Segmenting members and understanding their behavior is crucial to increase sales and revenue. Marketing campaigns need to target important member segments which have different behavioral characteristics and needs. Some credit unions and banking companies that neglect targeting important segments may find themselves falling behind their competitors, struggling to increase revenue.
Predictive Analytics enables marketers to understand the behavior patterns of their members and identify opportunities to present the right types of offers or messages that will result in increased sales or member loyalty.
The power of NEMESIS in marketing campaigns is not simply about a customer segmentation model, but about the campaign performance feedback and tracking through the NEMESIS in-build Case Management System (CMS). With NEMESIS CMS, marketers can review the feedback and results from the member service department in near real-time. All these data will be automatically saved in NEMESIS and ready to use for campaign performance review.
The result data can be fed back to the customer segmentation model, generating more accurate model results. With the machine learning technology of NEMESIS, marketers can make better targeting to offer the cross-sell products.
This case requires the use of member historical data, including demographic data and behavioral data, such as the data include member average account balance, vintage, member geographic data, member occupation, purchased credit product details, etc.