Adoption · UX

A start button that knows your machine

Quick Start let people connect a machine and track a workout, but adoption was slowly sliding. I rebuilt it around three ways to start, a live screen that fits the machine, and a summary worth sharing.

Company
Sportstech
Role
Product Manager
Timeline
2025–26
Team
Design, Engineering, Data Science
North-star
Feature adoption

At a glance

01 Problem

Quick Start adoption was gradually declining. It tracked data but helped nobody achieve anything, and looked the same on every machine.

02 Insight

People didn't need more numbers. They needed the right ones for their machine, and something to aim them at.

03 Solution

Three entry modes (Quick, Target, Goal), machine-aware live screens, and a summary with personal bests, streaks and one-tap sharing.

04 Result

22% → 32% of MAU (+45%), 3 months before vs 3 after. Workout-entry drop-offs −22%.

You're in the 30-second version. The full story covers the research, measurement design and guardrails.
01 Context

Quick Start was simple. Usage was quietly sliding.

The original idea was simple: connect your fitness machine, hit a button, and the app tracks your workout in real time.

When I looked at the usage data, adoption was gradually declining. Nothing was broken. The feature just wasn't giving anyone a reason to choose it.

02 Problem

It tracked everything and helped with nothing.

Too generic

It tracked data but didn't help anyone achieve anything. No goals, no milestones, no sense of progress.

Identical across machines

A treadmill runner and someone on a strength machine saw near-identical metrics, though their workouts have little in common.

Connected machine
Before · one screen for everything
Treadmill12:40
Same four tiles
After · built for the machine
Treadmill12:40
Fig. 01Switch the machine and watch which screen notices. The old screen asked a strength user to look at distance and speed. Recreated for illustration.
03 Insight

A start button isn't a reason to start.

“People didn't need more numbers. They needed the right ones, and something to aim them at.”
— Synthesis from user conversations and my own sessions

Two needs kept coming up. People wanted to know whether a workout was any good, which means a target, a goal or a personal best to compare against. And the numbers only meant something if they matched the machine: a runner cares about pace and incline; a strength user cares about sets and intensity.

04 Solution

Three ways in, a screen that fits the machine, and a summary worth sharing.

Three entry modes

Quick: just start. Target: calories, distance, duration or step count. Goal: work toward something longer.

Machine-aware live screen

Treadmill: pace, distance, cadence, incline. Strength: duration, sets completed, estimated calories, intensity.

A summary that celebrates

Personal bests, goal achievement, longest streak, pace improvement, calorie equivalents, milestones. One tap to WhatsApp or Instagram Stories.

Mode
Machine
Screen

Pick how you want to train

Quick is still one tap. Target and Goal are there for people who want a finish line.

Fig. 02The revamped flow. Change mode and machine, then step through start, live and summary. Every screen changes with the machine; the summary changes with the mode. Mock-up; values are illustrative.
05 Measurement

Three months on each side, because one month can lie.

Metric definitionQuick Start adoption
Definition
% of monthly active users who started at least one workout through Quick Start in a given month.
Cohort
Monthly active users.
Window
A calendar month: did this user start at least one Quick Start session in it?
Comparison
3 months before the revamp vs 3 months after, tracked monthly.

Why three monthsA single month can be distorted by seasonality, a marketing push or a holiday. Three months on each side smoothed that out and gave us a trend we could trust.

Revamp avg 22% avg 32%

Fig. 03The single-month trap. Illustrative monthly shape · only the 3-month averages (22%, 32%) are measured.
06 Results

More people pressed start, and fewer bailed on the way in.

32%of MAU used Quick Start, up from 22%
+45%Relative lift in adoption, 3 months before vs 3 after
−22%Drop-offs at workout entry
07 Guardrails

What could a richer Quick Start have broken?

Result · drop-offs −22%

Choice can't cost a tap

Three modes add a decision, which could have made starting slower. Entry drop-offs fell 22% instead, and Quick still just starts.

Built into the metric

Share of MAU, not raw starts

A user-growth spurt or a campaign can inflate raw session counts. Measuring the share of monthly actives keeps the number about the feature.

Built into the metric

No single-month wins

Three months on each side, so a holiday or a marketing push can't manufacture the result, or hide it.

08 What I learned

When adoption slides, the feature usually still works. It has just stopped being worth choosing. Fit it to the person and the machine, and give them something to show for it.

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