Google Data Analytics Second Project
Bellabeat* Analysis
My aim was to identify trends in the use of smart devices, then use the insights to make recommendations on marketing Spring, a product of Bellabeat for traking water intake and hydration.
My aim was to identify trends in the use of smart devices, then use the insights to make recommendations on marketing Spring, a product of Bellabeat for traking water intake and hydration.
The images above summarize the visualizations created in R:
The records by day show weekdays as most popular days for record entries.
The frequency comparison graph shows that the daily activity is the most popular, while weight logs are least popular, and least frequently entered.
The manual entries chart shows that most weight log entries were done manually.
All this combined suggests that smart devices usage depends heavily on integration into daily life. Spring has advantage of its packaging which makes it easily usable on weekdays and weekends when women are most likely socializing.
I produced two key deliverables for two key audiences: a Google Slides presentation for the Bellabeat executives, and a project document for the marketing analytics team that details everything I did.
Access the slideshow below.
The files for the marketing analytics team can be accessed at my Bellabeat Repository on GitHub.
Tools and methodology:
6-step analysis process: Ask, Prepare, Process, Analyze, Share, Act
SQL (BigQuery)
R (RStudio Cloud)
Google Slides
RMarkdown
GitHub
Google Sites