Pig E. Bank

To better understand the leading causes to customers leaving the bank, Pig E. Bank management has requested analysis of its customers’ demographics to understand them better. These insights will advise management on how to better retain customers..

Tools used

  • Excel

  • Powerpoint

Skills required

  • Data wrangling and subsetting

  • Consistency checks

  • Data merging

  • Deriving variables

  • Identifying PII data

  • Grouping and aggregating data

  • Vlookup

  • Understanding decision trees

  • Reporting in Excel

Initial Exploratory Analysis

Working to understand the tables, data available, and relationships between tables

Identify data issues to be addressed including:

  • PII data to be removed to protect customer identify

  • Data inconsistencies such as abbreviations and full words mixed in a column

  • NULL values present

  • Less useful ambiguous values in certain columns

Data Checks and Cleaning

Testing the data integrity and cleaning the data as needed

Data issues identified are cleaned.

No data was imputed as it would have had a significant impact on the results with so few records.

The HasCrCard, IsActiveMember, and ExistedFromBank fields were converted from boolean values to text.

(Changing the boolean values to text was done to make reporting more effective and impactful. Typically, I consider the balance between usefulness and efficiency when addressing this.)

Analysis

Provide full analysis of the data to better understand Instacart’s customers and products and address management’s questions

Customer Demographics vs Customer Retention

All available customer attributes have been assessed to understand their impact to customer retention

Decision tree to determine customer retention

  • According to the customer demographic analysis, this decision tree captures the primary challenges with customer retention

  • This can then be used to determine if a customer is expected to stay with Pig E. Bank

Customer Retention Decision Tree

Pig E. Bank Final Report and Recommendations

The decision tree to identify customers at risk of leaving the bank can be used to assess each customer per the criteria below:

  • The customer attributes that have the highest impact on increasing customer retention:

    • High Customer activity

    • Under 40 years old

    • Female

    • Bank balance over $100,000

  • Other attributes have shown less impact:

    • Credit score

    • Country

    • Tenure

    • Number of Products

    • Having a credit card

    • Salary