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Bellabeat Case Study - Google Data Analytics Capstone using Python.

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BellaBeat EDA

1_SjEGKrjDp7skk4URhzW5Nw

Bellabeat was founded in 2013. A high-tech company that manufactures health-focused wellness, smart devices, and products for women. By 2016, the company has grown globally and had become available to many online retailers and also including its own website.

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.

Table of Contents

Background

As a data analyst on the marketing team, I will analyze the data to gain insight into non-Bellabeat's smart devices and focus on one of Bellabeat’s smart devices and apply these insights to a presentation for the marketing strategy. These questions will guide our analysis.

  • What are some trends in smart device usage?
  • How could these trends apply to Bellabeat customers?
  • How could these trends help influence Bellabeat marketing strategy?

Stakeholders

  • Urška Sršen - Cofounder and Chief Creative Officer
  • Sando Mur - Cofounder and on the Executive Team
  • Bellabeat marketing analytics team.

Data Source

The data used is stored in Kaggle under the Fitbit Fitness Tracker Data which is made available through Mobius that contains personal information about their daily activity like heart rate, sleep pattern, and physical activity. The data is organized into 18 CSVs and It includes both wide and long formats.

Due to some limitations of the data, we might be missing out on a few demographic features like age. We also do not have the height of the users, since BMI calculation considers weight, height, age, and gender.

We are not sure if the thirty users are handpicked or called at random for the population of data. The data is not current and not direct from Bellabeat.

Suggestion

  • The total no of steps taken doesn’t necessarily mean that the person will have a better sleep. Bellabeat app could provide a quiz when the user signs up to help the user understand better how they can improve both their sleep and how much they need to walk per day according to their height, weight, and more.
  • Since the users’ motivation to walk during the week drops gradually, the app can provide points or streaks to help motivate the user. The points can be paid towards the membership program.
  • From the asleep distribution pattern, we can see that 44% of the users sleep less than 7 hours. Bellabeat can offer articles on their app on how to have a productive day and head to bed on time or articles that can help the user better their sleep pattern.
  • The total no of steps taken results in the calories burned. The app can send out alerts that say “they have reached their goal for the day or a word of appreciation”.
  • According to the BMI distribution, 5 users are overweight, 2 are of Normal Weight, and 1 is Obese, Bellabeat can implement an alarm to remind the user every day when it is time for a walk or workout. An alert could also be sent out if the user has been sedentary for a while.