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C5i > 实例探究 > Customer Segmentation for a Leading Money Exchange Company
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Customer Segmentation for a Leading Money Exchange Company

技术
  • 分析与建模 - 预测分析
适用行业
  • 金融与保险
适用功能
  • 销售与市场营销
服务
  • 数据科学服务
挑战
The company wanted to segment its customers according to their transaction patterns and other behavioral traits in order to identify the profitable customers and target relevant ones for the loyalty program. They also wanted to identify the customers performing adversely as compared to the cluster average and timely target them for reactivation. The goal was to perform targeted campaigns based on the behavioral pattern of the customers for revenue maximization.
关于客户
The customer is a leading money exchange company operating globally. They are one of the world's top companies in the financial services industry. The company wanted to understand their customers better for targeted promotions and reactivation campaigns. They aimed to identify profitable customers and target relevant ones for their loyalty program. Additionally, they wanted to identify customers performing adversely compared to the cluster average and target them for reactivation timely. The ultimate goal was to perform targeted campaigns based on the behavioral pattern of the customers for revenue maximization.
解决方案
The solution involved perceiving customer behavior through the analysis of their transactional trends. RFM (Recency, frequency, monetary) variables were used to perform K-means clustering to congregate similar characteristics and segregate dissimilar trends. Two models were built, one at an overall business level and the other at corridor level to have a better understanding of customers in different countries. Profiling of the customers in different clusters was done based on their transaction pattern (salary, festival, campaign period etc.).
运营影响
  • The model led to grouping of customers into five different clusters for customers who were doing multiple transactions.
  • New customers or customers who did just one transaction were grouped basis whether they made a transaction during salary week, festive season or promotional campaigns.
  • The segmentation helped the client to understand their customers better.

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