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 face ongoing challenges due to inconsistent sizing standards across different brands, which often results in confusion during the selection process. This lack of uniformity contributes significantly to high return rates, as customers frequently receive items that do not fit as expected. Over time, these negative experiences can erode trust and reduce overall confidence in the online shopping experience, ultimately impacting customer satisfaction and brand loyalty.
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.
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.
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.
Designed a gamified rewards system to boost user engagement by analyzing competitors and user behavior. Developed configurable reward types and rules (e.g., timing, frequency), built probability-based logic to ensure fairness, and crafted an intuitive scratch-and-win UI. Ensured seamless cross-platform functionality and collaborated with backend teams to integrate Magento for coupon validation, with thorough testing across regions and 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.
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.
If you like what you see and want to work together, get in touch!
merveozgealadag00@gmail.com
