The goal is to aim provide user-centric and efficient solutions;
Increase User Engagement: Introduce an exciting and interactive way for customers to interact with the app.
Boost Conversion Rates: Encourage purchases by offering rewards and discounts tied to specific conditions.
Ensure Scalability: Build a system flexible enough to adapt to varying country-wise rules, promotional strategies, and reward types.
Research & Planning: Identified gamification as a motivator for increased user interaction.
Competitor Analysis: Studied similar features in e-commerce apps to design a unique yet effective system.
Feature Design & Rules Configuration:Reward types (instant credits, cashback, free items).Validity rules (hourly or midnight).Frequency (daily or multi-day offers).
Logic Development: Designed probability-based logic for fair chances to win while maintaining user excitement.
User Interface & Experience: Created an intuitive and satisfying user interaction for scratching and revealing rewards.
Offer-Based Customization: Tailored "Congratulations" screens to align with different offers and rewards.
Cross-Platform Functionality: Ensured rewards could be redeemed seamlessly across app and PWA.
Implementation & TestingCollaborated with backend teams to integrate Magento system for coupon validation and data management.Thoroughly tested configurations to handle various country-wise rules and reward expiry scenarios.
The Scratch and Win feature provided users with a fun, engaging, and rewarding shopping experience, transforming the typical e-commerce journey into an interactive activity. By offering instant rewards such as discounts, cashback, and free items, it incentivized purchases while fostering excitement and anticipation. Users appreciated the transparency and fairness of the feature, with customizable rules ensuring equal opportunities for everyone. The seamless integration across platforms (app and PWA) allowed users to redeem rewards effortlessly, enhancing convenience and satisfaction. Ultimately, this gamified experience not only made shopping more enjoyable but also created a sense of value and exclusivity, encouraging repeat visits and loyalty to the platform.
Diverse Rules Across Countries:Challenge: Adapting terms and conditions for multiple regions.
Solution: Built a scalable backend to handle country-wise customizations dynamically.
Reward Expiry Management:Challenge: Balancing reward validity for user convenience and business goals.
Solution: Supported both hourly and midnight expiration logic.
Cancellation Handling:Challenge: Managing rewards and coupons for canceled orders.
Solution: Ensured users could reuse rewards if validity conditions still applied.
Success Metrics: The scratch-and-win feature’s performance was analyzed over a two-week period, focusing on:
Total customers who participation.
Number of coupons used
Number of coupons expired
Conversion rate (% of customers who redeemed coupons).
User Engagement: Achieved over 20,000 players within the first phase of deployment, demonstrating high user interest in gamified features.
Conversion Rate Impact The feature led to a future campaigns, ensuring offers align with user preferences and shopping behaviors.The system's flexible configuration (hourly, daily, or event-based) provides scalability, enabling it to adapt to various campaigns and regions.
Retention Metrics: The number of coupons used (redeemed) varied, with daily usage peaking at 1,040 coupons on.
Conversion rates ranged from 2.08% (November 15th) to a high of 6.92% (November 28th).The gradual increase in conversion rates over time shows improving user understanding and effectiveness of the feature.
A/B Test Results:
Users who interacted with the Scratch and Win feature showed 20% higher session durations compared to non-participants.
Redemption of rewards and static coupons contributed to a significant uplift in repeat purchases, confirming the feature's role in driving customer loyalty.
The customized reward structure (e.g., instant credits, static coupons) resulted in a 30% increase in reward utilization rates, further validating its user-centric design.
Long-Term Value:
The Scratch and Win feature has the potential to drive sustained value by continuously engaging users through daily reward opportunities, increasing long-term retention and loyalty.
Gamified interactions improve brand perception, creating a fun and memorable shopping experience that fosters emotional connections with the platform.
6thStreet is a leading eCommerce platform offering a diverse range of fashion brands. One of the primary challenges in online shopping is ensuring customers select the right size, as sizing standards vary across brands. To address this, I developed an AI-powered feature called "Can't Find Your Size?" that guides users in selecting their optimal fit based on personalized inputs.
Many users struggle with size discrepancies among different brands, leading to high return rates and decreased customer confidence in online shopping. Our goal was to:
Reduce sizing-related returns
Improve customer satisfaction and trust
Increase conversion rates by providing personalized size recommendation
This feature provides users with personalized size recommendations by leveraging an intelligent algorithm that considers brand-specific size variations. Users enter their height, weight, and age, and the system predicts the best size for them based on brand-specific sizing patterns.
User Research & Insights:
Conducted in-depth interviews and analyzed user feedback to understand sizing challenges.Reviewed customer complaints and return reasons to identify the root causes of sizing confusion.Identified key pain points: inconsistent brand sizing, lack of confidence in size selection, and frustration with returns.
Algorithm & Data Model Design:
Developed a machine learning model that maps user inputs to brand-specific sizing charts.Integrated historical data on customer purchases and returns to refine size predictions.Ensured adaptability by continuously improving recommendations based on user feedback and purchase behavior.Incorporated weight fluctuations and body type variations to enhance prediction accuracy.
UI/UX Design & User Flow:
Designed an intuitive, user-friendly interface for seamless interaction.Ensured clear call-to-action buttons and simple input fields for frictionless user engagement.Provided instant, visually engaging feedback with dynamic size recommendations.Incorporated educational tooltips explaining how the AI model works to increase user trust.Optimized the feature for both mobile and tablet interfaces to align with the 6thStreet shopping experience.
User Acceptance Testing (UAT):
Conducted UAT with a select group of real users to validate the functionality and usability of the feature.Collected feedback on the accuracy of size recommendations and ease of use.Identified and fixed last-minute issues before the full rollout.Ensured the feature met business requirements and delivered a seamless experience across different devices.
Implementation & Testing:
Collaborated with developers to integrate the feature into the 6thStreet app seamlessly.Conducted multiple rounds of A/B testing to measure effectiveness and user engagement.Gathered and analyzed user feedback post-launch to make iterative improvements.Ensured accessibility compliance for a wider range of users.
25% reduction in size-related return rates, decreasing logistical and operational costs.18% increase in conversion rates for users engaging with the feature.
30% higher customer confidence in size selection (measured via post-purchase surveys).
40% of users who struggled with sizing used the feature to make a purchase decision.
User engagement with the feature increased by 50% in the first three months after launch.
Positive feedback from users in qualitative surveys highlighted the ease and effectiveness of the feature.
Future Enhancements & Next Steps
Expansion to more data points: Incorporate additional user inputs such as body shape and fit preference (loose, regular, or tight fit).Enhanced AI learning: Improve machine learning models by integrating AI-driven feedback loops from return reasons.Multi-language support: Provide multilingual assistance to improve accessibility for diverse user bases.Integration with AR sizing technology: Explore the potential of augmented reality (AR) for an even more personalized shopping experience.
If you like what you see and want to work together, get in touch!
merveozgealadag00@gmail.com.svg){kind=small}
