Case Study 4 : Segmentation analysis

For a large bank

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01

Client

The client is a large private sector bank in India with a significant savings and current account holders base. The Client has various products in Assets and liabilities with a mix of vintaged and new clients

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02

Problem

The bank wanted to segment its entire customer base in various homogeneous groups based on their behavioral and demographic characteristics.

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03

Solution

  • G-Square analysed the demographics, and banking behaviours of all the customers of the bank.
  • G-Square built a robust segmentation model using unsupervised machine learning algorithms which formed a few clusters of customers sharing similar banking behavior and other characteristics.

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    04

    Outcome

    G-Square’s productified solution helped client to get homogenous segments & groups from their customers sharing similar behaviour and characteristics They are now managing customers as per the group characterstics and running customised campaigns for each segment.

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