Boosting Sales with an AI-Powered Recommendation Engine 

Overview

Turning Data into Sales: Smarter Product Discovery

An online shopping platform wanted to help customers find the right products faster and improve overall sales. We built a recommendation engine that studies user behavior, purchase history, and browsing patterns to suggest the most relevant products in real time.

This made shopping more personal, increased customer satisfaction, and led to higher conversions and larger cart values.

Services

- content-based filtering - capture clickstream - model training and deployment

Industry Type

- Ecommerce

Challenges

  • - Generic, Non-Engaging Recommendations
  • - Prior systems relied on trending or static logic, delivering low personalization and minimal user engagement
  • - Lack of Real-Time Adaptation
  • - The system couldn’t react mid-session—e.g., when customers shift from low- to high-priced categories
  • - Data Quality & Cold-Start Issues
  • - Poor or sparse historical data for new users/items hindered recommendation quality.
  • - Balancing Personalization with Merchandising Goals
  • - Aligning AI-driven suggestions with business priorities—like inventory focus and promotional strategy—necessitated constant experimentation.

Outcomes

  • - 52% Increase in Click-Through Rate
  • - Personalized carousels saw significantly higher engagement
  • - 35% Uplift in Add-to-Cart Actions
  • - Tailored recommendations drove more direct buying intent.
  • - 25% Growth in Average Order Value (AOV)
  • - Intelligent cross-selling and upselling increased cart value
  • - 30% Improvement in Homepage-to-Product Transitions
  • - Users clicked through recommended products more efficiently

Technology Stack

PHP PHP
Laravel Laravel
Python Microservices Python Microservices
MySQL MySQL
Laravel Horizon Laravel Horizon
Redis Redis
Google Vertex AI Google Vertex AI
TensorFlow TensorFlow

Project Solutions

  • • Deliver Personalized Shopping: Built an AI-powered recommendation engine that suggests products based on browsing history, past purchases, and real-time behavior.
  • • Boost Conversions: Implemented dynamic product carousels (e.g., “Recommended for You,” “Frequently Bought Together”) to drive higher click-through and add-to-cart actions.
  • • Enhance Customer Experience: Designed a smooth shopping journey with real-time updates, ensuring customers see relevant items during their session.
  • • Support Business Goals: Balanced personalization with promotional strategies by integrating seasonal campaigns, offers, and inventory priorities into recommendations.

Take the next step

Let's Build Remarkable Products Together!

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