FIGMA WORK

Workout Intensity Settings

Katalyst · 2025~3 monthsLead Product Designer
Role
Lead Product Designer
Scope
UX strategy, interaction design, user research
Tools
Figma, Miro, Mixpanel, Typeform
Timeline
~3 months
Team
Product Manager, Frontend Engineer, Backend Engineer, Creative Director

I created a pre-workout setup and an in-workout adjustment system that gave users predictable, safe, and personalized intensity control during at-home EMS training. The solution reduced discomfort, improved trust, and kept trainer-programmed workouts flowing without disruption.

Workout Intensity Settings
01

Problem & context

Katalyst’s EMS training sessions rely on electrical impulses tailored to each user. At home, without an EMS technician present, users had limited control over intensity progression, and trainer-programmed changes could feel abrupt or unpredictable, leading to anxiety, skipped adjustments, and reduced confidence.

Users expressed uncertainty around safety and comfort at higher intensities, which we validated through post-workout surveys and interviews. The goal was to empower users to train independently while preserving the flow of trainer-designed workouts.

02

The challenge

How might we make home EMS workouts safer and more personalized without breaking workout flow?

03

My responsibilities

I led the end-to-end UX process, including:

Leading UX strategy and design for pre-workout and in-workout control experiences
Turning user and trainer feedback into actionable design requirements
Collaborating with engineering to stay within firmware limits
Validating designs through usability testing with active members
Workout Intensity Settings, My responsibilities
04

Research & insights

Workout Intensity Settings, Research & insights

I combined:

Usage analytics to understand when and how often users adjusted intensities
User interviews & surveys on recorded-workout pain points
Trainer interviews to understand how intensity profiles are programmed
A/B testing on intensity profiles to measure perceived safety and usability
Usability testing with different profile configurations

Key insights:

Mixpanel data showed that 43% of sessions included mid-workout adjustments, mostly in Strength and Power workouts. Intensity increases clustered early and intensity decreases clustered late.
Interviews showed users adjusted early to gauge how they felt and adjusted late when workouts became harder than expected. Many unfollowed trainer-led increases when ramps felt abrupt.
Usability tests confirmed the need for smoother intensity changes and clearer expectations before starting.
Overall takeaway: users needed predictability, transparency, and control before the workout began.
05

Strategy & prioritization

We focused on two high-impact opportunities:

Choose Before You Train: Let users select their preferred intensity progression before starting, reducing disruptive mid-workout changes.
Smooth & Visible Changes: Show upcoming intensity adjustments and apply them gradually for predictability and safety.

Constraints:

Built fully within existing firmware. Launched in 3 months without costly hardware changes.

Workout Intensity Settings, Strategy & prioritization
06

Design solutions

1. Pre-Workout Intensity Profiles

Added a step to choose one of three profiles: Standard, Early Ramp-Up, Late Boost
Added Easy Mode and Hard Mode for single-session end-intensity tweaks without changing the default user profile
Reduced need for manual mid-session changes
Workout Intensity Settings, Design solutions
Workout Intensity Settings, Design solutions
Workout Intensity Settings, Design solutions
Workout Intensity Settings, Design solutions

2. Smooth Intensity Ramp-Up

Displayed target intensity next to the current value when an adjustment occurred (either by the trainer or the user)
Applied changes over the next 4-second impulse instead of instantly, creating a smoother, safer shift
Workout Intensity Settings, Design solutions
07

Results & impact

28% decrease in mid-workout adjustments
85% positive feedback on smoother, more predictable changes
Qualitative feedback: users felt “in control” and “safer”
Supported retention goals by boosting trust in solo training, a key driver for long-term subscriptions
Increased user confidence, reduced drop-offs, and improved adoption of customized intensity settings
08

Collaboration

Engineering: Designed logic for gradual adjustments within firmware limits
Creative Director: Ensured visuals aligned with Katalyst’s premium, approachable brand
Trainers: Defined optimal progression patterns for different workout types
09

Reflection

Control equals confidence, and in at-home EMS training, confidence drives consistency. By giving users transparent, safe, and customizable control, we strengthened trust in solo sessions and positioned Katalyst as a professional-grade home training platform, critical for scaling beyond studios and sustaining subscription growth.

If extended, I’d explore adaptive intensity algorithms that auto-adjust using heart rate and performance data.