week05.md

Customer Segmentation

📍 GOAL 🔥 :

Define customer from raw data using python

Tools & Others

Raw data :

( RESTRICTED : MLM (Multi-Level Marketing) or Network Marketing data from 2021 to 2023 )

CODE :

🔍 1st Inspection
After cleaning the data, I take another step to define customer behavior and perform segmentation.

Criteria of selecting customer behavior :

• RFM ( Recency Frequency Monetary ) analysis or RFM segmentation.

So, I need to transform the data from simple to RFM data.

The next step is to perform segmentation using these columns as follows

Segmentation result

• Overall (Segment 01)

• Last 6 month (Segment 02)

• Last 3 month (Segment 03)

Feature Importance

Overall (Segment 01)

Cluster 0 : Total Spending , Total Network (Tier 1)
Cluster 1 : Total Spending , Total Network (Tier 2)
Cluster 2 : Total Spending , Member Duration , Total Network
Cluster 3 : Total Spending , Total Transaction , Total Network
Cluster 4 : Total Network , Member Duration , Total Spending , Ticket Size
Cluster 5 : Total Spending , Total Network (Tier 3)

Last 6 month (Segment 02)

Cluster 0 : SKU last 6m , Network last 6m
Cluster 1 : Spending last 6m online , Transaction last 6m
Cluster 2 : Spending last 6m , Member Duration
Cluster 3 : Spending last 6m , Transaction last 6m
Cluster 4 : Spending last 6m online , Spending last 6m offline , Network last 6m
Cluster 5 : Spending last 6m offline , Spending last 6m online

Last 3 month (Segment 03)

Cluster 0 : Transaction last 3m , Network last 3m
Cluster 1 : Spending last 3m , Transaction last 3m
Cluster 2 : Spending last 3m , Spending last 3m offline , Spending last 3m online
Cluster 3 : Spending last 3m offline , Spending last 3m online
Cluster 4 : Spending last 3m online , Spending last 3m offline , Network last 3m
Cluster 5 : Spending last 3m , Transaction last 3m , Spending last 3m online

Segmentation Movement

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