Algonomy's Mid-Year Release: Doubles Down on Retail-Specific Products with Real-Time CDP, Demand Forecasting and Replenishment Software
SAN FRANCISCO and BENGALURU, India, June 22, 2022 (GLOBE NEWSWIRE) -- Algonomy, the leader in Algorithmic Customer Engagement, Merchandising and Supply Chain Planning, today announced an array of new AI-powered solutions as part of its Mid-year Release for ‘22. This release is aimed at empowering businesses with cutting-edge solutions that bolster topline through conversion rates and lifetime value improvements while also growing the bottomline by controlling cost and revenue leakage.
Algonomy introduces Real-time Customer Data Platform enabling Marketers to drive contextually relevant engagement in the moment. For Merchandising and Supply Chain Planning in grocery, Algonomy introduces version 3.0 of its ‘Right’ suite of products comprising Forecast Right, an AI-driven demand forecasting solution, and Order Right, a replenishment planning product.
“Retail is evolving at a rapid pace to keep up with the shifting needs of customers. Our vast experience in the industry tells us that it needs technology solutions that cater to distinct needs of every industry segment within - Fashion, Grocery, Specialty brands, D2C, and QSR. The products in this release are created to alleviate the growing pains experienced by Retailers and introduce new approaches to meet their customers' needs in the moment,” says Sarath Jarugula, CPO, Algonomy.
Unpacking Algonomy’s mid-year release:
Recommending the most relevant offer or cross-sell product while the customer is in the purchase journey is every Retail Marketers’ dream. Algonomy's CDP utilizes real-time data to drive contextually relevant engagement in seconds - based on latest customer events. Espousing the Design Thinking approach, the platform has a marketer-friendly UX with a simple drag-and-drop interface from data onboarding to audience activation. Streaming data is ingsted into the platform and the Audience Manager helps explore, identify, and activate audience segments automatically, in real-time. It is natively integrated into Algonomy’s Campaign orchestration and Personalization tools and provides out-of-the-box connectors to Shopify and Commerce Tools for real-time orchestration.
Read more about Real-time CDP.
Maintaining the right amount of stock that won’t eat into your capital, minimizing revenue leakage due to out-of-stock situations, and being proactive to changing industry dynamics is what sets winners apart. Algonomy’s Forecast Right sets you firmly on that path with an accurate, scalable and agile demand forecasting solution. With its AI-powered framework, Demand Planners can build thousands of accurate demand forecasts at SKU-location level with a few clicks. It incorporates any internal or external data, automatically pre-processes them, and applies advanced time series, ML & neural networks for demand sensing and optimization.
Read more about Forecast Right.
Stock balance rule-based replenishment solutions have performed poorly in the face of high demand and supply volatility. Algonomy’s intelligent 1-click replenishment optimization solution empowers Demand Planners with reliable order plans that help prevent wastage and loss of sales associated with sub-optimized inventory. It consumes demand forecasts from Forecast Right and optimizes order plans within constraints and parameters such as MOQ, lead time, replenishment frequency, shelf life, expiration dates, and display stock, using custom-built replenishment algorithms. It powers users with advanced features such as future stock predictions, day zero predictive alerts, and risk-based order planning.
Read more about Order Right.
Algonomy is the ONLY Algorithmic Customer Engagement, Merchandise and Supply Chain Planning platform that is made for retail. With 400+ retailers and brands as customers, Algonomy offers a real-time CDP, omnichannel personalization, customer journey orchestration, merchandise analytics, and supplier collaboration solution. More at algonomy.com
Media Contact: Amit Jain, [email protected]