Bellabeat-Analysis

Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products.

BELLABEAT Case Study

How can a Wellness Technology Company Play It Smart?

INTRODUCTION: Bellabeat is a high-tech manufacturer of health-focused smart products for women that keeps them informed of their health and activities inspiring and motivating them to take necessary steps in maintaining their health. The company has a variety of products namely the Bellabeat App, Leaf, Time, Spring and the Bellabeat Membership program to cater to gathering information on their activity, sleep, stress, menstrual cycle, mindfulness habits and water intake while also making their products stylish and wearable.
The aim of this report is to analyse non-Bellabeat devices’ smart device usage data to gain insights on some smart device trends, how these trends can be applied to Bellabeat customers and how these trends could be incorporated in any one Bellabeat product’s marketing strategy.
The key stakeholders in this task are Urska Srsen and Sando Mur, the cofounders of Bellabeat.

FINAL INSIGHTS AND SUGGESTIONS

INSIGHTS:

1. On an average, highest percentage of the Active Minutes composition is under SedentaryMinutes [81.3%], which means most users spend their day spending under 30 minutes of activity,that is equal to walking for 30 minutes at 4 miles per hour. For an adult of average weight, this amount of exercise will burn about 135 to 165 additional Calories.

Second highest makeup is of Lightly Active minutes [15.8%]. Roughly 3% of the makeup is composed of Very Active and Fairly Active Minutes in total.
From this we come to know that most of the sample users perform activities of daily living only, such as shopping, cleaning, watering plants, taking out the trash, walking the dog, mowing the lawn, and gardening. While a very small population spends active hours doing aerobics, jogging or skipping.

2. On an average, highest category of distance makeup is of Lightly Active Distance [61.7%], followed by Very active distances [27.8%] and then moderately active distances [10.5%].

3. On an average, users cover the highest no. of steps on Tuesdays and Thursdays of around 8000 steps. But we are not confident on Tuesday as it has more records.

4. On an average, most users have highest sleeping minutes of over 400 minutes i.e. 6.6 hours on Sundays and Wednesdays. But Wednesday is ruled out due to additional records on that day which poses skewness.

5. Average weight of users is found to be 72 kg and average BMI is found to be 25.18 which is found to be in overweight category.

6. Information on weight and bmi is more often manually recorded than done by users. Also, users are more likely to record their weights and bmi in the AM periods rather than PM periods.

7. User reports are mostly made between 6 o’clock to 9 o’clock each day, while manual reports are made at 11:59:59 pm each night.

8. Intensity counts highest between 8 – 11 am in the mornings, while highest between 12-2 pm and 5-7 pm in the afternoons and evenings.

APPLICATION OF INSIGHTS TO BELLABEAT PRODUCTS:

Goal-oriented:
1. For the Bellabeat app, based on the user's data on activity minutes, the app can suggest the user to take a few minutes out to achieve certain set goals and be active throughout the week.
2. The bellabeat app can monitor user's sleep records and suggest healthy sleeping schedules.

All this while monitoring how well the users keep up with the schedule and rewarding points as they complete each goal that can be converted to gift points for purchasing other lines of Bellabeat products for them and their loved ones.

Wellness Tracking:
1. Can incorporate weight and BMI measurement into Bellabeat App to inform and track user's health while using these data to add to the menstruation aid and letting the user's know how much exercise is needed and accordingly plan their day/week goals. [Weight and Menstrual Health Link]
2. Remind users to manually input their weight and BMI twice a week for all weeks and remove device calculated weight and bmi measurements as they can mislead. Can remind between 6-9 AM in the mornings.
3. Inform users when their intensity levels and stress levels peak and enable Zen mode (like a meditation period or a notification to rest for some minutes before continuing any work/task) to relieve of the high intensity/stress rates.