Supermarket Customer Insights Dashboard

I have already cleaned a public supermarket-sales dataset from Kaggle in Excel + Power Query, modelled it in Power BI, and built a first-pass dashboard. Now I want to push the analysis further so that it truly sharpens our understanding of who the shoppers are, how they buy, and how often they return.

What I need next is a deeper layer of customer-focused analytics built on the existing model—specifically customer segmentation, purchasing-behaviour analysis, and purchase-frequency analysis. You are free to extend or restructure the current Power BI report, add DAX measures, or supplement it with Python/R if that speeds up exploratory work, as long as the final story lives inside an intuitive Power BI dashboard.

Deliverables
• Updated .pbix file with clear tabs or bookmarks for:
 – Customer segments (cluster definition, size, revenue share)
 – Behaviour patterns (basket mix, time-of-day or day-of-week preferences)
 – RFM or similar repeat-purchase view
• A short walkthrough (recorded or live) that shows how you approached the analysis and how I can tweak filters or add new data later.

I will share the current dataset and .pbix once we kick off. Looking forward to seeing how you can turn raw sales rows into sharper customer insights.