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Jumprope

Designing an adaptive workout app that gets people moving faster

People wanted to work out — but decision-making got in the way.
Jumprope is a mobile fitness app that uses AI to build personalized workouts.


Users were overwhelmed before they even started. I redesigned the experience to remove friction, create momentum, and help people feel confident from the first rep.

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Project Overview

Jumprope simplifies how users start, follow, and finish personalized workouts.
I redesigned onboarding, the workout session flow, and key feedback patterns to reduce hesitation and strengthen motivation.

As the sole designer, I worked directly with the founder and developer across iOS and Android — leading user research, interaction design, and establishing a compact design system to support fast iteration.

Early usability testing and survey results projected a 20–30% lift in engagement once we streamlined the entry point and clarified progression.

Role: 

Sole Product Designer — Research, Interaction Design, Mobile Design System

Team:

Founder/Developer collaboration

Methods:

User interviews, comparative testing, prototype validation

Problem

Most fitness apps front-load setup. Users must choose workouts, durations, or goals before taking any action. This often leads to choice fatigue and drop-off.


Jumprope was created to flip that model: start first, adapt later.
The challenge was building an experience that preserved personalization without slowing momentum.

Objective

Design a friction-free experience that lets users start quickly, adjust workouts in context, and stay engaged through clear visual feedback and progress cues.

Process

I approached this project by understanding where hesitation began and designing for instant engagement instead of upfront effort. My goal was to translate user motivation into action through clear, confirmable feedback and adaptive personalization.

The process focused on balancing three principles:

  1. Momentum over setup — reduce cognitive friction.

  2. Personalization through context — adapt during use, not before.

  3. Confidence through clarity — every tap should reinforce success.

Understanding the Market and Motivation

Through competitor analysis and discovery surveys, I identified a pattern: users wanted short, guided workouts they could start immediately. Long setup forms and rigid routines caused emotional fatigue.

Mapping Friction in the Original Flow

Before Jumprope’s redesign, most fitness apps required users to configure personal data, goals, and levels before starting. Research and early discovery sessions showed that this approach caused decision fatigue and low engagement — users wanted to move immediately, not fill out forms.

Without a product of our own yet, I mapped these pain points using references from competitor workflows and survey feedback. The key insight: setup screens created more abandonment than motivation.

Designing an Experience

With early insights mapped, I began creating Jumprope’s first interactive prototype to test how quickly users could move from selection to action. The goal was to build flow efficiency. Thus minimizing hesitation between “I want to work out” and “I’m working out.”

These early Android screens focused purely on structure, hierarchy, and pacing rather than aesthetics. Each iteration explored how users interpreted labels, timing cues, and session results.

Testing revealed that small visual anchors — like dynamic labels, progress summaries, and color-coded confirmation states — dramatically improved comprehension without adding visual weight.

Refining and Building Momentum

Once early usability confirmed the pacing model, I shifted toward refining micro-interactions and real-time feedback. The experience needed to make progress feel tangible — through transitions, motion cues, and subtle confirmation.

These refinements focused on maintaining engagement across rest periods and transitions, ensuring that users felt guided rather than interrupted.

Refining and Building Momentum

After validating the flow, I finalized the onboarding experience. Instead of asking for everything upfront, Jumprope’s AI gathered a few key details (height, goals, and fitness level) to instantly generate a personalized first workout.

The result was a three-screen onboarding that balanced speed with relevance, cutting setup time by more than half while preserving meaningful personalization.

Validation and Testing

Prototype testing validated that the simplified flow boosted comprehension and confidence. Participants described it as “easier to start” and “less intimidating” than competitors.

Data from moderated tests showed a significant reduction in time to first workout and increased willingness to complete follow-up sessions.

Systematizing the Design

As the product stabilized, I created a mobile design system to unify type, color, spacing, and interaction logic across both Android and iOS.

The foundation established scalable consistency for future features — enabling faster design-to-dev handoff and smoother product iteration.

Solution

The final Jumprope experience focused on momentum, clarity, and adaptive personalization.

From the first tap, users can start a workout immediately. Every interaction provides confirmable feedback — subtle animations for success, color shifts for completion, and guided transitions that reinforce progress without distraction.

Impact

Testing projected a 20–30% increase in engagement and a 40% reduction in setup time.


User interviews confirmed that the experience “felt faster, simpler, and more encouraging.”

Key Outcomes:

  • Reduced entry friction: Drastically minimized setup time.

  • Improved confidence: Reinforced feedback created a sense of control.

  • Stronger retention potential: Users felt rewarded for consistency, not completion.

Reflection

Jumprope reinforced a key design principle — momentum sustains motivation.


By designing for immediacy rather than introspection, the app gave users what they needed most: a clear starting point.

If extended, I’d explore:

  • Real-time adaptive difficulty tuning via AI

  • Habit tracking tied to micro-feedback

  • Social streaks to connect intrinsic motivation with community accountability

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