Mid_Project_Customer_Behaviour_by Generation

Mid Project regarding Customer Behaviour made for completion of Data Analysis Bootcamp in IronHack

Data Source : https://www.kaggle.com/datasets/imakash3011/customer-personality-analysis

Subject : Based on this Customer Personality Analysis Data, is there any different pattern of acceptance should customer differentiate by Generattion Type?

Customer segmentation by Generation:

1. Generation Builder : Born between 1928 - 1945
2. Generation Baby Boomers : Born between 1946 - 1964
3. Generation X : Born between 1965 - 1980
4. Generation Y / Millenial : Born between 1981 - 1996
5. Generation Z : Born between 1997 - 2012

Step of the Process

1. Data understanding
2. Data Cleaning in Python : lower alphabetic, checking NaN, simplifying column, customer gereation added, etc
3. Data Statistic in Python : Distribution check, Heatmap for correlation, (X,y) Split, Numerical & Categorical separation, scaling & encoder
4. Data Modelling in Python : Logistic Regression & Smote
5. Data Saving to CSV for reading in SQL and Tableau
6. Data Interpretation using Tableau and saving it in Tableau Public

Data Summary

Based on actual data there is 2 type of customer : the on that rejecting and the other that accepting the marketing campaign. Sample shown that there is 3 major generation to check : Baby Boomers, Generation X and generation Y / Millenial Resume for Customer that rejecting the marketing campaign:

1. There is no special pattern between those generation : income Their pattern from 41 K to 55 K per year, most of them are in relation and have children & their expense around 400 with purchase from store
2. Suggestion : As they are educated, need to find out their interest beside relation and the children & make a marketing campaign more interesting especially in store and website so they are intriguing and grab the product Resume for Customer that accepting the marketing campaign :
3. Again there is no special pattern between those generation : Higher income starting 60 K above per year, family situation still in relation but a lot that did not have children & their expense is doubling around 1 K monthly with mostly purchase from store and high website purchase
4. Suggestion : As they are more educated due to high PhD, again qualitative research are needed to find out their interest & make a marketing campaign more interesting especially in website so they are intriguing and grab the product

Thank you