their previous approaches involved ad hoc and statistical implementations, which suffered from two main caveats: the relentless need for human input and the lack of generalization. Although Conrad was also using Google Analytics 360 data which tracks user interactions on the website, they had made hardly any use of the stored data. The challenge, thus, was fourfold:
- Clean and reformat Google Analytics 360 data.
- Extract relevant features from Google Analytics 360 data.
- Properly frame the machine learning task.
- Test the trained model – based on ensembles of decision trees – through diverse simulations.