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Maximize profitability through AI-driven menu engineering. Leverage insights on top-selling items, popular combos, food costs to optimize menu mix.
Director of Finance
CFO
CMO, McDonald's India
Restaurant Analytics is developed to support both brand use cases and franchise use cases. In the case of a brand, data from all the franchises of the brand will be standardized and consolidated to give a single view of the brand and how each franchise is performing.
In the case of a franchise, data from multiple brands operated by the franchise will be standardized and consolidated to give the franchise a view of how various brands are performing across different regions and across all metrics.
Algonomy ingests data from structured & unstructured data sources such as Point Of Sale, Front and Back-office systems, Kitchen systems, Delivery systems, Guest Experience Surveys, Learning Management System, Restaurant Compliance systems and other related platforms to create a single source of truth for use by various modules within Restaurant Analytics.
Alerts can be set in the application if there are any drops or unusual increases in specific metrics. For e.g., if the revenue growth drops for certain stores or some stores are not reporting a new combo launched then the tool can be configured to send auto scheduled reports & insights triggering relevant users.
Algonomy’s platform can handle late polling and process back-dated data up to a pre-defined number of days. Our platform handles 7 to 15 days late polling on a daily basis and on weekends we handle 15-30 days of late polling. This is a configurable parameter which can be modified at any point of time.
Restaurant Analytics supports both real-time and batch data. Typically, our customers push all their online order data in real-time in order to analyze sales, traffic, performance of new combo, deals launched, etc.
Restaurant Analytics comes with complete user-role-security-control, where any user can be restricted to a specific store or region or report or metrics.