Case Study: E.ON achieves 70% higher sales potential for natural gas with Adastra

E.ON boosts sales potential by 70% with Adastra

E.ON, a leading energy provider in the Czech Republic, faced the challenge of optimizing its customer acquisition process to expand its gas supply services. They needed to identify customers with a high likelihood of purchasing natural gas more effectively than their manual, expert rule-based approach. To address this, they partnered with vendor Adastra to implement an advanced analytics and machine learning solution on the Databricks platform.

Adastra designed and automated a propensity-to-buy model on Databricks, which was trained on a dataset of 1.2 million records. The solution involved building an analytical datamart and advanced feature engineering to identify potential customers. This implementation resulted in a 70% improvement in identifying potential customers willing to switch to E.ON compared to the original method. The model also achieved a 3x higher targeting efficiency in the top customer decile, significantly increasing the sales potential and efficiency of E.ON's acquisition process.

E.ON