Case Study: a Fortune 500 bank improves ROMI by 33% with Sigmoid's customer lifetime value prediction solution

Fortune 500 Bank improves ROMI by 33% with Sigmoid

The customer, a Fortune 500 bank, wanted to better understand each customer's potential revenue contribution and increase their return on marketing investment (ROMI). Their existing solution for forecasting customer lifetime value was inconsistent, not fully automated, and had a high rate of error. They engaged Sigmoid to implement a customer lifetime value prediction solution to address these challenges.

Sigmoid aggregated and cleansed six years of customer transaction data. They built machine learning models for revenue forecasting and customer churn to predict the probability of attrition and calculate lifetime value. This solution delivered a 33% improvement in ROMI and led to a 50% increase in operational efficiency for the bank.