Welcome to the repository for my Bellabeat case study! This project was completed as part of my Google Data Analytics Specialization. It explores how Bellabeat, a high-tech manufacturer of health-focused products for women, can use smart data analysis to improve decision-making and product strategy.
⚠️ Note: While this case study is completed using R (as recommended by the specialization I took), please note that I’m more confident in Python than R.
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├── src/ # Source code and analysis notebooks
│ └── case-study-bellabeat-updated-all-files.ipynb
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└── README.md # You are here!
Bellabeat wants to gain deeper insight into user behavior using data from smart devices such as Fitbits. The goal is to leverage this insight to enhance marketing strategies and refine their product offerings for better user engagement and health outcomes.
- How are users engaging with their wellness trackers?
- What patterns emerge from user activity and sleep data?
- How can Bellabeat tailor its strategies based on user behavior?
- Language Used: R
- Platform: Jupyter Notebook (
.ipynb) - Libraries: tidyverse, lubridate, ggplot2, dplyr, etc.
- 📑 Presentation: Bellabeat: How Can We Play it Smart?