Situation

The client in the healthcare industry needed to better understand customer value, market potential, and regional market share for subsequent sales activities. Existing data was fragmented, hindering effective decision-making and growth strategies.

Task

The objective was to develop a data-driven strategy to integrate customer data, define value principles, and use machine learning (XGBoost) for estimating customer value and consequently segment customers based on estimated value.

Action

I trained a XGBoost Machine Learning model for estimating customer value based on historical sales data. This included:

• Integration of internal and > 10 external data sources to create a consolidated customer database (SQL).

• Definition of standardized customer value principles.

• Training and evaluation of a XGBoost model for customer value estimation.

• Identification of novel profitable customers utilizing the Machine Learning model.

• Establishing data governance best practices to ensure ongoing data quality, enabling future data-driven strategic decision making.

Result

The project resulted in accurate customer segmentation, market potential estimation, and identification of profitable new business opportunities, driving data-driven targeted marketing and expansion. The implementation of data governance ensured sustained data quality, and the quantified impact demonstrated significant business growth.