Pakarillc

M.GEMI

Luxury Footwear Retailer

Before Optimization

M.Gemi, an online luxury footwear retailer, faced challenges in managing inventory for its high-end, handcrafted shoes. Due to the nature of their products and the need to maintain exclusivity, it was crucial to manage inventory tightly to avoid both stockouts and excess inventory.

AI Implementation

M.Gemi implemented an AI-driven inventory management system that uses machine learning algorithms to predict customer demand and optimize inventory levels. The system analyzes sales data, customer preferences, and seasonal trends to ensure the right products are available in the right quantities.

After Optimization

The AI system helped M.Gemi reduce stockouts, ensuring popular sizes and styles were always available, which improved ustomer satisfaction and sales. Additionally, by optimizing inventory levels, the company was able to minimize excess stock, reducing the need for discounting and maintaining the brand’s premium image.

AI-driven inventory management software specifically designed for small to medium-sized
businesses. It offers a comprehensive set of tools to manage inventory, orders, and customer
relationships, leveraging AI to optimize stock levels and streamline operations.

Key Features

Demand Forecasting

AI to analyze historical sales data and predict future demand, helping businesses maintain optimal inventory levels.

Automated Reordering

The system automatically generates purchase orders based on forecasted demand and current stock levels, reducing the risk of stockouts and overstocking.

Multi-Channel Management

Integrates with various sales channels (e.g., Shopify, Amazon) to synchronize inventory across platforms, ensuring accurate stock levels in real time.

Insights and Reporting

The software provides AI-driven insights and reports, helping businesses identify trends, optimize pricing strategies, and improve overall inventory management.

Inventory Management

Scenario: M.Gemi's Inventory Management

Before AI-Driven Optimization

Before AI-Driven Optimization
After AI-Driven Optimization

After AI-Driven Optimization

Let’s assume the AI system reduces stockouts by 80% and excess inventory by 60%.

Before vs. After Comparison

Before vs After Comparison

Net Impact

Total Improvement (Revenue Increase + Cost Reduction):

$160,000 (Revenue Increase) + $243,000 (Cost Reduction) = $403,000 improvement per month.

Explanation

Revenue Increase

The reduction in stockouts allowed M.Gemi to sell 400 more pairs of shoes, increasing monthly revenue by $160,000.

Cost Reduction

By reducing excess inventory and stockouts, the company saved $243,000 in costs related to storage and lost sales.

This example demonstrates the significant financial impact that AI-driven inventory optimization
can have on a luxury retailer like M.Gemi. By better aligning inventory levels with customer demand, M.Gemi can not only boost sales but also reduce unnecessary costs, leading to a more profitable and efficient operation.

Scroll to Top