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