Question
How are people using smart devices today, and where can Bellabeat make wellness feel more achievable?
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Marketing analytics · Tableau · R
Bellabeat: Smart Device Behavior & Growth Opportunities
A case study translating real Fitbit activity and sleep patterns into a clearer engagement strategy for the Bellabeat app.
The brief
Approach
Cleaned and joined daily activity, sleep, calorie, and hourly intensity data in R; designed the analysis and storytelling dashboard in Tableau.
Outcome
Three focused product and marketing levers: make movement achievable, time prompts well, and strengthen sleep tracking.
Behavior signals
The opportunity is in the everyday, not the extreme.
of the average user day was sedentary.
Movement nudges can focus on attainable activity.of days reached 10K steps.
There is room to meet users with a more flexible definition of progress.for the observed steps and calories relationship.
More steps aligned with higher daily calorie expenditure in this sample.participants logged sleep data.
Sleep tracking has meaningful uptake, but consistent use remains an opportunity.Dashboard
A single view of the story.
What the analysis suggests
Three ways Bellabeat can turn signals into support.
Make movement feel achievable
Light activity is a practical entry point for a user base that spends most of the day sedentary. Position short walks, stretch breaks, and movement snacks as meaningful wins, not substitutes for intensive workouts.
Campaign idea: “Small moves, real momentum.”
Time movement prompts around natural peaks
Average intensity rises into midday, dips in mid afternoon, and reaches a daily high around 6 PM. Use these moments for adaptive prompts: a midday reset, an afternoon follow up, or an evening movement cue.
Campaign idea: context aware reminders.
Promote sleep tracking as a complete wellness loop
Only 15 of the 24 people who recorded sleep did so consistently. Make the value exchange concrete: sleep patterns can make the app’s activity guidance and daily reflection feel more personal.
Campaign idea: show what consistent sleep data unlocks.
Method & limits
Designed to inform a hypothesis, not claim a universal truth.
I combined Fitbit daily activity, daily sleep, daily calories, and hourly activity files; standardized dates and IDs in R; then used Tableau calculations to define sleep duration groups, activity composition, 10K step days, and adoption measures.
The data is a small, historical convenience sample, not Bellabeat customer data. It is useful for directional exploration, but recommendations should be validated with representative Bellabeat behavioral data and controlled campaign testing.
Recommendation
Build a gentler engagement loop: move a little, rest well, learn more.
Bellabeat can connect movement and sleep into one supportive daily experience, then test which prompts turn occasional trackers into consistent, informed users.