Helping members start a workout without getting lost in choice.
UX/UI
Fitness
Too much choice before the workout.
Interview feedback described an overwhelming home screen and difficulty choosing a workout. Members had to compare content before they could get moving. I focused the redesign on a clearer starting point, with enough information to choose confidently.
80%
of completed workouts were already Daily Sessions before the redesign. This was the starting signal, not an uplift attributed to the new design.
The design question: how could home reflect what people already used, while keeping enough choice for different needs?
01 / Put the next workout first. I gave Today’s Plan Session priority so members could start with a recommendation instead of comparing the whole catalogue.
02 / Make suitability easy to judge. I placed duration, equipment and difficulty beside the session so members could decide whether it worked for them before opening it.
03 / Offer a way out, not a dead end. Start workout leads the card; swapping stays available when the recommendation does not fit the member’s day.
Reconstructed wireframes explaining the design rationale, created for this case study.
Browse-led home
Trainers
Collections
Programmes
Workouts
Recommendation first
Recommended session
Start workout
Choice before commitment
Recommended + alternative
Start workout
What I would test next
Can someone identify today’s recommendation, judge whether it suits them and find an alternative without help?
Usability checks: observe first action, task completion, hesitation and comprehension. These are evaluation questions, not reported test results.
One journey, with a meaningful choice.
The journey follows the member’s decision: what should I do, does it suit me, and how do I start? If the answer is no, swapping offers another route without restarting the search.
Open home
01
Find the recommended session.
Review
02
Understand the workout context.
Choose
03
Start or select an alternative.
Move
04
Enter the workout experience.
Journey summary reconstructed for this portfolio from the design direction; not presented as an original research artifact.
Home helps members decide what to do now. The library supports deliberate browsing by programme, category or training need. Separating those jobs keeps the daily route focused without taking choice away.
Turn the problem into design criteria
Use the existing behaviour
Daily Sessions already accounted for 80% of completed workouts. I used that baseline to prioritise the daily recommendation on home, while keeping the wider catalogue accessible.
Connect behaviour with the reported difficulty
Interview feedback pointed to an overwhelming home screen and difficulty choosing a workout. The design challenge was to reduce the effort between opening the app and deciding what to do.
Define the member’s next step
The member’s immediate job: recognise today’s recommendation, check that it fits their time and equipment, then start or choose an alternative. This sequence became the basis of the hierarchy.
Decide what must be visible
Three questions guided the layout: what must be visible before opening a session, how much context is enough, and how can swapping remain easy without competing with Start workout?
Three routes into a workout
1. Browse the library
A catalogue-led home makes the range visible. It works for someone who wants to explore, but still asks a member to compare options before they can exercise. This route prioritises discovery over getting started.
2. Follow a single recommendation
One prominent workout creates a clear starting point. But if the session does not fit today’s time, equipment or preference, that simplicity becomes a dead end. A useful default needs a visible alternative.
3. Recommend, explain, let me swap
The chosen direction keeps Today’s Plan Session prominent and puts duration, equipment and difficulty beside it. Members can judge suitability in the same place they decide whether to start. Swapping provides an alternative without restarting the search.
Make the hierarchy match the decision
Start workout is the main action. Swap remains easy to find but secondary. The screen gives a recommendation without taking control away from the member. The recreated wireframes show this structural trade-off; the final screen shows how it becomes an interface.
Delivery and the next learning loop
Work within a focused delivery window
The work developed over three weeks and three sprints within a four-person design team. The feature was in development in September 2024. The focus was the daily-session entry point: the home hierarchy, suitability information and the choice to start or swap.
Keep home and discovery complementary
Home provides the useful default; the library supports deliberate exploration. Giving these surfaces different jobs keeps the daily route focused while preserving the breadth of the product.
Evaluate the decision sequence
A proposed usability check: find today’s recommendation, explain whether it suits you, then start or swap. Observe hesitation, backtracking and whether the alternative is understood. These tasks test the design’s central decisions rather than asking whether the screen looks good.
Connect learning to future iteration
After release, I would review recommendation-to-start behaviour, swap usage and abandonment alongside member feedback. Frequent swaps could indicate a mismatch in recommendations; hesitation could indicate unclear information. Those are different problems and should lead to different iterations. Post-launch results are not claimed here.
What the design changed
The work was developed over three weeks and three sprints, within a four-person design team. The feature was in development in September 2024.
The design replaced an open-ended first decision with a guided one: a recommended session, the context to assess it, and a clear start or swap action. This addressed the choice problem directly while preserving access to the wider library.
What I would evaluate next
Can people identify the recommended session, judge whether it suits them and start or swap without hesitation? I would pair task observation with recommendation-to-start behaviour, keeping user context and cohort differences visible.
The design was in development in September 2024. Post-launch performance is not included in this case study.