Retailigence

Retailigence provides a suite of artificial intelligence-driven solutions designed to enhance category management for brick-and-mortar retailers. The company was founded in 2018 by a team with extensive experience in data science and retail, including Sid Sarangi, who previously served as CIO for retailer Kazyon and founded a retail consulting firm with clients like Tesco and Selfridges. Retailigence is headquartered in London, with a presence in India and the US.

The firm's core business revolves around a cloud-based, machine-learning platform that helps retailers optimize in-store performance by tackling issues of product assortment, space allocation, and operational inefficiencies. This SaaS (Software as a Service) platform is designed to integrate with existing retailer systems, such as POS and CRM, to analyze vast amounts of data without bias. By analyzing customer basket data, the system moves beyond historical sales analysis to offer future-facing insights, aiming to increase sales by 3-5% and reduce waste. The business model is primarily subscription-based, with pricing tiers that vary by the number of users and scale of implementation.

Retailigence's AI suite includes several key applications. The Store Clustering tool groups stores based on nuanced customer behavior rather than simple geographic or sales data. Assortment Optimization then uses these clusters to tailor product ranges for each specific store, ensuring the right products are in the right locations. Another feature, the Space Modeller, helps allocate shelf space to categories based on their potential. To address operational issues, the X-Ray Hub and mobile app identify and flag problems like out-of-stock items, incorrect pricing, or poor displays that lead to lost sales. This allows for rapid correction of in-store problems. Clients include major European retailers, grocers in the Middle East and South Africa, and electronics giants.

Keywords: retail analytics, category management, AI in retail, machine learning for retail, assortment optimization, store clustering, space allocation, operational efficiency, retail data science, customer basket analysis, SaaS for retail, in-store analytics, retail technology, merchandise planning, demand forecasting, inventory optimization, retail performance management, customer segmentation, data-driven retail, lost sales reduction