Customer Analytics Model

For a Large Bank


  • 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.
  • The client wanted to identify the potential customers from their existing customer base, to whom they can sell targeted third-party products.
  • The client also wanted to know when and how to target these prospects.


  • G-Square analysed the demographics, buying pattern & banking behaviour of customers and identified most important factors which affects the propensity of buying the third-party products.
  • Using these factors, G-Square developed a robust Propensity Model using ‘R’ tool.
  • G-Square also analysed the time series data to identify the time period for targeting the set of prospective customers.
  • Customers are prioritized or de-prioritized based on the Data Science models at various sales process stages.


  • A higher conversion rate was observed from the past, which led to a marked increase in revenue and at the same time efficiency.
  • A few thousand customers were identified with the help of propensity model, who have very high propensity to buy targeted products
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