JumpSquad

Project Overview

JumpSquad is a community-driven fitness app that turns a simple bodyweight exercise, jumping jacks, into a social, habit-forming challenge. Instead of designing another all-in-one fitness tracker, I intentionally narrowed the scope to one exercise, one clear metric, and one loop: challenge, complete, compete, repeat.

This was a dual-track project. Alongside the UX design, I ran it as a business venture, building a full business model canvas, stress-testing the riskiest assumptions behind the idea, and validating demand through three separate pretotyping experiments before investing in high-fidelity design. The goal wasn't just to design a good app; it was to prove people actually wanted it.

Discover

The Problem:

Most fitness apps ask for too much too soon: equipment, subscriptions, complex routines, and users abandon them within weeks. The core insight driving JumpSquad: motivation dies faster than good intentions. People don't quit because exercise is hard; they quit because there's no one watching, no momentum, and no reason to come back tomorrow.

Customer Needs, Pains & Gains:
Needs

• An engaging, accessible way to exercise inside a busy routine

• Motivation, structure, and visible progress

• Community support and recognition while working toward a goal

Pains

• Lack of motivation and boredom from repetitive workouts

• Limited personalization in existing fitness apps

• Difficulty tracking progress or staying consistent

• Confusing tools that increase the risk of giving up

Gains users wanted

• A fitness journey that feels like a game, not a chore

• A visible sense of accomplishment and progress

• Social connection and a motivational community

• Fast, low-effort, at-home workouts

Competitive Landscape

The fitness app market is saturated, but mostly at two extremes:

• Crossrope: premium, hardware-integrated ecosystem (jump rope + sensors)

• JumJac: simple, low-cost, single-purpose counter app, no community layer

The gap: no competitor combined gamification, community, and flexibility without requiring hardware. That gap became JumpSquad's positioning — a middle ground for both fitness beginners and returning users who want engagement without complexity.

Define

Framing the Behavior Loop

Before scoping features, I mapped the target user's motivation cycle using the Hooked model (trigger → action → variable reward → investment), storyboarded through a persona, Sam:

1. External trigger — Sam gets a notification about today's challenge (100 jumping jacks)

2. Internal trigger — Sam sees the leaderboard and wants to beat the top time

3. Action — Sam completes the challenge and beats his own record

4. Variable reward — Sam tops the leaderboard and unlocks a badge ("Lightning Leap Legend")

5. Investment — Sam checks his stats, streak, and shares his win, deepening his commitment to return tomorrow

This loop became the backbone of the entire information architecture and feature set.

Scoping with MoSCoW

To keep the MVP disciplined, I scored every feature against effort (Basic / Performance / Delighter):

Must Have — Jumping Jack Tracker, Daily Calories Burn Tracker, Badges, Reminders & Notifications, User Registration & Login, Progress Tracking

Should Have — Social Leaderboards, Setting Customized Goals, Daily Fitness Challenges

Could Have — Social Media Sharing, Wearable Device Integration, Offline Mode, Dark Mode

Won't Have (this release) — AI Assistant Bot, Background Music Options, VR Experience

Naming the Risk Before Building

Rather than assume the idea would work, I wrote out 10 risky assumptions underpinning the business — spanning market size, retention, monetization, content velocity, and scalability — and plotted them on a Certainty × Impact matrix. Three rose to the top as high-impact, high-uncertainty, and became the focus of validation:

1. Desirability — Will users be interested in a fitness app focused purely on jump-based workouts?

2. Motivation — Will gamification (badges, streaks, leaderboards) actually reduce early drop-off?

3. Real-time experience — Will users perceive live tracking and leaderboard updates as fast and motivating?

Develop

Testing Before Building: Three Pretotyping Experiments

Instead of jumping into high-fidelity design, I ran three lightweight experiments to pressure-test the riskiest assumptions, each framed as an explicit XYZ hypothesis with a pass/fail threshold set in advance.

1. Fake Door Test — Desirability Hypothesis: If exposed to JumpSquad, ≥10% of visitors will click through or sign up. Method: Built a landing page in Framer with the core value prop and a "Join the Waitlist" CTA, distributed via Instagram, WhatsApp, and student fitness communities. Result: 110 page visits → 22 CTA clicks (20%) → 18 sign-ups (16.36%) Outcome: Proven exceeded the interest threshold by 2x, confirming real curiosity and intent.

