Stride: A smarter, more flexible running app

Case Study

My role: Product Designer

Led end-to-end product design from research and ideation through high-fidelity execution.

Timeline: 12 weeks

Background

Most running apps offer one-size-fits-all training plans focused on distance and pace goals. These plans are often rigid, requiring unrealistic time commitments, and rarely adapt to the user’s life or fitness changes. As a result, runners burn out, get injured, or fall behind—especially when recovery and cross-training are ignored.

Opportunity

Stride aims to solve this problem by providing personalized and dynamic training plans that adjust based on real-time data, such as performance feedback and schedule changes. It incorporates cross-training, rest, and recovery strategies, creating a more holistic and sustainable approach to race preparation and injury prevention.

Target Audience

Stride serves amateur and intermediate runners, who are training for various race distances (e.g. 5k, 10k, half-marathons, etc.)

Key segments include: 

  • Injury-prone runners looking for a smarter, safer way to train without overloading mileage,

  • Goal-oriented athletes training for a specific race, who want guidance without micromanagement

  • Fitness-focused users seeking balance through cross-training and better recovery, not just running

Impact

Stride aims to redefine how runners approach training by offering a more adaptive, human-centered experience. The potential impact includes:

  • Reduced injury rates due to better emphasis on rest, cross-training, and recovery

  • Improved consistency by adjusting to life’s unpredictability, helping users stay on track even when plans change

  • Increased confidence through clear, guided onboarding and progress tracking

  • More inclusive training that supports different experience levels, body types, and schedules

By meeting runners where they are—not where a rigid training plan expects them to be—Stride empowers users to train smarter, stay healthier, and build a lifelong relationship with running.

Research Approach

Competitive Research

I conducted a SWOT analysis of the leading running apps to understand where Stride could differentiate itself:

  • Runna: Personalized plans with strength and nutrition guidance, but lacks real-time adaptability and focus on recovery.

  • RunCoach: Offers personalized coaching, but its outdated interface and static plans limit user engagement.

  • Nike Run Club: Popular among beginners but lacks depth and flexibility, and doesn't cater to more experienced runners.

  • Garmin Connect: Provides in-depth analytics for experienced users but is complex and lacks coaching features

The opportunity lies in creating an app that not only prepares runners of all levels for races but also educates them on the importance of cross-training, rest, and recovery—elements critical for long-term performance and injury prevention.

Findings

Across all platforms, there’s a gap for a flexible, dynamic running plan that automatically updates plans based on real-life schedule changes or performance data.

  • All apps offer valuable tools for runners, but fall short in key areas that present a strong market opportunity.

    Runna leads with its sleek design, personalized plans, and added strength and nutrition components, yet lacks real-time adaptability and deeper recovery focus.

    Runcoach offers personal coaching and goal-specific plans, but its outdated interface and static structure limit user engagement.

    Nike Training Plan appeals to beginners with its free, accessible programs, though it lacks depth, adaptability, and holistic training elements.

    Garmin Connect delivers advanced analytics for experienced users, but its complexity, lack of coaching support, and rigid plans make it less appealing to a broader audience.

User Interviews

To ensure user needs aligned with gaps identified in the market, I interviewed four runners—active individuals in their mid-20s to early 30s, all living in major cities and familiar with structured training plans.

These conversations revealed deeper frustrations with existing tools, particularly around inflexible plans, burnout, and a lack of support for injury prevention.

Through affinity mapping, several key themes emerged:

  • Simplicity over complexity: Users preferred clear, straightforward guidance over input-heavy systems

  • Desire for holistic training: There was strong interest in incorporating cross-training, rest, and stretching

  • Injury concerns: All participants had experienced or worried about injuries caused by rigid, run-heavy programs

POV & HMW

These insights shaped my POV and How Might We (HMW) statements, which informed the development of user personas—frustrated runners in search of smarter, safer, and more adaptable training support.

Help runners training for long distances find a balance between structure and flexibility, allowing room for rest during tough weeks

This problem is particularly relevant to marathoners and long-distance runners who need structure but also benefit from flexibility. By solving this, the app could offer a unique value proposition that resonates with a broad and committed audience segment.

Encouraging runners to prioritize injury prevention during training.

This POV ties into a more holistic and sustainable approach to running that could differentiate the app by supporting longevity and well-being—not just performance. It's especially relevant for newer runners who might not yet understand how crucial recovery is.

Design Solutions

I followed an iterative design process—starting with user personas and prioritizing features based on research insights. This informed a site map, user flows, and task flows, which I translated into low-fidelity wireframes. 

User Personas

 I created personas based on my research, such as Caroline, a 24-year-old runner training for her second half-marathon. She has a busy lifestyle and often misses workouts. She needs a flexible plan that fits her schedule and incorporates strength and recovery exercises.

Key needs identified:

  • Flexible, adaptive plans

  • Clear instructions and expectations

  • Integration of cross-training and rest

  • Prevention-focused training approach

Feature Prioritization

I prioritized features based on impact and feasibility. I then developed a site map using the results of a card-sorting exercise. For card-sorting, I had 4 different users than the ones interviewed who all had experience using running apps. The site map reflected the common groupings, and was organized by core app functions, such as onboarding, training plan customization, and progress tracking.

Site Map & User Flows

This led to clearly defined user and task flows. These flows focused on onboarding and selecting a dynamic training plan.

Branding

During the branding phase, I developed a visual identity that balanced energy with support—motivating yet approachable. This included logo exploration, defining brand values, and creating a mood board to establish visual direction.

The color palette featured deep, muted blues to convey clarity and focus.

Expressive typography and generous white space were used to elevate aesthetics while maintaining usability.

Wireframes to Prototypes

I tested early concepts to validate the overall structure and flow before moving on to mid- and high-fidelity prototypes.

Low-Fidelity

  • Mapped onboarding and training plan selection

  • Focused on clarity, minimal steps, and user confidence

Mid to High-Fidelity

  • Refined the visual language, incorporated branding

  • Streamlined flow based on initial testing insights

Usability Testing & Iteration

With my final interactive prototype, I conducted usability testing. Five users provided feedback on how intuitive the onboarding and training plan were.

During testing, I discovered that some of my original assumptions—such as users needing to manually navigate to the training plan section—were outdated due to changes made in the final flow. Instead, users were automatically guided into that experience post sign-up, which required me to adjust my success metrics and interpretation of results. 

Based on feedback, I made several targeted improvements (see one example below).

These changes were all driven directly by usability testing insights and helped shape a more polished, user-centered final product.

Before

Reorganized the question flow based on user feedback indicating that the previous order was confusing. The revised order begins by asking whether the user is training for a race, allowing for a more intuitive branching experience:

  • If 'Yes' → the user is prompted to specify the race distance, etc.

  • If 'No' → the user is asked to define their goal (e.g., distance, pace, or general health)."

Additionally, adjusted spacing to reduce frame height and minimize unnecessary vertical scrolling. Introduced contextual messaging after the user inputs their race date, explaining how the recommended training plans are tailored based on the time remaining until race day.

After

Reflection & Results

This project gave me a deep understanding of how important flexibility and adaptability are—not just in the product I was designing, but in the design process itself. One of the biggest challenges I faced was that some testing insights became misaligned with success metrics as the prototype evolved. However, this taught me to be more agile and to continuously reevaluate assumptions as the design matured.

Through user research, iterative design, and usability testing, I created a product that encourages runners to train smarter, stay healthier, and show up on race day confident and injury-free.