Project Summary: Consumer Behavior & CLV Analysis in Educational Subscription Services

Overview:
This project explores consumer behavior, segmentation, and customer lifetime value (CLV) in educational content subscription services. With e-learning platforms booming post-pandemic, understanding user preferences, engagement, and retention strategies is key for market positioning and business growth.

Key Objectives:
✅ Analyze Consumer Preferences – Identify key factors driving engagement with e-learning platforms.
✅ Segment Users – Classify consumers based on demographics, behavior, and psychographics.
✅ Estimate CLV – Assess customer lifetime value across different user segments.
✅ Evaluate Market Positioning – Compare major e-learning platforms and their unique value propositions.
✅ Develop Business Strategies – Provide recommendations for optimizing engagement, retention, and profitability.

Data & Methodology:
📊 Data Sources: Primary (Surveys, Interviews) + Secondary (Market Reports, Competitor Analysis)
🛠 Tech Stack: Python 🐍, Excel 📑, Enginius, Tableau 📊
📌 Analytical Approaches:

• Segmentation Analysis: Hierarchical & K-means clustering to classify users.
• CLV Estimation: Churn rates, retention analysis, and predictive modeling.
• Market Positioning: Perceptual mapping and competitive analysis.

Key Findings & Insights:
📌 Identified Four Consumer Segments:

• Engaged Explorers – Community-driven, value quality & credentials.
• Price-Sensitive Students – Cost-conscious, prefer broad content.
• Practical Professionals – Prioritize usability & tangible career benefits.
• Selective Learners – Invest in personalized learning experiences.
  📌 CLV varies significantly across platforms, with LinkedIn Learning leading due to professional integration.
  📌 Key Retention Strategies: Personalization, micro-credentials, and career-aligned content drive engagement.

Impact & Future Scope:
This study provides actionable insights for e-learning providers to enhance engagement, refine # models, and improve CLV. Future work could explore AI-driven personalized learning, adaptive # models, and integration with corporate training programs.

---

List of Topics Covered:

• Consumer Behavior in Educational Subscriptions
• Market Segmentation (Hierarchical & K-Means Clustering)
• Customer Lifetime Value (CLV) Estimation
• Subscription-Based Business Models
• Data Collection & Survey Analysis
• Predictive Modeling & Churn Analysis
• Competitor Analysis (Coursera, Udemy, LinkedIn Learning)
• Perceptual Mapping & Market Positioning
• User Retention Strategies & Engagement Optimization
• Data Visualization (Enginius, Tableau)
• AI & Personalized Learning Recommendations
• # Models & Revenue Optimization