2. Vision Video — Motivation Hypothesis: If shown JumpSquad's gamification system, ≥70% of viewers will say it makes them feel motivated to keep using the app. Method: Created a 45-second Figma-based demo video showing challenge completion, badge unlock animation, streak tracking, and the leaderboard. Shown to 5 participants in person and online. Result: 3 of 5 (60%) watched the full video without skipping; badges and leaderboards were named the most motivating features. Outcome: Partially proven the motivational pull is real, but fell short of the 70% threshold, signaling that gamification alone needs more variety/depth to fully convince skeptical users.

3. Mechanical Turk — Real-Time Experience Hypothesis: If users experience a simulated real-time leaderboard during a live challenge, ≥80% will describe it as fast, responsive, and motivating. Method: Hosted a live session where participants performed real jumping jacks while I manually fed data into a mocked leaderboard interface in real time. Result: 4 of 5 (80%) described the experience as "fast and motivating"; 3 of 5 said they felt competitive and excited instantly. Outcome: Proven met the responsiveness threshold exactly, with competitiveness emerging as a strong secondary driver.

What the Data Changed

• Confirmed the core concept had real pull (2x over threshold), worth building

• Surfaced that gamification needed more reward variety (streaks vs. coins vs. unlockable challenges) to move past a "nice to have" into a genuine retention driver

• Validated that live, responsive feedback was a bigger emotional hook than expected, and prioritized snappy real-time UI states in the final design

From Validation to Structure

With the concept validated, I mapped the full product:

• User flow — from landing → dashboard → workout → completion → reward → leaderboard → social share, including the returning-user path and the 7-day-streak reward branch

• Sitemap — six core destinations: Home, Workout, Progress Tracking, Challenge Tracking, Leaderboard, Profile, plus a dedicated Reward layer

• Low-fidelity wireframes — 19 annotated screens across Onboarding & Dashboard, Workout & Rewards, Leaderboard & Community, Profile, Settings, and Extras (wearable connection, live workout screen)

Deliver

Visual Direction

The final UI leans into the "energy" pole of the brand exploration, with high-contrast black backgrounds, a signature lime-yellow accent, bold, condensed type, and circular progress rings that make the live jump counter feel lively rather than clinical.

Key Features

• Real-time jump tracking with a live counter and progress ring

• Daily challenges with streak tracking and milestone badges

• Leaderboard with global and squad-based rankings

• Community feed for sharing wins and encouragement

• Customizable challenges (set your own jump target)

• Wearable device sync and offline-friendly workout mode

• Profile & activity dashboard (weekly/monthly/yearly views)

Final Screens

Business Model Snapshot

To ground the design in a viable business, I built out a full Business Model Canvas:

• Value proposition: A retention-first model that converts short-term motivation into recurring engagement, positioned as a differentiated player in gamified fitness.

• Revenue streams: Freemium tiers (exclusive challenges, badges, advanced analytics), sponsored content/brand partnerships, and subscription revenue from retained users.

• Customer segments: Primary: digital fitness enthusiasts (18–35); Secondary: casual users drawn to gamified competition; Emerging: corporate wellness programs.

• Key partners: Fitness influencers for credibility and acquisition, wearable device integrations, and co-marketing with health/fitness brands.

Measuring Success

I defined three growth objectives to track post-launch:

1. Engagement metrics — session time, challenges completed, reward adoption, feeding a retention/LTV dashboard

2. Product reliability — usability testing to reduce churn-causing friction, a shared design system to lower future dev cost

3. Market traction — influencer partnerships, cost-per-install tracking, freemium conversion funnel

Result

• 2x the target sign-up rate in the Fake Door Test (16.36% vs. a 10% threshold)

• 80% of users in live simulation described the real-time experience as fast and motivating, validating the core interaction before full build

• Identified a genuine market gap (gamification + community + no hardware dependency) that competitors hadn't filled

• Shipped a scoped, MVP-disciplined feature set (MoSCoW) instead of an over-built first release

Reflection / What's Next

The Vision Video result (60% vs. a 70% target) was the most useful "failure" in the project. It told me gamification alone isn't a silver bullet, and pointed directly at next steps: testing reward variety (streaks vs. coins vs. unlockable challenges) and building an interactive prototype to measure motivation beyond passive video-watching. Future testing also includes higher-load simulations (50–100 concurrent users) and comparisons of competitive vs. cooperative leaderboard framing across different user types.