Data_projects_TripleTen

Mobile Plans: Usage & Revenue Analysis

Goal:
Analyze user behavior and revenue patterns across two mobile plans to determine which generates higher engagement and profitability.

Data Tasks:

• Cleaned and prepared the dataset for analysis
• Calculated descriptive statistics and plan-specific KPIs
• Visualized call duration, message count, and internet usage distributions

Statistical Analysis:

• Conducted hypothesis testing to compare average revenue between plans
• Assessed statistical significance using t-tests

Key Insight:
The analysis identified measurable differences in user spending patterns between the two plans, providing evidence for data-driven business recommendations.

Skills Used: pandas, matplotlib, NumPy, statistical testing, data visualization

Files:

• mobile_plans_eda.ipynb

View Project Notebook

Future Improvements

• Expand the dataset with additional years of data to analyze long-term customer behavior and seasonal patterns.
• Use machine learning to predict which plan a new customer is more likely to choose, based on historical usage.
• Develop an interactive dashboard (e.g., using Streamlit or Plotly Dash) to visualize plan performance, user demographics, and revenue trends in real time.
• Explore segmentation by location or age group to identify targeted marketing opportunities for each plan type.