https://github.com/dcostachar/bellabeat-case-study

An analysis of Fitbit Fitness Tracker data with R to examine user behaviour and conduct a competitor analysis to optimize Bellabeat's product marketing strategies.
https://github.com/dcostachar/bellabeat-case-study

consumer-behaviour-analysis data-visualization exploratory-data-analysis ggplot2 marketing-analytics r statistical-analysis tidyverse

Last synced: about 2 months ago
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An analysis of Fitbit Fitness Tracker data with R to examine user behaviour and conduct a competitor analysis to optimize Bellabeat's product marketing strategies.

• Host: GitHub
• URL: https://github.com/dcostachar/bellabeat-case-study
• Owner: dcostachar
• Created: 2024-08-20T18:01:42.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-12-04T21:45:03.000Z (2 months ago)
• Last Synced: 2024-12-04T22:32:53.629Z (2 months ago)
• Topics: consumer-behaviour-analysis, data-visualization, exploratory-data-analysis, ggplot2, marketing-analytics, r, statistical-analysis, tidyverse
• Homepage:
• Size: 68.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Bellabeat Case Study: How Can A Wellness Technology Company Play It Smart?

Author: Charlene D'Costa 


Date: July 4, 2024 


Capstone project for the Google Data Analytics Professional Certificate. 


[Fitbit Fitness Tracker Datasets](https://www.kaggle.com/datasets/arashnic/fitbit?select=mturkfitbit_export_3.12.16-4.11.16)

# Project Overview 

**This case study analyzes Fitbit Fitness Tracker data to develop a data-driven marketing strategy for Bellabeat, a leading manufacturer of health-focused smart devices for women.**

Using the six-step data analysis process—**Ask, Prepare, Process, Analyze, Share, and Act**—I leveraged **R** and the **tidyverse ecosystem (including `readr`, `dplyr`, and `tidyr`)** to clean, process, and analyze complex datasets. The analysis included competitor research and provided insights into key user behaviours such as activity levels, sleep quality, energy expenditure, and device usage trends.

With **ggplot2**, I created data visualizations to communicate my findings and proposed actionable recommendations, including **targeted advertising campaigns, in-app engagement strategies,** and **product feature enhancements.** These initiatives aim to increase customer engagement, strengthen Bellabeat's market position, and drive its business growth in the smart device market.

[Click here](https://dcostachar.github.io/bellabeat-case-study/) to view the full project.