Enhance Subscription Retention with Customer Churn Prediction

Enhance Subscription Retention with Customer Churn PredictionEnhance Subscription Retention with Customer Churn Prediction

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Zacchaeus Olabode

• Mar 23

Customer Churn Prediction & Retention Analytics:

Helps subscription-based businesses lower their attrition rates, I developed a "Churn Warning System." The model analyzes user engagement signals to flag customers who are showing signs of leaving before they actually cancel. This gives the business a proactive window to reach out with retention offers and save the account.

Key Result: Identified the top 3 drivers of customer loss, allowing for data-driven retention strategies that protect long-term revenue.

Data Analysis Machine Learning Engineering pandas Python

Advik Rathee

• Jul 14

Built this one for an e-commerce customer behavior project - 18,000+ customers, segmented using RFM (Recency, Frequency, Monetary) analysis.

The interesting part wasn't the segmentation itself, it was what it revealed: nearly 22% of customers were "at risk" of churning, and most businesses wouldn't know that until those customers had already stopped buying.

This is the kind of insight that's usually sitting in your order data already, it just needs the right lens. Happy to take a look at your numbers if you're curious what's hiding in yours.

Tools used: Power BI, SQL, Python (Pandas, Scikit-learn for clustering)

Data Modeling Data Visualization dataanalytics Python Microsoft Power BI Data Analysis

SHA'AIBU AUWAL

• Jul 16

I am a website designer

Python Web Design

Samiya Imran

• Jul 15

Built a 4-part Power BI dashboard suite analyzing $80M+ in revenue for supply chain & e-commerce data — designed for 4 different stakeholders.

📊 Executive KPI Dashboard (VP of Supply Chain) — Revenue, profit & a 71% revenue drop identified in 2018 🚚 Delivery Performance (Procurement Team) — 54.8% late delivery rate flagged, broken down by shipping class 📦 Product & Warehouse Analysis (Warehouse Ops) — 33K SKUs across 9 warehouses, revenue vs. margin comparison 💳 Customer & Payment Insights (Finance Team) — Sentiment, review scores & payment method breakdown

Tools: Tableau, SQL, Excel, Python