RETAILIGENCE utilizes machine learning algorithms to optimize category management by clustering stores and curating product assortments based on true sales potential rather than historical data. This approach addresses the issue of sales leakage due to poorly assorted stores, enhancing customer satisfaction and operational efficiency.
Funding
$13M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AMGBPAQVFounders
Product
Problem
Retailers often experience sales leakage due to suboptimal category management, resulting in poorly assorted stores that erode customer trust and tie up working capital with slow-selling items. Existing category management systems often rely on historical data, failing to account for a product's true sales potential in specific store locations. Furthermore, there is a lack of effective tools to monitor and rectify in-store operational issues that prevent shoppers from finding what they need.
Solution
Retailigence offers an AI-powered suite of solutions that optimizes category management by clustering stores and curating product assortments based on predicted sales potential. The platform uses machine learning algorithms to analyze retailer data, identify sales leakage, and provide actionable insights for improving store-level assortment and space allocation. Retailigence's intelligent control tower monitors store clusters and assortments, flagging issues and suggesting corrective measures. The X-Ray mobile app enables store staff to monitor on-shelf availability and address operational issues in real-time, ensuring plan compliance and minimizing lost sales.
Target Audience
Retailers seeking to optimize category management, improve store-level assortment, reduce sales leakage, and enhance customer satisfaction are the primary target audience.
Features
- AI-driven store clustering based on multiple attributes, including store revenue, demographics, and local competition
- Assortment optimization that considers a product's true sales potential rather than relying solely on historical data
- Space Modeller to optimize category space allocation based on customer demand
- X-Ray Hub and mobile app to monitor in-store execution, identify issues, and facilitate corrective actions
- Role-based dashboards to monitor business performance against plan and guide issue resolution
- Integration with retailer data to create a credible and optimal customer offer
- User-friendly interface for easy deployment and intuitive use