This project requires segmentation of Active credit card holders of a credit card company to define their marketing strategy.
The sample dataset(CC GENERAL) summarizes the usage behavior of about 9000 active credit card holders during the last 6 months. The file is at a customer level with 18 behavioral variables.
The objective of this project is to develope a customer segmentation to define marketing strategy.
- Advanced data preparation: Built an ‘enriched’ customer profile by deriving “intelligent” KPIs such as: Monthly average purchase and cash advance amount Purchases by type (one-off, installments) Average amount per purchase and cash advance transaction, Limit usage (balance to credit limit ratio), Payments to minimum payments ratio etc.
- Advanced reporting: Used the derived KPIs to gain insight on the customer profiles.
- Identification of the relationships/ affinities between services.
- Factor Analysis: Applied factor analysis technique for variable reduction.
- Clustering: Applied K-means clustering algorithm to reveal the behavioural segments of credit card holders.
- Identification of cluster characterisitics of the chosen cluster solution using detailed profiling.
- Provided the strategic insights and implementation of strategies for the segments of chosen cluster solution.
The Excel file(Case study 1 - Segmentation) contains the descriptive stats of all the variables,detailed profiling sheet with all the results and insights.