Bellabeat Smart Device Usage Analysis
Google Data Analytics Capstone – Smart Device Health Data Exploration (In Progress)
Business Problem & Objectives
Bellabeat, a high-tech manufacturer of health-focused smart products for women, wants to analyze smart device usage data to uncover how consumers use non-Bellabeat smart devices (Fitbit). Findings will guide executive marketing strategy for the Bellabeat Leaf wellness tracker.
Dataset Overview
Fitbit Fitness Tracker Data (Public Domain via Kaggle/Mobius), containing personal fitness tracker responses from 33 eligible Fitbit users including minute-level activity, heart rate, and sleep monitoring data.
Data Preparation & Cleaning Steps
- Loaded raw Fitbit CSV datasets (dailyActivity, sleepDay, weightLog) into Google BigQuery environment.
- Queried schema definitions and checked for duplicate user ID entries across 33 distinct participants.
- Standardized date timestamps into YYYY-MM-DD formats using SQL CAST functions.
- Calculated daily active time categories: VeryActiveMinutes, FairlyActiveMinutes, LightlyActiveMinutes, and SedentaryMinutes.
Analytical Methodology & Core Insights
Methodology Framework
- •BigQuery SQL Aggregations: Grouped daily step counts, calorie burn, and sleep duration per user.
- •Activity Segmentation: Classified users into activity tiers (Sedentary < 5k steps, Low < 7.5k, Somewhat Active < 10k, Active > 10k).
- •Correlation Analysis: Evaluated relationship between daily active steps and sleep quality indicators.
Analysis Highlights
- •Sedentary Dominance: Participants spent an average of 991 minutes (~16.5 hours) per day in sedentary state.
- •Step Count Clustering: Average daily step count was ~7,637 steps, slightly below the recommended 10,000-step daily target.
- •Sleep & Activity Link: Initial SQL queries indicate a positive correlation between active afternoon movement and sleep efficiency score.
Key Findings
- In-Progress Exploration: Ongoing BigQuery analysis focused on hourly activity spikes during 5 PM – 7 PM commute windows.
- User Engagement Drop-off: Tracking compliance decreases significantly after 20 consecutive days of logging.
Business Recommendations
- Smart Notification Triggers: Send gentle sedentary alerts on the Bellabeat app during mid-afternoon idle hours.
- Gamified Habit Loops: Introduce weekly streak rewards to maintain user logging compliance past the 20-day drop-off threshold.
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