Urška Sršen and Sando Mur founded Bellabeat, a high-tech company that manufactures health-focused smart products. Sršen leveraged her background as an artist to develop beautifully designed technology that informs and inspires women worldwide. Bellabeat collects data on activity, sleep, stress, and reproductive health to empower women with knowledge about their own health and habits. Since its establishment in 2013, Bellabeat has rapidly grown, positioning itself as a tech-driven wellness company for women. By 2016, Bellabeat had expanded globally, offering multiple products available through various online retailers and its e-commerce channel.
Welcome to the Bellabeat analysis case study! In this project, I take on the role of a junior data analyst in Bellabeat's marketing and analytics team. Bellabeat designs health-focused products for women and has the potential to become a larger player in the global smart device market. Urška Sršen, Bellabeat's co-founder and Chief Creative Officer, believes that analyzing smart device fitness data could unlock new growth opportunities for the company. I have been tasked with analyzing smart device data to gain insight into how consumers are using Bellabeat's products.
The primary goal of this case study is to perform real-world tasks as a data analyst and answer key business questions using the six phases of data analysis: ask, prepare, process, analyze, share, and act.
Three main questions will guide my analysis:
a. What are some trends in smart device usage?
b. How could these trends apply to Bellabeat customers?
c. How could these trends help influence Bellabeat's marketing strategy?
Bellabeat needs support in marketing its product lineup, which includes health-tracking devices like the Leaf, Ivy, and Time. This case study focuses on a comparative analysis with competitor data, specifically examining user trends from Fitbit to identify opportunities in the wellness smart device market. The insights gleaned from this analysis will help identify growth opportunities for Bellabeat and inform marketing strategies.
To tackle this case study, I follow the six phases of data analysis as outlined by Google: Ask, Prepare, Process, Analyze, Share, and Act.
1. Ask Phase
This phase clarifies our business objectives, focusing on understanding how smart devices are used by non-Bellabeat users and how those insights can apply to Bellabeat's products.
2. Prepare Phase
We leverage publicly available Fitbit data to analyze the daily habits of smart device users. This dataset includes minute-level details from 30 users, providing a base for understanding general user behaviors.
3. Process Phase
Using RStudio, I cleaned and prepared the data for analysis. This included installing necessary packages, importing data, and handling missing values or inconsistencies.
4. Analyze Phase
After processing, I conducted a thorough analysis to uncover patterns and trends in the data, focusing on steps, sleep, and sedentary behavior.
5. Share Phase
The results from the analysis were visualized to clearly communicate findings, using tools like ggplot2 for graphical representations.
6. Act Phase
The final phase involves making strategic recommendations based on the analysis. This includes enhancing Bellabeat’s app functionality and marketing strategies to better meet the needs of current and potential users.
a. A clear summary of the business tasks.
b. Descriptions of all data sources used.
c. Documentation of data cleaning/manipulation.
d. A summary of the analysis.
e. Supporting visualizations and key findings.
f. High-level content recommendations based on our analysis.
i. Smart Device Usage Trends: Users primarily track activity levels and calories burned, with fewer monitoring sleep and even fewer tracking weight.
ii. Activity and Sedentary Behavior: Users fall short of recommended activity levels and spend excessive time in sedentary activities.
iii. Sleep Patterns: Average sleep duration is about 7 hours per night, with users spending around 30 minutes awake in bed.
iv. Weekly Trends: Users track activities more on Sunday, Monday, and Tuesday compared to other weekdays.
i. Enhanced Focus: Bellabeat should emphasize tracking steps, calories, and sleep within its application based on user preferences.
ii. Health Promotion: Promote healthy lifestyles and offer guidance on achieving fitness goals through guided programs.
iii. Communications Strategy: Clearly communicate Bellabeat's wearable technology benefits through tailored communication across various channels.
iv. User Engagement: Investigate reasons for low sleep tracking usage and engage users through focus groups or surveys.
v. Goal-Setting Programs: Introduce guided goal-setting programs to help users establish and track fitness and wellness objectives.
vi. Health Status: A significant portion of fitness tracker users (62.5%) are categorized as obese.
This case study provides valuable insights into the health and activity patterns of smart device users. By applying these insights, Bellabeat can enhance its marketing approach and product offerings, potentially increasing its market share and influence in the tech wellness space.
For further information, please contact:
Name: Jitu Kumar
Email: jitukumar9387@gmail.com