Case Study

Revolutionizing Retail Engagement with AI-Powered Personalization & Pricing Intelligence

Retail / E-commerce

Discover how Keylent delivered a 90% increase in customer engagement and a 60% boost in conversion rates by powering real-time personalization and adaptive pricing.

Project Overview

A fast-scaling e-commerce company struggled to deliver personalized experiences across its growing customer base. Static listings, generic promotions, and rigid pricing models limited engagement and conversions. Keylent built a Smart Retail App that leveraged behavioral data, purchase history, and inventory dynamics to deliver hyper personalized recommendations and intelligent pricing adjustments, creating a seamless shopping experience that adapts to each user.

Key Challenges

Low Personalization in Product Discovery

Static Pricing Models

Inventory & Demand Mismatch

Fragmented Customer Data

Our Solution

  • Recommendation Engine
  • Dynamic Pricing Intelligence
  • 360° Customer Profiles
  • Real-Time Engagement Dashboards

Key Technologies

PyTorch & Scikit-learn for recommendation and pricing modelsAWS SageMaker for scalable training and deploymentReact Native for cross-platform app developmentSnowflake for unified customer data warehousingPower BI for engagement and conversion analytics

Impact

90%

Increase in customer engagement

60%

Boost in conversion rates

70%

Improvement in inventory turnover efficiency

Client Testimonial

“The personalized recommendations feel intuitive and relevant, and the dynamic pricing engine keeps us competitive while maximizing margins. Users spend more time and buy more.”

— VP of Product, Leading E-Commerce Platform