A European bank was concerned about its increased customer loss in recent years, which already posed a significant threat to the bottom line. After Altair was brought in to help, we discovered that the model of predicting customer churn was particularly poor.
The objective of this project is to renovate the valuation model to better predict customer churn and based on the analysis of historical data, design a proper recuperation plan to bring back the revenue lost.
Altair’s new valuation model draw pattern from historical behavior of churn clients, factoring in linear and logistic regression analysis, probability modeling and macroeconomic correction, we managed to calculate for each churn client the probability of recuperation, time required to recuperate, and the percentage of business that could be potentially recuperated.
We proposed a year-long, three-phase partnership to the bank:
The result of analysis of the model will be presented in the form of a quality score, indicating how likely the clients can be brought back. Taking the score as the starting point, customized strategies of recuperation were designed with clear action plan, prioritizing the clients with highest scores.
A year after the model was implemented, recuperation rate of the lost clients increased by 15%, as we predicted at the beginning of the partnership. The change resulted in improved profits and effectiveness of the entire customer acquisition process.
September 01, 2017
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