Retailers often struggle to accurately predict customer demand and preferences, leading to inefficient inventory management, lost sales, and increased costs associated with unsold or excess stock. Traditional forecasting methods often fail to capture the nuances of individual customer tastes and evolving trends.

VarietyIQ offers an AI-powered inventory management platform that analyzes historical sales data to provide personalized product assortment recommendations. The platform's machine-learning algorithms identify individual customer preferences and predict demand, enabling retailers to make more informed purchasing decisions. By aligning inventory with customer tastes, VarietyIQ helps retailers optimize their product mix, minimize overstocking, and increase sales. The system goes beyond standard forecasting by identifying products that drive growth based on an understanding of each customer's unique preferences.

Data ingestion module that connects and analyzes historical sales data.

Machine-learning curation engine that tailors product assortment recommendations to individual customer preferences.

AI-driven inventory plans that optimize buying strategies based on past purchase patterns and current inventory.

Identification of incremental sales opportunities by pinpointing styles that drive top-line and bottom-line growth.

Tools for crafting diverse assortments that balance fashion products and enduring best-sellers.

Features to improve operational efficiency by avoiding overbuying and ensuring steady sell-through across the assortment.

VarietyIQ primarily targets apparel retailers, grocery retailers, and wine & beverage retailers seeking to optimize their inventory management and improve sales by aligning product assortments with individual customer preferences.