IMPROVING THE RETENTION CAMPAIGN EFFECTIVENESS USING CUSTOMER VALUE INDEX CONCEPT AND DECISION TREE ANALTICS: A CASE STUDY OF MAGENTA BANK
This study aims to improve retention campaign take up rate as well as justifying the marketing cost to maintain campaign effectiveness that leads into company profitability in Magenta bank. Because In fact, not all customers are good customers, not all customers require massive marketing investment....
Saved in:
Main Author: | |
---|---|
Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/70655 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | This study aims to improve retention campaign take up rate as well as justifying the marketing cost to maintain campaign effectiveness that leads into company profitability in Magenta bank. Because In fact, not all customers are good customers, not all customers require massive marketing investment. Retention campaign become major issue since competition of digital banking industry in Indonesia has increasing during Pandemic COVID-19. Other thinks that make the condition worsen is buying power of Indonesian is dramatically declining during pandemic COVID-19. This condition will make the retention strategy more difficult due to very tight competition. Therefore, an effective marketing effort should be implemented to increase customer loyalty as a result of high customer retention rate. To see how existing condition of Magenta Bank customer, researcher used Customer Value Index (CVI) to calculate the cost component and income component for each customer. From the result of the analysis, this method is not only measuring customer value, but also create customer segmentation. For example, premium segment is more likely use Magenta as a saving account while other segment uses for transaction. This analysis also indicates a different critical stage of customer retention between each acquisition channel that must be anticipated by Magenta. Using CVI Analysis combined with several portfolio parameter such as MOB, Acquisition channel, and Funding balance tier, the retention campaign strategy can be improved by creating different approach using segmentation based on customer behavior. Researcher used Machine learning analytic approach to create segmentation using Scikit Learn Module to produce decision tree. The predictive result of this model will ensure that the marketing effort is cost-effective by investing more marketing budget on High CVI Customers that has a potential return for Magenta Bank and invest less marketing budget on Zero or Negative CVI Customers. |
---|