Welcome to the Bellabeat data analysis case study! In this case study, we delve into the world of health-focused smart products for women and explore smart device usage data to gain insights that will inform Bellabeat's marketing strategy.
In this case study, we will perform real-world tasks of a junior data analyst at Bellabeat. By following the steps of the data analysis process – ask, prepare, process, analyze, share, and act – we aim to uncover valuable insights from the provided datasets.
The datasets used in this analysis were made available through Mobius. They include:
- Daily Activity
- Daily Steps
- Daily Sleep These datasets provide detailed information on activity, steps, and sleep patterns of individuals using smart wellness products, which will be crucial for our analysis.
As a junior data analyst at Bellabeat, we are tasked with analyzing smart device usage data to gain insight into how consumers use non-Bellabeat smart devices. We will then select one Bellabeat product to apply these insights to and formulate high-level recommendations for Bellabeat's marketing strategy.
To guide our analysis, we will address the following questions:
- What are some trends in smart device usage?
- How could these trends apply to Bellabeat customers?
- How could these trends help influence Bellabeat marketing strategy?
Guiding Questions
- What is the problem you are trying to solve?
- How can your insights drive business decisions?
- Identify the business task
- Consider key stakeholders
- Deliverable
- A clear statement of the business task
We will use various data analysis techniques and visualizations to uncover trends and patterns in smart device usage, providing actionable insights for Bellabeat's marketing team.
To begin exploring the datasets and following along with the analysis process, download or clone this repository and refer to the provided Jupyter Notebook or R script.
Note:the datasets can be acessed through https://www.kaggle.com/datasets/arashnic/fitbit