1. Improved Visual Hierarchy with Modular Card-Based Layout

Before

After

• Design Rationale:
  As the account center content increased, users found it difficult to quickly grasp their account status. Thus, I introduced a modular card-based layout to organize subscription details, promotional content, and action items into clearly separated visual zones. This helped guide user attention, reduced cognitive load, and laid the foundation for scalable component-based design in the future.
  I benchmarked against platforms like Netflix and Adobe, where card-based dashboards improved clarity and task completion.
• Hypothesis:
  By restructuring content into visually distinct cards, users will be able to quickly identify key information—such as current subscriptions, payment deadlines, and available promotions—leading to improved task efficiency and reduced confusion.

• Trade-off:
  ‍I considered using a more minimalist list view to save space, but it lacked the visual cues needed to distinguish different types of content. The card-based layout takes up more vertical space, but it significantly improves scanability and user orientation, especially for mobile-first users.

• Validation:
  

• Usability Testing:
  We can run task-based tests comparing the old list view and new card layout.
• GA Metrics:
  We can track drop-off rate, average time-on-task, and tap-through rates (e.g., “renew”, “upgrade”) to measure post-launch performance.

2. Making Benefits and Rewards Discoverable Through Visible Incentive Modules

Before

After

• Design Rationale:
  ‍The original Member Center had fragmented information and lacked engagement. Users often ignored it unless something went wrong. To address this, I redesigned it as a modular, campaign-driven dashboard with dynamic content such as news, referral tasks, mascot banners, and time-limited offers. This approach proactively communicates brand value, increases user trust, and promotes return visits.
  
  Engineering confirmed implementation feasibility with backend support for content modules. I benchmarked against platforms like Notion, Shopee, and Adobe, which use dashboard-style centers for engagement.
• Hypothesis:
  A modular interface with gamified and branded elements will increase user engagement and conversions. Features like third-party news enhance credibility, while referral progress bars and time-limited promotions drive action through urgency and goal completion psychology.
• Trade-off:
  ‍This approach introduced more frontend and backend complexity to handle dynamic states, data fallbacks (e.g., cold start), and configuration logic. Compared to a static UI, it required more engineering effort but offered significantly higher potential for retention and marketing impact.
• Validation:
  

• Analytics Tracking (e.g., GA): Monitor key metrics such as:

• Tap-through rates on referral tasks and banners
• Coupon redemption rates
• Return visit frequency to the Member Center

3. Dynamic Personalization Based on Membership Tier and Behavior

Before

After

Progressive Disclosure – Delayed Optional Questions to Reduce Friction

• Design Rationale:
  To minimize drop-off during sign-up, I chose to delay non-essential questions—such as “How did you hear about us?”—until after users completed an initial key action. Early friction often drives abandonment, especially when users are still evaluating trust. By deferring optional prompts and making them lightweight and skippable, I respected user focus and followed NN/g’s best practice:
  “Minimize fields and only ask what’s necessary at the start.”
  
  ‍I referenced successful patterns from Duolingo, Notion, Figma, and Superhuman, which all use progressive disclosure to reduce initial friction.Implementation included:

• One-click login with auto-fill support
• Skippable, contextual prompt cards triggered after meaningful actions (e.g., posting the first job or browsing personalized results)
  We can measure impact through sign-up completion rate, first 7-day engagement, and optional data submission rate.

• Hypothesis:
  ‍Delaying non-critical questions until after initial engagement would:

• Increase sign-up completion rates
• Reduce early bounce
• Maintain marketing data quality without compromising UX

• Trade-off:
  We deprioritized collecting marketing insights at the point of registration in favor of optimizing the first-time user experience.
  Compared to showing all questions upfront, progressive disclosure may delay access to data for internal teams but ultimately improves user activation and long-term engagement.
• Validation:
  

• A/B Testing:
  Compare sign-up completion rates and bounce rates between users shown the optional questions upfront vs. those who see them after the first engagement.
• GA :
  ‍Monitor engagement within the delayed prompts—such as response rates, skip behavior, and time spent—to ensure that optional data collection still performs without degrading UX.

4. Driving Engagement Through Referral Progress Bars and Limited-Time Offers

4.1. Reducing Churn While Respecting User Autonomy

• Design Rationale:
  ‍While we respect a user’s right to cancel their subscription, offering an instant, one-click cancellation can lead to impulsive churn—especially when driven by temporary emotions or misunderstandings. Instead, we designed a short, thoughtful exit flow that:

• Reminds users what they’re losing
• Offers alternative options (pause, discount, etc.)
• Collects feedback to improve the product

This moment of reflection helps users make more informed decisions, reduces avoidable churn, and generates qualitative data without feeling aggressive or manipulative.

I benchmarked platforms like Spotify, Netflix, and Duolingo, all of which use multi-step cancellation flows with soft, respectful nudges.

Our final implementation included:

• Step 1 – Reminder of Lost Benefits:
  You’ll lose access to premium features like advanced filters and saved preferences.
• Step 2 – Retention Offers:
  Options to pause subscription, extend trial, or accept a one-time discount
• Step 3 – Feedback Collection + Final Cancel Button:
  ‍Quick form to understand cancellation reasons (e.g., pricing, value, features)

• Hypothesis:
  ‍A structured, empathetic multi-step cancellation flow would:

• Reduce impulsive unsubscriptions
• Increase retention via alternative offers
• Generate actionable insights through user exit feedback

• Trade-off:
  ‍A one-click cancel button is fast and user-friendly, but lacks the opportunity to learn why users churn or attempt recovery.
  Our chosen approach added slight friction to the process, which risks frustrating users if not handled delicately. I addressed this by keeping the flow short, clearly worded, and easy to exit at any time.

• Validation:

• Churn rate comparison (before/after implementation)
• Offer acceptance rate
• Completion vs. abandonment rate in the flow
• Quality of feedback collected

4.2. Adding a Progress Bar to Marketing Pages to Boost Completion

• Design Rationale:
  ‍On marketing pages, users often drop off mid-way through multi-step interactions. To address this, I introduced a visual progress bar based on behavioral psychology principles like the goal-gradient effect and sunk cost effect. When users see they've already completed more than 50%, they feel motivated to finish. Real-time visual feedback also reduces uncertainty and makes the process feel more manageable.
  
  Referenced:
  ‍Behavioral psychology studies on the goal-gradient and sunk cost effects
  ‍UX research from Nielsen Norman Group on progress indicators and real-time feedback
  ‍Industry benchmarks from Duolingo, Typeform, and Mailchimp, which use similar patterns in their onboarding and marketing flows
• Hypothesis:
  ‍I believed that implementing a visual progress indicator would:

• Increase form or flow completion rates
• Reduce abandonment in multi-step tasks
• Enhance user confidence by providing a clear sense of progression

• Trade-off:
  ‍Compared to a short, single-step form, a multi-step structure with a progress bar requires additional front-end complexity and logic. It also introduces the need for reward triggers and state handling. However, we prioritized psychological reinforcement and perceived progress over implementation simplicity to drive higher user engagement and conversions.
• Validation:
  We can validate through metrics such as completion rate, drop-off points, and reward redemption rate.