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Optimizing E-commerce Application with AI-Driven Digital Transformation for A Leading Jewelry Brand

Optimizing E-commerce Application with AI-Driven Digital Transformation for A Leading Jewelry Brand

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    Technology Stack

    Salesforce Commerce Cloud

    Salesforce Marketing Cloud


    Open AI

    Lama 2


    SQL Server

    Client Overview

    The Client is a global retailer of fashion jewelry and lifestyle accessories on its proprietary TV home shopping and e-commerce platforms.


    The client sought to optimize their e-commerce platform by leveraging AI-powered inventory management, demand forecasting, personalized recommendations, and anomaly detection.


    Q3 team provided an AIOps solution utilizing deep learning for inventory management, demand forecasting, and anomaly detection. Coupled with a personalized recommendation engine, it optimizes the e-commerce platform, enabling strategic decision-making and sales growth.

    • AI-Powered Inventory Management: Integrated a generative AI frontend interface for dynamic inventory visualization and real-time stock recommendations. Deep learning models analyze historical data, trends, and external factors, optimizing inventory levels.
    • Advanced Demand Forecasting with Deep Learning: Leveraged generative AI for intuitive visualizations of demand trends and uncertainties. Deep learning algorithms analyze extensive data sources for accurate forecasts.
    • Personalized Recommendations through DataOps and AIOps: Leveraging deep learning techniques like Gradient Boosting Tree and Wide & Deep models, our recommendation system delivered tailored product suggestions based on customer data.
    • Anomaly Detection using Deep Learning: Deployed Graph Neural Networks (GNNs) for intuitive anomaly visualization and root cause analysis. GNNs also captured complex relationships within transactional data.


    10-15% New Customer Acquisition
    New Market Opportunities
    20% Increase in Sales Conversion
    Optimized Inventory Management

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