bank-marketing-strategy-analysis
Final project of Categorical Data Analysis 2020 fall.
Goal
-
Forecast the success rate of the telemarketing calls, given information of target customers and the campaign records.
-
Customer profiling for a effective marketing strategy.
Data Preparation
Data explore
Discrete variables
- Personal Information:
- Marital, Y Vs Job/Education/Housing:
Continuous variables
-
Account Information
-
Economics
Combined
- Age vs job/education
Feature Engineering/Selecting
Lable Encoding:
- Transform education type into education year:
Extracted features:
- year features and monthly contact features from labelled
month
:
Delete/modify bad feature
- weekday of last contact:
- previous and poutcome are similar, so just keep one.
Missing value and ouliters handling:
We used Random Forest
, Pmm linear prediction
,
mode/Average
, and combined them.
Modelling
We used Logistics, SVM and decision tree.
Results: