https://github.com/rupashi03/fitbit-user-eda-case-study

Performed Exploratory Data Analysis (EDA) on Fitbit users' data to uncover trends in activity and health metrics.
https://github.com/rupashi03/fitbit-user-eda-case-study

business-analysis case-study consumer-insights data-analysis exploratory-data-analysis health-data r user-behavior-analytics

Last synced: about 2 months ago
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Performed Exploratory Data Analysis (EDA) on Fitbit users' data to uncover trends in activity and health metrics.

• Host: GitHub
• URL: https://github.com/rupashi03/fitbit-user-eda-case-study
• Owner: rupashi03
• Created: 2024-11-09T18:38:43.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-11-10T12:02:36.000Z (6 months ago)
• Last Synced: 2025-03-25T22:45:04.985Z (about 2 months ago)
• Topics: business-analysis, case-study, consumer-insights, data-analysis, exploratory-data-analysis, health-data, r, user-behavior-analytics
• Language: Jupyter Notebook
• Homepage:
• Size: 591 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
 Bellabeat Capstone Project| R 

  
 1. Company Background 

  
  Bellabeats is a high-tech company founded by Urška Sršen and Sando Mur in 2013.

    It manufactures health-focused smart products that collects data on activity, sleep, stress and reproductive health and helps women around the world grow healthy habits. 

    By 2016, Bellabeat has expanded their products globally, through online retailers and selling them on their own e-commerce website.

    


  
 Bellabeat has launched 5 products:

    

 
 


Bellabeat app: The Bellabeat app provides users with health data related to their activity, sleep, stress, menstrual cycle, and mindfulness habits.

    This data can help users better understand their current habits and make healthy decisions. The Bellabeat app connects to their line of smart wellness products.

 
 


Leaf: Bellabeat’s classic wellness tracker can be worn as a bracelet, necklace, or clip. The Leaf tracker connects to the Bellabeat app to track activity, sleep, and stress.

  


Time: This wellness watch combines the timeless look of a classic timepiece with smart technology to track user activity, sleep, and stress.

    The Time watch connects to the Bellabeat app to provide you with insights into your daily wellness.

  


Spring: This is a water bottle that tracks daily water intake using smart technology to ensure that you are appropriately hydrated throughout the day. 

    The Spring bottle connects to the Bellabeat app to track your hydration levels.

 
 


Bellabeat Membership: Bellabeat also offers a subscription-based membership program for users.

    Membership gives users 24/7 access to fully personalized guidance on nutrition, activity, sleep, health and beauty, and mindfulness based on their lifestyle and goals.

    

  

  
 2. Ask 

  
 2.1. Business Task

  


  As an analyst working in the marketing analyst team I will use the smart device usage data in order to gain insights into how customers use non-Bellabeat smart devices. I will then use these insights to recommend some market strategies which will be presented to the key stakeholders.

  In this case study, I will focus on the Bellabeat App for recommendations.

  


   
 2.2. Key Stakeholders

    


      
Urška Sršen: cofounder and Chief Creative Officer.

      
Sando Mur: cofounder and a key member of the Bellabeat executive team.

      
Bellabeat marketing analytics team.

  

  

  
 Steps 3-5[Prepare, Process and Analyse] elaborated in details, in the notebook

  

  
6. Act 

  


    Key findings: 
 

      
On an average, users take 7,638 steps each day. This average is lower than the 10,000 steps recommended by CDC.

      
On average, each user spends 16.5 hours per day being seated or inactive, which accounts to almost 70% of the day.

      
On an average, people sleep 6.98 hours per day.

      
Users tend to start their day later on weekends, that is around 9am - 10am in the morning. They are most active on Wednesdays between 4pm - 6pm, and around 11am - 1pm on Saturdays.

      
The lightly active type has the longest sleep, while the very active type has lowest duration of sleep.

   

  

  


    
Based on the findings, below are few suggestions:

    


      
The App could recommend daily steps target based on user's profile, lifestyle and personal information available in the app.

        It can also send daily reminders and alerts to their users, if they start to fall behind their daily target.

       
The Bellabeat App can provide a playlist of songs for meditation, to encourage their users to meditate to elevate their users' mental health and wellness. 

         They can also send weekly health tips on their device.

    

  

  Click here to view full case study