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Victkhur/Customer-Segmentation-Using-RFM-Analysis-Clustering

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This project applies RFM (Recency, Frequency, Monetary) analysis and clustering techniques to segment customers based on their purchasing behavior. It leverages K-Means, Hierarchical Clustering, and DBSCAN to identify distinct customer groups and provide actionable insights for marketing strategies.

active 2025-02-13 → 2025-02-18 (UTC)

Complete coverage27,841 / 27,841 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-18 (UTC)
Events
10
Pushes
7
Pull requests
0
Issues
0
Stars
0
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 6 days from 2025-02-13 to 2025-02-18. Pushes: 7 total, peak 5 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
Victkhur7700

Recent activity

Latest issues, pull requests and releases

No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.