SACASE
04HabitSphere
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04 / 07Wellness / Behavior analytics2026

HabitSphere

Habit tracking becomes useful when the product explains patterns—not when it only celebrates streaks.

ROLE
Product design · Full-stack interface · Analytics UX
STATUS
Product prototype
STACK
React · TypeScript · Analytics UI · Responsive web
PRODUCT INTERFACE / 04Daily check-in
HabitSphere dashboard showing daily completion progress and habit check-ins
PRODUCT JOURNEY / 04

THE PRODUCT,
IN USE.

One complete interface state at a time. Each screen documents the task, the system response, and what the user can do next.

01
01 / PLAN

Define the behavior

The user creates a habit with cadence, target, and context.

01Daily check-in
HabitSphere dashboard showing daily completion progress and habit check-ins
02
02 / LOG

Record daily reality

Simple check-ins build the behavioral history without making the dashboard heavy.

02Risk signal
Habit risk analysis with confidence, source, and review recommendation
03
03 / INSPECT

Reveal patterns

Calendar, streak, completion, and predictive views expose what is changing.

03Detailed analytics
Detailed habit prediction cards with confidence and evidence
04
04 / RECOVER

Turn a lapse into a plan

The product offers an explicit recovery path rather than relying on motivation copy.

04Recovery plan
Recovery and quit lab for creating a structured plan around an unhealthy habit
01 / CONTEXT

WHY THIS PRODUCT
NEEDED TO EXIST.

CHALLENGE

Most habit products reward completion but do little with missed behavior, correlated patterns, or recovery. The difficult part is turning activity history into guidance without presenting weak signals as medical certainty.

RESPONSE

I organized the experience into a daily action layer, a history layer, and an analysis layer. Predictions are shown with confidence and source context, while recovery plans remain explicit user decisions.

02 / OPERATING LOGIC

THE OPERATING
SEQUENCE.

  1. 01PLAN

    Define the behavior

    The user creates a habit with cadence, target, and context.

  2. 02LOG

    Record daily reality

    Simple check-ins build the behavioral history without making the dashboard heavy.

  3. 03INSPECT

    Reveal patterns

    Calendar, streak, completion, and predictive views expose what is changing.

  4. 04RECOVER

    Turn a lapse into a plan

    The product offers an explicit recovery path rather than relying on motivation copy.

03 / PRODUCT DECISIONS

DECISIONS THAT
SHAPED THE BUILD.

01 / DAILY

Action stays simple

The main dashboard keeps completion and logging immediate while deeper analysis lives one level away.

02 / EVIDENCE

Predictions show their limits

Risk states include confidence and source context so analysis does not masquerade as certainty.

03 / RECOVERY

Missing is not failure

Recovery flows help users restart or change a habit instead of turning a broken streak into a dead end.

04 / INTERFACE EVIDENCE

Secondary screens that extend the core journey without diluting it.

05 / 05Habit library
Habit library with current streaks, completion rates, and quick logging
05 / MY RESPONSIBILITY

SCOPE OF
RESPONSIBILITY.

I designed the product structure, the responsive application shell, habit workflows, analytics views, calendar, recovery experience, and report surfaces shown in this prototype.

The prototype demonstrates daily tracking, habit creation, streak and completion views, calendar activity, detailed analytics, pending reminders, and recovery planning. Predictive insights are prototype behavior, not health advice.

  • Habit tracking
  • Behavior analytics
  • Recovery UX
  • Data visualization
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