Optimizing Online Customer Interaction by Advanced Data Analytics (OCIDA)
The objective of the research project OCIDA is to reduce the churn of customers through optimal strategies through efficient evaluation of individual customer data from e-commerce. Methods of analytical marketing, mathematical modeling and optimization from revenue management and pricing as well as suitable forecasting methods will be applied. Due to the large amounts of data, Big Data is evaluated based on Hadoop technologies.
Based on a new attribution model, the effectiveness of the churn reduction campaigns and the return of investment (ROI) should be maximized by optimizing the budget. Based on customer segments to be formed, the churn probabilities are estimated and the effects of promising strategies are evaluated and optimized.
Aims of the project
- better estimate the churn rate of customers (churn rate),
- develop and evaluate effective strategies that prevent or significantly reduce churn,
to develop more accurate models that allow a common view of the marginal functions of demand and the effects of price and supply control.
Cooperation partners of the comercial economy
Thomas Winter (BHT), Nicola Winter (HWR), Patrick Erdelt (BHT)