Bellabeat Case Study

Project overview

This case study analyzes fitness tracker data to understand user behavior and provide strategic recommendations for Bellabeat, a wellness technology company. Using R, the work examines daily activity, sleep, and calorie patterns to inform product and marketing decisions.

The analysis surfaces user engagement and health behaviors relevant to the competitive wellness technology market and demonstrates how data can drive business decisions.

Dataset / source

Fitbit-style fitness tracker data (daily and intraday steps, calories, sleep, intensity) used in Kaggle for the Bellabeat case study.

Tools used

R and Kaggle.

What problem you solved

Bellabeat needed evidence-based insight into how users interact with wearables so product and marketing could be aligned with real usage, activity, and sleep patterns.

Key insights

• Data quality
  Cleaning and standardization steps ensured consistent date handling and metrics across users.
• Activity & engagement
  Step counts, calories, intensity, and sedentary behavior describe how users engage with tracking.
• Sleep & health
  Sleep duration and quality were examined alongside physical activity.
• Recommendations
  Findings were translated into actionable themes for product development, marketing, and engagement.