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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.

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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

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 to view the full project.

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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.

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