AI
enhancing user engagement with personalization
Key Results
Project
Client
Industry
Duration
Supported Platforms
RetailX aimed to boost conversion and engagement by implementing AI-driven personalization into their e-commerce platform. The system dynamically adapts content, product listings, and recommendations in real-time for each visitor, based on behavioral data and preferences.
Whether near or far, we're here to support your journey every step of the way.
Products are automatically reordered per user interest and browsing history, improving the likelihood of conversion.
AI models group users into behavioral segments and personalize homepage content and call-to-actions accordingly.
Search results adapt to user context and preferences, offering a smoother, more effective product discovery experience.
The admin dashboard provides real-time analytics, such as:
RetailX received onboarding workshops and a dedicated success manager for continuous optimization after launch.
Technologies
All recommendation logic is explainable, auditable, and aligned with ethical AI standards.
Marketing teams can adjust algorithm weights and segment rules via an intuitive backend UI.
Built with TensorFlow and trained on anonymized clickstream data to deliver real-time recommendations.
Modular APIs enable easy integration into third-party e-commerce platforms.
All user data is anonymized before processing to meet GDPR and CCPA regulations.
“TVM Engineering helped us truly understand our customers and serve them better. The personalized product recommendations are already driving significant results, and our marketing team loves the flexibility of the dashboard.
Increase in Average Order Value
Higher Conversion from Search
Integrated with both mobile and desktop storefronts, serving millions of users with personalized content in real-time.
2 AI Engineers 2 Frontend Developers 1 Product Manager 1 UX Designer 2 QA Engineers
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