[cite_start]This project analyzes physical activity data from smart device users to help Bellabeat, a high-tech manufacturer of health-focused products for women, optimize its marketing strategy. [cite: 1, 2]
- [cite_start]Analyze consumer behavior using open-source Fitbit data. [cite: 3, 5]
- [cite_start]Identify trends and growth opportunities for Bellabeat products. [cite: 3]
- [cite_start]Provide data-driven strategic recommendations. [cite: 315]
- [cite_start]SQL (BigQuery): For data cleaning, joining tables, and user categorization. [cite: 33, 58, 88]
- [cite_start]Google Sheets: For initial data cleaning and formatting. [cite: 24]
- [cite_start]R (ggplot2): For data visualization and identifying patterns. [cite: 108, 148, 179]
During the analysis, I identified several critical data limitations:
- [cite_start]Time Period: The data actually covers only 2 days instead of the stated period. [cite: 9, 301]
- [cite_start]Sample Size: 33 users were analyzed instead of the 30 originally mentioned. [cite: 9, 303]
- [cite_start]Reliability: Due to the short 48-hour observation period, the data is used to identify general trends rather than long-term habits. [cite: 304, 306]
- [cite_start]User Engagement: 88% of analyzed users are "Power Users" who track their data daily. [cite: 92, 94]
- [cite_start]Activity vs Calories: Confirmed a strong positive correlation between high-intensity activity and calorie burn. [cite: 295, 309]
- [cite_start]Sedentary Behavior: Even active users spend an average of 990 minutes per day being sedentary. [cite: 170]
- [cite_start]Step Goals: Most users consistently stay below the recommended 7,500-step health threshold. [cite: 269, 313]
- [cite_start]Implement notifications to encourage high-intensity "short bursts" of activity. [cite: 318]
- [cite_start]Use educational alerts regarding WHO and health standards (30 mins activity/7,500 steps). [cite: 311, 319]
- [cite_start]Improve long-term data collection (30+ days) for more personalized reporting. [cite: 321]