K Means Clustering & RFM Analysis SECRET to Boost Customer Segmentation Insights in Power BI

Описание: Learn how to perform Customer Segmentation in Power BI using K-Means Clustering and RFM Analysis (Recency, Frequency, Monetary) in a simple, practical, end-to-end project.

In this full Power BI dashboard project, I’ll show you how to segment customers using machine learning (K-Means) and business logic (RFM) to identify high-value customers, loyal customers, churn risks, and inactive customers.

PBIX + Data Files: https://drive.google.com/drive/folder...

This tutorial walks you through data cleaning in Power Query, Python implementation inside Power BI, and building a complete customer segmentation dashboard from scratch.
If you’ve ever been confused about how K-Means clustering works or how to apply RFM analysis in a real Power BI project, this video will make it clear and practical.

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Timestamps
00:00 – Intro
01:00 – Why Customer Segmentation Matters?
01:35 – Techniques
03:10 – Data Cleaning in Power Query
05:20 – K-Means & RFM Using Python
15:40 – RFM scoring and customer segments
12:55 – Building the Power BI dashboard
16:40 – Final insights and key takeaways

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