Introduction: Bellabeat is a high-tech company and the go-to wellness brand for women with an ecosystem of products and services focused on women’s health. The company’s mission is to empower women to reconnect with themselves, unleash their inner strengths, and be what they were meant to be. Their main focus is on giving women the tools to live in harmony with themselves. The company was founded by Urška Sršen and Sando Mur in 2013.Sršen used her background as an artist to develop beautifully designed technology that informs and inspires women around the world. Collecting data on activity, sleep, stress, and reproductive health has allowed Bellabeat to empower women with knowledge about their own health and habits. You can find more about the company on their website https://bellabeat.com/

The purpose of this case study is to focus on one of the Bellabeat products devices and perform data analysis to gain better insight into how consumers use their smart devices. The insights we will gain through this analysis will help guide the marketing strategy for the company.

Ask

The business task is to analyze smart devices usage data and provide high-quality recommendations for Bellabeat’s marketing strategy.

Questions for the analysis:

1. What are some trends in smart device usage?

2. How could these trends apply to Bellabeat customers?

3. How could these trends help influence Bellabeat’s marketing strategy?

Key Stakeholders:

Urška Sršen: Bellabeat’s cofounder and Chief Creative Officer.

Sando Mur: Mathematician and Bellabeat’s cofounder; key member of the Bellabeat executive team.

Bellabeat marketing analytics team: A team of data analysts responsible for collecting, analyzing, and reporting data that helps guide Bellabeat’s marketing strategy.

About data:

The data used in this analysis come FitBit Fitness Tracker Data (CC0: Public Domain, dataset made available through Mobius) This Kaggle dataset was generated by respondents to a distributed survey via Amazon Mechanical Turk between 03.12.2016-05.12.2016. The dataset contains personal fitness tracker from thirty fitbit users. Thirty eligible Fitbit users consented to the submission of personal tracker data, including minute-level output for physical activity, heart rate, and sleep monitoring.

Limitation:

• The sample size of data is small. It contains only 33 participants. Data has low reliability, and we might get inaccurate or inconsistent results that are not valid.

• The data is 6 years old and the results may not be relevant for the present moment.

• Originality of data is low because this is the third- party data generated by respondents to a distributed survey via Amazon Mechanical Turk between 03.12.2016-05.12.2016.