Customer retention is a critical challenge in the retail industry. This project analyzes IKEA customer behavior to identify churn patterns, understand repeat purchase dynamics, and support data-driven retention strategies that improve long-term customer value.

This project presents an interactive Power BI dashboard designed to analyze:

• Customer retention and churn trends
• Repeat purchase behavior across customer segments
• Revenue contribution by loyalty tiers
• Impact of promotions and loyalty programs on retention
• Regional and store-level retention performance

• Power BI
• DAX
• Excel / CSV
• Data Modeling
• Data Cleaning & Transformation

The analysis is based on multiple structured datasets, including:

• Customer demographics
• Transaction history
• Loyalty program data
• Store and regional information
• Churn-labeled customer records

All datasets used in this project are available in the data/ folder.

• Customer Retention Rate
• Churn Rate
• Repeat Purchase Frequency
• Customer Lifetime Value (CLV) indicators
• Revenue by customer segment and region

Certain customer segments demonstrate significantly higher retention, indicating strong loyalty and repeat engagement.

Churn is notably higher among low-frequency buyers, highlighting the need for targeted engagement and reactivation strategies rather than blanket promotions.

Customers enrolled in loyalty programs show higher repeat purchase frequency, reinforcing the importance of loyalty-driven retention.

A relatively small group of loyal customers contributes a disproportionately large share of total revenue, emphasizing the value of retaining high-tier customers.

Specific regions (notably Liverpool and Birmingham) exhibit higher churn rates, while store maturity and localized engagement play a key role in retention performance.

Due to file size limitations, the complete dashboard walkthrough video is hosted externally.

👉 Watch the demo here: [Paste your public video link]

(The same link is also referenced in the project documentation.)

Detailed documentation covering project objectives, methodology, assumptions, and insights is available in the docs/ folder.

• data/ – Datasets used for analysis
• analysis/ – Analysis-related files
• powerbi/ – Power BI (.pbix) dashboard
• docs/ – Project documentation
• exports/ – Exported reports (PDF / HTML)
• resources/ – Images, logos, and supporting assets
• insights/ – Dashboard screenshots used in README

This analysis helps identify at-risk customers, high-value inactive segments, and region-specific churn patterns. The insights support data-driven decisions to improve customer retention, increase repeat purchases, and enhance overall customer lifetime value through targeted loyalty and engagement strategies.

• This project is created for analytical and educational purposes.
• All brand names and datasets are used strictly for demonstration purposes.